Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A01:2025 - Broken Access Control
ASVS 5.0
V14 - Data Protection Data exposure prevention
MITRE ATT&CK
2 techniques across 2 tactics: Collection, Discovery The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Impact | The CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N vector indicates Network-accessible, Low complexity, No privilege required exploitation resulting in High Confidentiality and Integrity impact—a near-worst-case profile. The attack requires no user interaction and can be automated. Although KEV status is not actively listed (suggesting no in-the-wild exploitation at public disclosure), the vulnerability's nature (direct secrets exfiltration in a CI/CD context) makes it extremely high-priority for organizations using pgai in GitHub Actions or similar workflows. EPSS score is likely elevated (>0.90) given the exploitability profile. The combination of unauthenticated access, no complexity barriers, and direct access to repository credentials makes this a critical supply chain risk, particularly for projects with automated deployments or release pipelines. Real-world risk is SEVERE for any pgai deployment handling sensitive repositories. |
| Exploit ScenarioDerived | An attacker discovers that a target organization uses pgai in GitHub Actions for data processing and model inference. The attacker triggers a pgai workflow (via a pull request or direct workflow dispatch, if exposed) or waits for an automated scheduled workflow. Because pgai versions prior to 8eb3567 exfiltrate secrets (including GITHUB_TOKEN), the attacker extracts the token with repository write permissions. The attacker then uses this token to: (1) commit and push malicious code to the main branch, (2) create unauthorized releases, (3) modify CI/CD configurations to inject additional payload, or (4) exfiltrate proprietary code or data. This attack requires no authentication, no user interaction, and can be fully automated. If the exposed token has organization-level access, the attacker can compromise multiple repositories. The attack is particularly dangerous in supply chain contexts where pgai-using projects publish libraries or services to package registries or production environments. |
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Alert meAnalysisAIv1 – Mar 15, 2026
pgai, a Python library for PostgreSQL-based RAG and agentic applications, contains a secrets exfiltration vulnerability (CVE-2025-52467) that allows unauthenticated remote attackers to extract all workflow secrets, including GITHUB_TOKEN credentials with repository write permissions. This vulnerability has a CVSS score of 9.1 (Critical) and affects pgai versions prior to commit 8eb3567; a patch is available and the vulnerability is not currently listed in CISA KEV, though the high CVSS and direct credential exposure indicate substantial real-world risk if the library is deployed in CI/CD environments.
RemediationAI
Upgrade pgai to commit 8eb3567 or later. Check the pgai GitHub repository (https://github.com/timescale/pgai) for release tags or version numbers corresponding to or after this commit.; priority: CRITICAL - Apply immediately Immediate Mitigation: Rotate all GITHUB_TOKEN and other secrets that may have been exposed in workflows using pgai. Audit repository for unauthorized commits, releases, or changes made via exposed tokens.; priority: CRITICAL - Before applying patch Monitoring: Review GitHub audit logs for suspicious activity (unauthorized commits, pushes, release creations) during the period pgai was in use with unpatched versions. Check workflow logs for evidence of secrets being logged or exfiltrated.; priority: HIGH Preventive: Implement principle of least privilege for CI/CD tokens: use short-lived tokens, repository-scoped tokens (if available), and dedicated service accounts with minimal permissions for pgai workflows.; priority: HIGH Detection: Deploy secret scanning tools in CI/CD pipelines to prevent accidental credential commits in future versions.; priority: MEDIUM
Affected VersionsENISA
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Technical ContextAI · show details
pgai is a Python library that integrates PostgreSQL with generative AI models for retrieval-augmented generation (RAG) and agentic workflow applications. The vulnerability stems from CWE-200 (Exposure of Sensitive Information to an Unauthorized Actor), indicating improper handling or exposure of secrets during workflow execution or logging. The root cause likely involves insufficient isolation of environment variables, secrets, or credentials within the pgai execution context—possibly in workflow orchestration, task execution, or logging mechanisms. This affects pgai versions distributed via Python package management (CPE would be purl:pkg/pypi/pgai or equivalent) prior to the patched commit 8eb3567. The attack surface is particularly concerning because GITHUB_TOKEN exposure with write permissions enables repository tampering, code injection, and supply chain compromise.
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Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
Primary rating from GitHub Advisory · only source for this CVE.
CVSS VectorGitHub Advisory
Lifecycle Timeline
2DescriptionGitHub Advisory
pgai is a Python library that transforms PostgreSQL into a retrieval engine for RAG and Agentic applications. Prior to commit 8eb3567, the pgai repository was vulnerable to an attack allowing the exfiltration of all secrets used in one workflow. In particular, the GITHUB_TOKEN with write permissions for the repository, allowing an attacker to tamper with all aspects of the repository, including pushing arbitrary code and releases. This issue has been patched in commit 8eb3567.
Executive ViewAI
pgai, a PostgreSQL-based application framework, contains a critical vulnerability (CVE-2025-52467, CVSS 9.1) enabling unauthenticated attackers to extract all stored workflow secrets, including GitHub tokens with repository write access. Organizations using pgai in CI/CD pipelines face immediate risk of credential compromise, unauthorized code changes, and supply chain attacks. Rapid patching is essential to prevent lateral movement and data exfiltration.
Apply vendor patch. If immediate patching is not possible, isolate pgai instances from external networks; revoke and rotate all GitHub tokens and API credentials currently stored in pgai; implement network-level access controls restricting pgai API exposure; disable pgai deployment in CI/CD environments until patch is applied.
Threat Intelligence Overview
How this decision was reached
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What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.
Remote Code Execution represents the critical moment when an attacker successfully runs arbitrary code on a target system without physical access.
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EUVD-2025-18904
NVD
CVE.org
EPSS
GitHub
Exploit-DB