Find, fix and prevent vulnerabilities in your code.
critical severity
- Vulnerable module: knex
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
knex is a query builder for PostgreSQL, MySQL and SQLite3
Affected versions of this package are vulnerable to SQL Injection. None
Remediation
Upgrade knex
to version 0.19.5 or higher.
References
critical severity
- Vulnerable module: hawk
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
hawk is a library for the HTTP Hawk Authentication Scheme.
Affected versions of this package are vulnerable to Authentication Bypass. The incoming (client supplied) hash of the payload is trusted by the server and not verified before the signature is calculated.
A malicious actor in the middle can alter the payload and the server side will not identify the modification occurred because it simply uses the client provided value instead of verify the hash provided against the modified payload.
According to the maintainers this issue is to be considered out of scope as "payload hash validation is optional and up to developer to implement".
Remediation
There is no fixed version for hawk
.
References
high severity
- Vulnerable module: knex
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
knex is a query builder for PostgreSQL, MySQL and SQLite3
Affected versions of this package are vulnerable to SQL Injection due to missing escape of field objects, which allows ignoring the WHERE
clause of a SQL
query.
Note:
Exploiting this vulnerability is possible when using MySQL
DB.
PoC
const knex = require('knex')({
client: 'mysql2',
connection: {
host: '127.0.0.1',
user: 'root',
password: 'supersecurepassword',
database: 'poc',
charset: 'utf8'
}
})
knex.schema.hasTable('users').then((exists) => {
if (!exists) {
knex.schema.createTable('users', (table) => {
table.increments('id').primary()
table.string('name').notNullable()
table.string('secret').notNullable()
}).then()
knex('users').insert({
name: "admin",
secret: "you should not be able to return this!"
}).then()
knex('users').insert({
name: "guest",
secret: "hello world"
}).then()
}
})
attackerControlled = {
"name": "admin"
}
knex('users')
.select()
.where({secret: attackerControlled})
.then((userSecret) => console.log(userSecret))
Remediation
Upgrade knex
to version 2.4.0 or higher.
References
high severity
- Vulnerable module: nodemailer
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
nodemailer is an Easy as cake e-mail sending from your Node.js applications
Affected versions of this package are vulnerable to Command Injection. Use of crafted recipient email addresses may result in arbitrary command flag injection in sendmail transport for sending mails.
PoC
[email protected] (-bi Initialize the alias database.)
[email protected] (The option -d0.1 prints the version of sendmail and the options it was compiled with.)
[email protected] (Debug output ffile)
Remediation
Upgrade nodemailer
to version 6.4.16 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Write. node-tar
aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.
This logic was insufficient when extracting tar
files that contained both a directory and a symlink with the same name as the directory, where the symlink and directory names in the archive entry used backslashes as a path separator on posix systems. The cache checking logic used both \
and /
characters as path separators. However, \
is a valid filename character on posix systems.
By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar
symlink checks on directories, essentially allowing an untrusted tar
file to symlink into an arbitrary location. This can lead to extracting arbitrary files into that location, thus allowing arbitrary file creation and overwrite.
Additionally, a similar confusion could arise on case-insensitive filesystems. If a tar
archive contained a directory at FOO
, followed by a symbolic link named foo
, then on case-insensitive file systems, the creation of the symbolic link would remove the directory from the filesystem, but not from the internal directory cache, as it would not be treated as a cache hit. A subsequent file entry within the FOO
directory would then be placed in the target of the symbolic link, thinking that the directory had already been created.
Remediation
Upgrade tar
to version 6.1.7, 5.0.8, 4.4.16 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Write. node-tar
aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat calls to determine whether a given path is a directory, paths are cached when directories are created.
This logic is insufficient when extracting tar
files that contain two directories and a symlink with names containing unicode values that normalized to the same value. Additionally, on Windows systems, long path portions would resolve to the same file system entities as their 8.3 "short path" counterparts.
A specially crafted tar
archive can include directories with two forms of the path that resolve to the same file system entity, followed by a symbolic link with a name in the first form, lastly followed by a file using the second form. This leads to bypassing node-tar
symlink checks on directories, essentially allowing an untrusted tar
file to symlink into an arbitrary location and extracting arbitrary files into that location.
Remediation
Upgrade tar
to version 6.1.9, 5.0.10, 4.4.18 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Write. node-tar
aims to guarantee that any file whose location would be outside of the extraction target directory is not extracted. This is, in part, accomplished by sanitizing absolute paths of entries within the archive, skipping archive entries that contain ..
path portions, and resolving the sanitized paths against the extraction target directory.
This logic is insufficient on Windows systems when extracting tar
files that contain a path that is not an absolute path, but specify a drive letter different from the extraction target, such as C:some\path
. If the drive letter does not match the extraction target, for example D:\extraction\dir
, then the result of path.resolve(extractionDirectory, entryPath)
resolves against the current working directory on the C:
drive, rather than the extraction target directory.
Additionally, a ..
portion of the path can occur immediately after the drive letter, such as C:../foo
, and is not properly sanitized by the logic that checks for ..
within the normalized and split portions of the path.
Note: This only affects users of node-tar
on Windows systems.
Remediation
Upgrade tar
to version 6.1.9, 5.0.10, 4.4.18 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient symlink protection.
node-tar
aims to guarantee that any file whose location would be modified by a symbolic link is not extracted. This is, in part, achieved by ensuring that extracted directories are not symlinks. Additionally, in order to prevent unnecessary stat
calls to determine whether a given path is a directory, paths are cached when directories are created.
This logic is insufficient when extracting tar files that contain both a directory and a symlink with the same name as the directory. This order of operations results in the directory being created and added to the node-tar
directory cache. When a directory is present in the directory cache, subsequent calls to mkdir
for that directory are skipped.
However, this is also where node-tar
checks for symlinks occur. By first creating a directory, and then replacing that directory with a symlink, it is possible to bypass node-tar
symlink checks on directories, essentially allowing an untrusted tar file to symlink into an arbitrary location and subsequently extracting arbitrary files into that location.
Remediation
Upgrade tar
to version 3.2.3, 4.4.15, 5.0.7, 6.1.2 or higher.
References
high severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Arbitrary File Overwrite. This is due to insufficient absolute path sanitization.
node-tar
aims to prevent extraction of absolute file paths by turning absolute paths into relative paths when the preservePaths
flag is not set to true
. This is achieved by stripping the absolute path root from any absolute file paths contained in a tar file. For example, the path /home/user/.bashrc
would turn into home/user/.bashrc
.
This logic is insufficient when file paths contain repeated path roots such as ////home/user/.bashrc
. node-tar
only strips a single path root from such paths. When given an absolute file path with repeating path roots, the resulting path (e.g. ///home/user/.bashrc
) still resolves to an absolute path.
Remediation
Upgrade tar
to version 3.2.2, 4.4.14, 5.0.6, 6.1.1 or higher.
References
high severity
- Vulnerable module: ajv
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
ajv is an Another JSON Schema Validator
Affected versions of this package are vulnerable to Prototype Pollution. A carefully crafted JSON schema could be provided that allows execution of other code by prototype pollution. (While untrusted schemas are recommended against, the worst case of an untrusted schema should be a denial of service, not execution of code.)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade ajv
to version 6.12.3 or higher.
References
high severity
- Vulnerable module: ansi-regex
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]*
and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*
.
PoC
import ansiRegex from 'ansi-regex';
for(var i = 1; i <= 50000; i++) {
var time = Date.now();
var attack_str = "\u001B["+";".repeat(i*10000);
ansiRegex().test(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ansi-regex
to version 3.0.1, 4.1.1, 5.0.1, 6.0.1 or higher.
References
high severity
- Vulnerable module: dicer
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
Overview
Affected versions of this package are vulnerable to Denial of Service (DoS). A malicious attacker can send a modified form to server, and crash the nodejs service. An attacker could sent the payload again and again so that the service continuously crashes.
PoC
await fetch('https://127.0.0.1:8000', { method: 'POST', headers: { ['content-type']: 'multipart/form-data; boundary=----WebKitFormBoundaryoo6vortfDzBsDiro', ['content-length']: '145', connection: 'keep-alive', }, body: '------WebKitFormBoundaryoo6vortfDzBsDiro\r\n Content-Disposition: form-data; name="bildbeschreibung"\r\n\r\n\r\n------WebKitFormBoundaryoo6vortfDzBsDiro--' });
Remediation
There is no fixed version for dicer
.
References
high severity
- Vulnerable module: fresh
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
fresh
is HTTP response freshness testing.
Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. A Regular Expression (/ *, */
) was used for parsing HTTP headers and take about 2 seconds matching time for 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade fresh
to version 0.5.2 or higher.
References
high severity
- Vulnerable module: html-to-text
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
html-to-text is an Advanced html to plain text converter
Affected versions of this package are vulnerable to Denial of Service (DoS). The application may crash when the parsed HTML is either very deep or has a big amount of DOM elements.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade html-to-text
to version 6.0.0 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution through the zipObjectDeep
function due to improper user input sanitization in the baseZipObject
function.
PoC
lodash.zipobjectdeep:
const zipObjectDeep = require("lodash.zipobjectdeep");
let emptyObject = {};
console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined
zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function
console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true
lodash:
const test = require("lodash");
let emptyObject = {};
console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined
test.zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function
console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.17 or higher.
References
high severity
- Vulnerable module: minimatch
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via complicated and illegal regexes.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade minimatch
to version 3.0.2 or higher.
References
high severity
- Vulnerable module: minimatch
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS).
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade minimatch
to version 3.0.2 or higher.
References
high severity
- Vulnerable module: moment
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Directory Traversal when a user provides a locale string which is directly used to switch moment locale.
Details
A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.
Directory Traversal vulnerabilities can be generally divided into two types:
- Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.
st
is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public
route.
If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.
curl https://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa
Note %2e
is the URL encoded version of .
(dot).
- Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as
Zip-Slip
.
One way to achieve this is by using a malicious zip
archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip
archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
2018-04-15 22:04:29 ..... 19 19 good.txt
2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade moment
to version 2.29.2 or higher.
References
high severity
- Vulnerable module: negotiator
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
negotiator is an HTTP content negotiator for Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS)
when parsing Accept-Language
http header.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade negotiator
to version 0.6.1 or higher.
References
high severity
- Vulnerable module: nth-check
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) when parsing crafted invalid CSS nth-checks, due to the sub-pattern \s*(?:([+-]?)\s*(\d+))?
in RE_NTH_ELEMENT
with quantified overlapping adjacency.
PoC
var nthCheck = require("nth-check")
for(var i = 1; i <= 50000; i++) {
var time = Date.now();
var attack_str = '2n' + ' '.repeat(i*10000)+"!";
try {
nthCheck.parse(attack_str)
}
catch(err) {
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade nth-check
to version 2.0.1 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Override Protection Bypass. By default qs
protects against attacks that attempt to overwrite an object's existing prototype properties, such as toString()
, hasOwnProperty()
,etc.
From qs
documentation:
By default parameters that would overwrite properties on the object prototype are ignored, if you wish to keep the data from those fields either use plainObjects as mentioned above, or set allowPrototypes to true which will allow user input to overwrite those properties. WARNING It is generally a bad idea to enable this option as it can cause problems when attempting to use the properties that have been overwritten. Always be careful with this option.
Overwriting these properties can impact application logic, potentially allowing attackers to work around security controls, modify data, make the application unstable and more.
In versions of the package affected by this vulnerability, it is possible to circumvent this protection and overwrite prototype properties and functions by prefixing the name of the parameter with [
or ]
. e.g. qs.parse("]=toString")
will return {toString = true}
, as a result, calling toString()
on the object will throw an exception.
Example:
qs.parse('toString=foo', { allowPrototypes: false })
// {}
qs.parse("]=toString", { allowPrototypes: false })
// {toString = true} <== prototype overwritten
For more information, you can check out our blog.
Disclosure Timeline
- February 13th, 2017 - Reported the issue to package owner.
- February 13th, 2017 - Issue acknowledged by package owner.
- February 16th, 2017 - Partial fix released in versions
6.0.3
,6.1.1
,6.2.2
,6.3.1
. - March 6th, 2017 - Final fix released in versions
6.4.0
,6.3.2
,6.2.3
,6.1.2
and6.0.4
Remediation
Upgrade qs
to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Poisoning which allows attackers to cause a Node process to hang, processing an Array object whose prototype has been replaced by one with an excessive length value.
Note: In many typical Express use cases, an unauthenticated remote attacker can place the attack payload in the query string of the URL that is used to visit the application, such as a[__proto__]=b&a[__proto__]&a[length]=100000000
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade qs
to version 6.2.4, 6.3.3, 6.4.1, 6.5.3, 6.6.1, 6.7.3, 6.8.3, 6.9.7, 6.10.3 or higher.
References
high severity
- Vulnerable module: semver
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
semver is a semantic version parser used by npm.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range
, when untrusted user data is provided as a range.
PoC
const semver = require('semver')
const lengths_2 = [2000, 4000, 8000, 16000, 32000, 64000, 128000]
console.log("n[+] Valid range - Test payloads")
for (let i = 0; i =1.2.3' + ' '.repeat(lengths_2[i]) + '<1.3.0';
const start = Date.now()
semver.validRange(value)
// semver.minVersion(value)
// semver.maxSatisfying(["1.2.3"], value)
// semver.minSatisfying(["1.2.3"], value)
// new semver.Range(value, {})
const end = Date.now();
console.log('length=%d, time=%d ms', value.length, end - start);
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade semver
to version 5.7.2, 6.3.1, 7.5.2 or higher.
References
high severity
- Vulnerable module: sqlite3
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Denial of Service (DoS) which will invoke the toString function of the passed parameter. If passed an invalid Function object it will throw and crash the V8 engine.
PoC
let sqlite3 = require('sqlite3').verbose();
let db = new sqlite3.Database(':memory:');
db.serialize(function() {
db.run("CREATE TABLE lorem (info TEXT)");
db.run("INSERT INTO lorem VALUES (?)", [{toString: 23}]);
});
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
Upgrade sqlite3
to version 5.0.3 or higher.
References
high severity
- Vulnerable module: hawk
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
hawk is a library for the HTTP Hawk Authentication Scheme.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in header parsing where each added character in the attacker's input increases the computation time exponentially.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade hawk
to version 9.0.1 or higher.
References
high severity
- Vulnerable module: aws-sdk
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Prototype Pollution. If an attacker submits a malicious INI file to an application that parses it with loadSharedConfigFiles
, they will pollute the prototype on the application. This can be exploited further depending on the context.
PoC by Eugene Lim:
payload.toml:
[__proto__]
polluted = "polluted"
poc.js:
var fs = require('fs')
var sharedIniFileLoader = require('@aws-sdk/shared-ini-file-loader')
async function main() {
var parsed = await sharedIniFileLoader.loadSharedConfigFiles({ filepath: './payload.toml' })
console.log(parsed)
console.log(parsed.__proto__)
console.log({}.__proto__)
console.log(polluted)
}
main()
> node poc.js
{
configFile: { default: { region: 'ap-southeast-1' } },
credentialsFile: {}
}
{ polluted: '"polluted"' }
{ polluted: '"polluted"' }
"polluted"
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade aws-sdk
to version 2.814.0 or higher.
References
high severity
- Vulnerable module: follow-redirects
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Improper Input Validation due to the improper handling of URLs by the url.parse()
function. When new URL()
throws an error, it can be manipulated to misinterpret the hostname. An attacker could exploit this weakness to redirect traffic to a malicious site, potentially leading to information disclosure, phishing attacks, or other security breaches.
PoC
# Case 1 : Bypassing localhost restriction
let url = 'https://[localhost]/admin';
try{
new URL(url); // ERROR : Invalid URL
}catch{
url.parse(url); // -> https://localhost/admin
}
# Case 2 : Bypassing domain restriction
let url = 'https://attacker.domain*.allowed.domain:a';
try{
new URL(url); // ERROR : Invalid URL
}catch{
url.parse(url); // -> https://attacker.domain/*.allowed.domain:a
}
Remediation
Upgrade follow-redirects
to version 1.15.4 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
using a constructor
payload.
PoC by Snyk
const mergeFn = require('lodash').defaultsDeep;
const payload = '{"constructor": {"prototype": {"a0": true}}}'
function check() {
mergeFn({}, JSON.parse(payload));
if (({})[`a0`] === true) {
console.log(`Vulnerable to Prototype Pollution via ${payload}`);
}
}
check();
For more information, check out our blog post
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.12 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution via the set
and setwith
functions due to improper user input sanitization.
PoC
lod = require('lodash')
lod.set({}, "__proto__[test2]", "456")
console.log(Object.prototype)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.17 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The functions merge
, mergeWith
, and defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
. This is due to an incomplete fix to CVE-2018-3721
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
high severity
- Vulnerable module: static-eval
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
static-eval evaluates statically-analyzable expressions.
Affected versions of this package are vulnerable to Arbitrary Code Execution. It passes untrusted user input directly to the global function constructor, resulting in an arbitrary code execution vulnerability when user input is parsed via the package.
Proof of concept
var evaluate = require('static-eval');
var parse = require('esprima').parse;
var src = process.argv[2];
var payload = '(function({x}){return x.constructor})({x:"".sub})("console.log(process.env)")()'
var ast = parse(payload).body[0].expression;
console.log(evaluate(ast, {x:1}));
Remediation
Upgrade static-eval
to version 2.0.2 or higher.
References
high severity
- Vulnerable module: static-eval
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
static-eval
is a module to evaluate statically-analyzable expressions.
Affected versions of the package are vulnerable to Arbitrary Code Execution. If un-sanitized user input is passed to static-eval
, it is possible to break out of the sandboxed instance, and execute arbitrary code from the standard library.
Remediation
Upgrade static-eval
to version 2.0.0 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Code Injection via template
.
PoC
var _ = require('lodash');
_.template('', { variable: '){console.log(process.env)}; with(obj' })()
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
medium severity
- Vulnerable module: morgan
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
morgan is a HTTP request logger middleware for node.js.
Affected versions of this package are vulnerable to Arbitrary Code Injection. An attacker could use the format parameter to inject arbitrary commands.
Remediation
Upgrade morgan
to version 1.9.1 or higher.
References
medium severity
- Vulnerable module: follow-redirects
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Information Exposure due to the handling of the Proxy-Authorization
header across hosts. When using a dependent library, it only clears the authorization header during cross-domain redirects but allows the proxy-authentication header, which contains credentials, to persist. This behavior may lead to the unintended leakage of credentials if an attacker can trigger a cross-domain redirect and capture the persistent proxy-authentication header.
PoC
const axios = require('axios');
axios.get('https://127.0.0.1:10081/',{
headers: {
'AuThorization': 'Rear Test',
'ProXy-AuthoriZation': 'Rear Test',
'coOkie': 't=1'
}
}).then(function (response) {
console.log(response);
})
Remediation
Upgrade follow-redirects
to version 1.15.6 or higher.
References
medium severity
- Vulnerable module: request
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
Overview
request is a simplified http request client.
Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to insufficient checks in the lib/redirect.js
file by allowing insecure redirects in the default configuration, via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).
NOTE: request
package has been deprecated, so a fix is not expected. See https://github.com/request/request/issues/3142.
Remediation
A fix was pushed into the master
branch but not yet published.
References
medium severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Uncontrolled Resource Consumption ('Resource Exhaustion') due to the lack of folders count validation during the folder creation process. An attacker who generates a large number of sub-folders can consume memory on the system running the software and even crash the client within few seconds of running it using a path with too many sub-folders inside.
Remediation
Upgrade tar
to version 6.2.1 or higher.
References
medium severity
- Vulnerable module: tough-cookie
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.
Affected versions of this package are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false
mode. Due to an issue with the manner in which the objects are initialized, an attacker can expose or modify a limited amount of property information on those objects. There is no impact to availability.
PoC
// PoC.js
async function main(){
var tough = require("tough-cookie");
var cookiejar = new tough.CookieJar(undefined,{rejectPublicSuffixes:false});
// Exploit cookie
await cookiejar.setCookie(
"Slonser=polluted; Domain=__proto__; Path=/notauth",
"https://__proto__/admin"
);
// normal cookie
var cookie = await cookiejar.setCookie(
"Auth=Lol; Domain=google.com; Path=/notauth",
"https://google.com/"
);
//Exploit cookie
var a = {};
console.log(a["/notauth"]["Slonser"])
}
main();
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade tough-cookie
to version 4.1.3 or higher.
References
medium severity
- Vulnerable module: hoek
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
hoek is an Utility methods for the hapi ecosystem.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade hoek
to version 4.2.1, 5.0.3 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.5 or higher.
References
medium severity
- Vulnerable module: nodemailer
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
nodemailer is an Easy as cake e-mail sending from your Node.js applications
Affected versions of this package are vulnerable to HTTP Header Injection if unsanitized user input that may contain newlines and carriage returns is passed into an address object.
PoC:
const userEmail = '[email protected]: foobar'; // imagine this comes from e.g. HTTP request params or is otherwise user-controllable
await transporter.sendMail({
from: '...',
to: '...',
replyTo: {
name: 'Customer',
address: userEmail,
},
subject: 'My Subject',
text: message,
});
Remediation
Upgrade nodemailer
to version 6.6.1 or higher.
References
medium severity
- Vulnerable module: inflight
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]
Overview
Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime via the makeres
function due to improperly deleting keys from the reqs
object after execution of callbacks. This behavior causes the keys to remain in the reqs
object, which leads to resource exhaustion.
Exploiting this vulnerability results in crashing the node
process or in the application crash.
Note: This library is not maintained, and currently, there is no fix for this issue. To overcome this vulnerability, several dependent packages have eliminated the use of this library.
To trigger the memory leak, an attacker would need to have the ability to execute or influence the asynchronous operations that use the inflight module within the application. This typically requires access to the internal workings of the server or application, which is not commonly exposed to remote users. Therefore, “Attack vector” is marked as “Local”.
PoC
const inflight = require('inflight');
function testInflight() {
let i = 0;
function scheduleNext() {
let key = `key-${i++}`;
const callback = () => {
};
for (let j = 0; j < 1000000; j++) {
inflight(key, callback);
}
setImmediate(scheduleNext);
}
if (i % 100 === 0) {
console.log(process.memoryUsage());
}
scheduleNext();
}
testInflight();
Remediation
There is no fixed version for inflight
.
References
medium severity
- Vulnerable module: express
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
express is a minimalist web framework.
Affected versions of this package are vulnerable to Open Redirect due to the implementation of URL encoding using encodeurl
before passing it to the location
header. This can lead to unexpected evaluations of malformed URLs by common redirect allow list implementations in applications, allowing an attacker to bypass a properly implemented allow list and redirect users to malicious sites.
Remediation
Upgrade express
to version 4.19.2, 5.0.0-beta.3 or higher.
References
medium severity
- Vulnerable module: moment
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
moment
is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of the package are vulnerable to Regular Expression Denial of Service (ReDoS) attacks for any locale that has separate format and standalone options and format
input can be controlled by the user.
An attacker can provide a specially crafted input to the format
function, which nearly matches the pattern being matched. This will cause the regular expression matching to take a long time, all the while occupying the event loop and preventing it from processing other requests and making the server unavailable (a Denial of Service attack).
Disclosure Timeline
- October 19th, 2016 - Reported the issue to package owner.
- October 19th, 2016 - Issue acknowledged by package owner.
- October 24th, 2016 - Issue fixed and version
2.15.2
released.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
References
medium severity
- Vulnerable module: minimist
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype
using a constructor
or __proto__
payload.
PoC by Snyk
require('minimist')('--__proto__.injected0 value0'.split(' '));
console.log(({}).injected0 === 'value0'); // true
require('minimist')('--constructor.prototype.injected1 value1'.split(' '));
console.log(({}).injected1 === 'value1'); // true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 0.2.1, 1.2.3 or higher.
References
medium severity
- Vulnerable module: underscore
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
underscore is a JavaScript's functional programming helper library.
Affected versions of this package are vulnerable to Arbitrary Code Injection via the template
function, particularly when the variable
option is taken from _.templateSettings
as it is not sanitized.
PoC
const _ = require('underscore');
_.templateSettings.variable = "a = this.process.mainModule.require('child_process').execSync('touch HELLO')";
const t = _.template("")();
Remediation
Upgrade underscore
to version 1.13.0-2, 1.12.1 or higher.
References
medium severity
- Vulnerable module: express-hbs
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
express-hbs is an Express handlebars template engine complete with multiple layouts, partials and blocks.
Affected versions of this package are vulnerable to Information Exposure. The layout
parameter may trigger file disclosure vulnerabilities in downstream applications. This potential vulnerability is somewhat restricted in that only files with existing extensions (i.e. file.extension
) can be included, files that lack an extension will have .hbs
appended to them.
Remediation
Upgrade express-hbs
to version 2.4.0 or higher.
References
medium severity
- Vulnerable module: follow-redirects
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Information Exposure by leaking the cookie header to a third party site in the process of fetching a remote URL with the cookie in the request body. If the response contains a location
header, it will follow the redirect to another URL of a potentially malicious actor, to which the cookie would be exposed.
Remediation
Upgrade follow-redirects
to version 1.14.7 or higher.
References
medium severity
- Vulnerable module: jison
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]
Overview
jison is a package that provides an API for creating parsers in JavaScript.
Affected versions of this package are vulnerable to Command Injection. Arbitrary OS shell command execution is possible through a crafted command-line argument.
Remediation
There is no fixed version for jison
.
References
medium severity
- Vulnerable module: js-beautify
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
js-beautify is a reformat and re-indent bookmarklets, ugly JavaScript, unpack scripts packed by Dean Edward’s popular packer, as well as partly deobfuscate scripts processed by the npm package "javascript-obfuscator".
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an unsafe regex in tokenizer.py
and tokenizer.js
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade js-beautify
to version 1.14.1 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the toNumber
, trim
and trimEnd
functions.
POC
var lo = require('lodash');
function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret + "1";
}
var s = build_blank(50000)
var time0 = Date.now();
lo.trim(s)
var time_cost0 = Date.now() - time0;
console.log("time_cost0: " + time_cost0)
var time1 = Date.now();
lo.toNumber(s)
var time_cost1 = Date.now() - time1;
console.log("time_cost1: " + time_cost1)
var time2 = Date.now();
lo.trimEnd(s)
var time_cost2 = Date.now() - time2;
console.log("time_cost2: " + time_cost2)
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
medium severity
- Vulnerable module: minimatch
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the braceExpand
function in minimatch.js
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade minimatch
to version 3.0.5 or higher.
References
medium severity
- Vulnerable module: nodemailer
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
nodemailer is an Easy as cake e-mail sending from your Node.js applications
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the attachDataUrls
parameter or when parsing attachments with an embedded file. An attacker can exploit this vulnerability by sending a specially crafted email that triggers inefficient regular expression evaluation, leading to excessive consumption of CPU resources.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade nodemailer
to version 6.9.9 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isSlug
function
PoC
var validator = require("validator")
function build_attack(n) {
var ret = "111"
for (var i = 0; i < n; i++) {
ret += "a"
}
return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isSlug(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isHSL
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = "hsla(0"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
if (i % 1000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isHSL(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isEmail
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = ""
for (var i = 0; i < n; i++) {
ret += "<"
}
return ret+"";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isEmail(attack_str,{ allow_display_name: true })
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: xml2js
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Prototype Pollution due to allowing an external attacker to edit or add new properties to an object. This is possible because the application does not properly validate incoming JSON keys, thus allowing the __proto__
property to be edited.
PoC
var parseString = require('xml2js').parseString;
let normal_user_request = "<role>admin</role>";
let malicious_user_request = "<__proto__><role>admin</role></__proto__>";
const update_user = (userProp) => {
// A user cannot alter his role. This way we prevent privilege escalations.
parseString(userProp, function (err, user) {
if(user.hasOwnProperty("role") && user?.role.toLowerCase() === "admin") {
console.log("Unauthorized Action");
} else {
console.log(user?.role[0]);
}
});
}
update_user(normal_user_request);
update_user(malicious_user_request);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade xml2js
to version 0.5.0 or higher.
References
medium severity
- Vulnerable module: concat-stream
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
concat-stream
is writable stream that concatenates strings or binary data and calls a callback with the result.
Affected versions of the package are vulnerable to Uninitialized Memory Exposure.
A possible memory disclosure vulnerability exists when a value of type number
is provided to the stringConcat()
method and results in concatenation of uninitialized memory to the stream collection.
This is a result of unobstructed use of the Buffer
constructor, whose insecure default constructor increases the odds of memory leakage.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with raw (not "zero-ed") memory.
In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":
// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');
concat-stream
's stringConcat
function uses the default Buffer
constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed
flaw in OpenSSL.
You can read more about the insecure Buffer
behavior on our blog.
Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.
Remediation
Upgrade concat-stream
to version 1.5.2 or higher.
Note This is vulnerable only for Node <=4
References
medium severity
- Vulnerable module: passport
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
passport is a Simple, unobtrusive authentication for Node.js.
Affected versions of this package are vulnerable to Session Fixation. When a user logs in or logs out, the session is regenerated instead of being closed.
Remediation
Upgrade passport
to version 0.6.0 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
low severity
- Vulnerable module: debug
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
debug is a small debugging utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the function useColors
via manipulation of the str
argument.
The vulnerability can cause a very low impact of about 2 seconds of matching time for data 50k characters long.
Note: CVE-2017-20165 is a duplicate of this vulnerability.
PoC
Use the following regex in the %o
formatter.
/\s*\n\s*/
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade debug
to version 2.6.9, 3.1.0, 3.2.7, 4.3.1 or higher.
References
low severity
- Vulnerable module: mime
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
mime is a comprehensive, compact MIME type module.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/
in its lookup, which can cause a slowdown of 2 seconds for 50k characters.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mime
to version 1.4.1, 2.0.3 or higher.
References
low severity
- Vulnerable module: minimist
- Introduced through: [email protected] and [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution due to a missing handler to Function.prototype
.
Notes:
This vulnerability is a bypass to CVE-2020-7598
The reason for the different CVSS between CVE-2021-44906 to CVE-2020-7598, is that CVE-2020-7598 can pollute objects, while CVE-2021-44906 can pollute only function.
PoC by Snyk
require('minimist')('--_.constructor.constructor.prototype.foo bar'.split(' '));
console.log((function(){}).foo); // bar
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 0.2.4, 1.2.6 or higher.
References
low severity
- Vulnerable module: moment
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (/[0-9]*['a-z\u00A0-\u05FF\u0700-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]+|[\u0600-\u06FF\/]+(\s*?[\u0600-\u06FF]+){1,2}/i
) in order to parse dates specified as strings. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade moment
to version 2.19.3 or higher.
References
low severity
- Vulnerable module: ms
- Introduced through: [email protected], [email protected] and others
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
ms
is a tiny millisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms()
function.
Proof of concept
ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s
Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.
For more information on Regular Expression Denial of Service (ReDoS)
attacks, go to our blog.
Disclosure Timeline
- Feb 9th, 2017 - Reported the issue to package owner.
- Feb 11th, 2017 - Issue acknowledged by package owner.
- April 12th, 2017 - Fix PR opened by Snyk Security Team.
- May 15th, 2017 - Vulnerability published.
- May 16th, 2017 - Issue fixed and version
2.0.0
released. - May 21th, 2017 - Patches released for versions
>=0.7.1, <=1.0.0
.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade ms
to version 2.0.0 or higher.
References
low severity
- Vulnerable module: tar
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected] › [email protected]
Overview
tar is a full-featured Tar for Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). When stripping the trailing slash from files
arguments, the f.replace(/\/+$/, '')
performance of this function can exponentially degrade when f
contains many /
characters resulting in ReDoS.
This vulnerability is not likely to be exploitable as it requires that the untrusted input is being passed into the tar.extract()
or tar.list()
array of entries to parse/extract, which would be unusual.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade tar
to version 6.1.4, 5.0.8, 4.4.16 or higher.
References
low severity
- Vulnerable module: validator
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected]Remediation: Upgrade to [email protected].
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\s*data:([a-z]+\/[a-z0-9\-\+]+(;[a-z\-]+=[a-z0-9\-]+)?)?(;base64)?,[a-z0-9!\$&',\(\)\*\+,;=\-\._~:@\/\?%\s]*\s*$
) in order to validate Data URIs. This can cause an impact of about 10 seconds matching time for data 70K characters long.
Disclosure Timeline
- Feb 15th, 2018 - Initial Disclosure to package owner
- Feb 16th, 2018 - Initial Response from package owner
- Feb 18th, 2018 - Fix issued
- Feb 18th, 2018 - Vulnerability published
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 9.4.1 or higher.
References
low severity
- Vulnerable module: follow-redirects
- Introduced through: [email protected]
Detailed paths
-
Introduced through: ghost@grnd/ghost#d7c2376f1a77a349c5ee6c4b9ecc82e85262b742 › [email protected] › [email protected] › [email protected]Remediation: Upgrade to [email protected].
Overview
Affected versions of this package are vulnerable to Information Exposure due a leakage of the Authorization header from the same hostname during HTTPS to HTTP redirection. An attacker who can listen in on the wire (or perform a MITM attack) will be able to receive the Authorization header due to the usage of the insecure HTTP protocol which does not verify the hostname the request is sending to.
Remediation
Upgrade follow-redirects
to version 1.14.8 or higher.