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piccolo SQL Injection via named transaction savepoints

Critical severity GitHub Reviewed Published Nov 10, 2023 in piccolo-orm/piccolo • Updated Oct 9, 2024

Package

pip piccolo (pip)

Affected versions

< 1.1.1

Patched versions

1.1.1

Description

Summary

The handling of named transaction savepoints in all database implementations is vulnerable to SQL Injection as user provided input is passed directly to connection.execute(...) via f-strings.

Details

An excerpt of the Postgres savepoint handling:

    async def savepoint(self, name: t.Optional[str] = None) -> Savepoint:
        name = name or f"savepoint_{self.get_savepoint_id()}"
        await self.connection.execute(f"SAVEPOINT {name}")
        return Savepoint(name=name, transaction=self)

In this example, we can see user input is directly passed to connection.execute without being properly escaped.

All implementations of savepoints and savepoint methods directly pass this name parameter to connection.execute and are vulnerable to this. A non-exhaustive list can be found below:

Care should be given to ensuring all strings passed to connection.execute are properly escaped, regardless of how end user facing they may be.

Further to this, the following method also passes user input directly to an execution context however I have been unable to abuse this functionality at the time of writing. This method also has a far lower chance of being exposed to an end user as it relates to database init functionality.

PoC

The following FastAPI route can be used in conjunction with sqlmap to easily demonstrate the SQL injection.

DB = ...

@app.get("/test")
async def test(name):
    async with DB.transaction() as transaction:
        await transaction.savepoint(name)
Steps
  1. Create a standard Piccolo application with Postgres as a database backend
  2. Add the route shown previously
  3. Run your application, making a note of the URL it is served on
  4. Install sqlmap
  5. In a terminal, run the following command substituting URL with your applications URL: sqlmap -u "https://URL/test?name=a" --batch
  6. Observe sqlmap identifying the vulnerability

For sqlmap help, this usage guide may be useful. The following commands may also be helpful to see the impact.

Dumping all tables

The --tables flag will enumerate all tables accessible from within the exposed database session.

sqlmap -u "https://URL/test?name=a" --batch --tables

An example output of this can be seen in the following screenshot.
Screenshot from 2023-11-06 23-10-30

OS Shell

The --os-shell will drop the user into an OS shell on the underlying system if permissions permit. This can be seen in the attached screenshot which prints the databases current working directory.
Screenshot from 2023-11-06 22-43-50

Impact

While the likelihood of an end developer exposing a savepoints name parameter to a user is highly unlikely, it would not be unheard of. If a malicious user was able to abuse this functionality they would have essentially direct access to the database and the ability to modify data to the level of permissions associated with the database user.

A non exhaustive list of actions possible based on database permissions is:

  • Read all data stored in the database, including usernames and password hashes
  • Insert arbitrary data into the database, including modifying existing records
  • Gain a shell on the underlying server

References

@dantownsend dantownsend published to piccolo-orm/piccolo Nov 10, 2023
Published by the National Vulnerability Database Nov 10, 2023
Published to the GitHub Advisory Database Nov 12, 2023
Reviewed Nov 12, 2023
Last updated Oct 9, 2024

Severity

Critical

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

EPSS score

0.086%
(37th percentile)

Weaknesses

CVE ID

CVE-2023-47128

GHSA ID

GHSA-xq59-7jf3-rjc6

Source code

Credits

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