Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2026-31987 is a high-severity Insertion of Sensitive Information into Log File (CWE-532) vulnerability in Apache Airflow. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Unsecured Credentials (T1552); ranked in the top 49% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-31987 is a vulnerability in Apache Airflow where JWT tokens used by tasks are exposed in logs, classified under CWE-532 (Insertion of Sensitive Information into Log File). This issue affects Airflow deployments prior to version 3.2.0 and was published on 2026-04-16. The CVSS v3.1 base score is 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N), indicating high confidentiality impact with network accessibility, low attack complexity, and no privileges or user interaction required.
An attacker with access to the exposed logs can extract the JWT tokens, enabling UI users to impersonate DAG authors. This privilege escalation allows unauthorized actions typically reserved for DAG authors, such as potentially modifying or executing workflows, leading to high confidentiality risks without impacting integrity or availability.
Apache Airflow advisories recommend upgrading to version 3.2.0, which contains the fix for this issue. Relevant discussions and patches are documented in GitHub issues #62428 and #62773, pull request #62964, and announcements on the Apache mailing list and oss-security list.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-23233
Vulnerability Data
JWT Tokens used by tasks were exposed in logs. This could allow UI users to act as Dag Authors. Users are advised to upgrade to Airflow version that contains fix. Users are recommended to upgrade to version 3.2.0, which fixes…
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- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Procedures mandate excluding sensitive data from logs to prevent unauthorized exposure via audit records.
Identifies insertion of sensitive data into logs, allowing detection of unauthorized disclosure.
Cross-organizational coordination enables agreement on what data to include in audit logs, directly reducing insertion of sensitive information.
Identifying logging as a data action allows prevention of sensitive information being inserted into log files.
The process of identifying and eradicating spilled information applies directly to sensitive data inserted into log files.
Specific processing rules for sensitive PII categories commonly include restrictions on logging, making insertion of such data into log files less likely.
PIAs detect planned or existing logging of PII and require removal or protection, preventing insertion of sensitive information into logs.
Limits insertion of sensitive operational details into logs by treating such data as key information requiring protection.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly prohibit writing sensitive data to logs; eliminating the weakness satisfies only one narrow slice of the control.
Log generation configuration can and should exclude sensitive data, but the control statement focuses on availability rather than content filtering.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Requiring de-identification and privacy controls before logs leave the organization reduces the chance that sensitive data inadvertently captured in logs becomes exposed to external parties.
By defining what records must be kept, where, and for how long, the control discourages the inadvertent inclusion of sensitive information in logs or other externally accessible files that fall outside the formal record system.
Mandating deletion of temporary files and logs that may contain sensitive information prevents those artifacts from remaining accessible after the data is no longer needed.
When log entries are produced from masked data sets, the control prevents the inadvertent insertion of sensitive values into externally accessible log files.
DLP inspection of logs and file transfers can detect and block the inadvertent placement of sensitive tokens or credentials into externally accessible log files before they are written or transmitted.
Requiring restrictions on free-text fields and proper error-message handling stops developers from embedding or leaking sensitive data into logs or diagnostic output.