A short motivational video clip to inspire us: https://youtu.be/rDMMYT3vkTk "You passed! All D's ... and an A!"
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Automate analysis and trust decisions on the security posture of open source projects.
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Use this data to proactively improve the security posture of the critical projects the world depends on.
If you're only interested in seeing the results over time, we run this program nightly and publish the results in
json
format.
This data is available on Google Cloud Storage and can be downloaded via the
gsutil
command-line tool.
$ gsutil ls gs:https://ossf-scorecards/
gs:https://ossf-scorecards/11-11-2020.json
...
The latest results are also always available at https://storage.googleapis.com/ossf-scorecards/latest.json
The list of projects that are checked each night is available in the
cron/projects.txt
file in this repository. If you would like us to track more, please feel free to
send a Pull Request with others.
The program only requires one argument to run, the name of the repo:
$ go build
$ ./scorecard --repo=github.com/kubernetes/kubernetes
Starting [Active]
Starting [Branch-Protection]
Starting [CI-Tests]
Starting [CII-Best-Practices]
Starting [Code-Review]
Starting [Contributors]
Starting [Frozen-Deps]
Starting [Fuzzing]
Starting [Packaging]
Starting [Pull-Requests]
Starting [SAST]
Starting [Security-Policy]
Starting [Signed-Releases]
Starting [Signed-Tags]
Finished [Fuzzing]
Finished [CII-Best-Practices]
Finished [Branch-Protection]
Finished [Packaging]
Finished [Security-Policy]
Finished [Frozen-Deps]
Finished [Signed-Tags]
Finished [Signed-Releases]
Finished [SAST]
Finished [CI-Tests]
Finished [Active]
Finished [Contributors]
Finished [Pull-Requests]
Finished [Code-Review]
RESULTS
-------
Active: Pass 10
Branch-Protection: Fail 10
CI-Tests: Pass 10
CII-Best-Practices: Pass 10
Code-Review: Pass 10
Contributors: Pass 10
Frozen-Deps: Pass 10
Fuzzing: Pass 10
Packaging: Fail 0
Pull-Requests: Pass 10
SAST: Fail 10
Security-Policy: Pass 10
Signed-Releases: Fail 10
Signed-Tags: Fail 10
scorecard has an option to provide either --npm
/ --pypi
/ --rubygems
package name and it would run the checks on the corresponding GitHub source
code.
For example:
./scorecard --npm=angular
Starting [Active]
Starting [Branch-Protection]
Starting [CI-Tests]
Starting [CII-Best-Practices]
Starting [Code-Review]
Starting [Contributors]
Starting [Frozen-Deps]
Starting [Fuzzing]
Starting [Packaging]
Starting [Pull-Requests]
Starting [SAST]
Starting [Security-Policy]
Starting [Signed-Releases]
Starting [Signed-Tags]
Finished [Signed-Releases]
Finished [Fuzzing]
Finished [CII-Best-Practices]
Finished [Security-Policy]
Finished [CI-Tests]
Finished [Packaging]
Finished [SAST]
Finished [Code-Review]
Finished [Branch-Protection]
Finished [Frozen-Deps]
Finished [Signed-Tags]
Finished [Active]
Finished [Pull-Requests]
Finished [Contributors]
RESULTS
-------
Active: Fail 10
Branch-Protection: Fail 0
CI-Tests: Pass 10
CII-Best-Practices: Fail 10
Code-Review: Pass 10
Contributors: Pass 10
Frozen-Deps: Fail 0
Fuzzing: Fail 10
Packaging: Fail 0
Pull-Requests: Fail 9
SAST: Fail 10
Security-Policy: Pass 10
Signed-Releases: Fail 0
Signed-Tags: Fail 10
scorecard
is available as a Docker container:
The GITHUB_AUTH_TOKEN
has to be set to a valid token
docker run -e GITHUB_AUTH_TOKEN=token docker.pkg.github.com/ossf/scorecard/scorecard --show-details --repo=https://github.com/ossf/scorecard
The Dockerfile in the root directory utilizes experimental features which is available in Docker v18.09 or later.
Scorecard uses httpcache
with https://docs.github.com/en/rest/overview/resources-in-the-rest-api#conditional-requests for caching httpresponse. The default cache is in-memory.
Some details on caching #80 (comment)
Scorecard results can be cached into a blob for increasing throughput for subsequent runs.
To use blob cache two env variables have to be set USE_BLOB_CACHE=true
and BLOB_URL=gs:https://scorecards-cache/
.
The code uses https://github.com/google/go-cloud for blob caching. It is compatible with GCS,S3 and Azure blob.
Scorecard results can be cached into a disk for increasing throughput for subsequent runs.
To use disk cache two env variables have to be set USE_DISK_CACHE=true
and DISK_CACHE_PATH=./cache
.
There is no TTL on cache.
The default cache size is 10GB.
Gitcache reduces the GitHub API usage by cloning the Git repository without authentication and checking for updates.
- Clone the repository anonymously (not using GitHub API token).
- Tarball and compress it.
- Store the compressed file into a blob store GCS.
- Store the last commit date within the blob.
- Also compress the folder without .git for the consumers.
- pull gzip from GCS
- unzip git repo
- git pull origin
- update metadata (last sync, etc.)
- gzip, reupload to GCS
gitcache documentation for more details.
Before running Scorecard, you need to
create a GitHub access token
and set it in environment variable GITHUB_AUTH_TOKEN
.
This helps to avoid the GitHub's
api rate limits
with unauthenticated requests.
# For posix platforms, e.g. linux, mac:
export GITHUB_AUTH_TOKEN=<your access token>
# For windows:
set GITHUB_AUTH_TOKEN=<your access token>
Multiple GITHUB_AUTH_TOKEN
can be provided separated by comma to be utilized in a round robin fashion.
As an alternative to personal access tokens, we also support GitHub App Installations for higher rate-limit quotas. If you have an installed GitHub App and key file, you can use these three environment variables, following the commands shown above for your platform.
GITHUB_APP_KEY_PATH=<path to the key file on disk>
GITHUB_APP_INSTALLATION_ID=<installation id>
GITHUB_APP_ID=<app id>
These can be obtained from the GitHub developer settings page.
The following checks are all run against the target project:
Name | Description |
---|---|
Security-Policy | Does the project contain a security policy? |
Contributors | Does the project have contributors from at least two different organizations? |
Frozen-Deps | Does the project declare and freeze dependencies? |
Signed-Releases | Does the project cryptographically sign releases? |
Signed-Tags | Does the project cryptographically sign release tags? |
CI-Tests | Does the project run tests in CI, e.g. GitHub Actions, Prow? |
Code-Review | Does the project require code review before code is merged? |
CII-Best-Practices | Does the project have a CII Best Practices Badge? |
Pull-Requests | Does the project use Pull Requests for all code changes? |
Fuzzing | Does the project use fuzzing tools, e.g. OSS-Fuzz? |
SAST | Does the project use static code analysis tools, e.g. CodeQL, SonarCloud? |
Active | Did the project get any commits in the last 90 days? |
Branch-Protection | Does the project use Branch Protection ? |
Packaging | Does the project build and publish official packages from CI/CD, e.g. GitHub Publishing ? |
To see detailed information about each check and remediation steps, check out the checks documentation page.
If you'd like to add a check, make sure it is something that meets the following criteria:
- automate-able
- objective
- actionable
and then create a new GitHub Issue.
Each check returns a Pass / Fail decision, as well as a confidence score between 0 and 10. A confidence of 0 should indicate the check was unable to achieve any real signal, and the result should be ignored. A confidence of 10 indicates the check is completely sure of the result.
Many of the checks are based on heuristics, contributions are welcome to improve the detection!
To use a particular check(s), add the --checks
argument with a list of check
names.
For example, --checks=CI-Tests,Code-Review
.
There are three formats currently: default
, json
, and csv
. Others may be added in the future.
These may be specified with the --format
flag.
- The scorecard must only be composed of automate-able, objective data. For example, a project having 10 contributors doesn’t necessarily mean it’s more secure than a project with say 50 contributors. But, having two maintainers might be preferable to only having one - the larger bus factor and ability to provide code reviews is objectively better.
- The scorecard criteria can be as specific as possible and not limited general recommendations. For example, for Go, we can recommend/require specific linters and analyzers to be run on the codebase.
- The scorecard can be populated for any open source project without any work or interaction from maintainers.
- Maintainers must be provided with a mechanism to correct any automated scorecard findings they feel were made in error, provide "hints" for anything we can't detect automatically, and even dispute the applicability of a given scorecard finding for that repository.
- Any criteria in the scorecard must be actionable. It should be possible, with help, for any project to "check all the boxes".
- Any solution to compile a scorecard should be usable by the greater open source community to monitor upstream security.
If you want to get involved or have ideas you'd like to chat about, we discuss this project in the OSSF Best Practices Working Group meetings.
See the Community Calendar for the schedule and meeting invitations.
See the Contributing documentation for guidance on how to contribute.