Repository compromise via untrusted pull-request workflow execution
Published Jul 16, 2024 · Updated Aug 16, 2024
Code injection in Project Jupyter JupyterLab Extension Template before 4.3.3 allows remote authenticated users to execute code in GitHub Actions. The generated update-integration-tests.yml workflow checks out code from an untrusted pull request after an issue comment and runs its scripts with a privileged GITHUB_TOKEN and repository secrets. An attacker needs a GitHub account and a pull request, and execution can expose secrets or permit unauthorized repository changes.
Summary
What happened
Code injection in Project Jupyter JupyterLab Extension Template before 4.3.3 allows remote authenticated users to execute code in GitHub Actions. The generated update-integration-tests.yml workflow checks out code from an untrusted pull request after an issue comment and runs its scripts with a privileged GITHUB_TOKEN and repository secrets. An attacker needs a GitHub account and a pull request, and execution can expose secrets or permit unauthorized repository changes.
The record
- CVE
- CVE-2024-39700
- Published
- Jul 16, 2024
- Updated
- Aug 16, 2024
- Vendor
- Project Jupyter
- Product
- JupyterLab Extension Template
- Classifications
- CWE-94, T1059
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Jul 16, 2024CVE publishedPublication date reported by the CVE source.
- Aug 16, 2024Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=0 <4.3.3
- Affected versionversion=< 4.3.3
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
- Checkout and execution of untrusted code in JupyterLab GitHub workflowsproof of concept · demonstrated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
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Your stack
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