Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2025-66236 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 at the 36th percentile by exploit likelihood (below the median); 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-2025-66236 affects Apache Airflow versions prior to 3.2.0. The issue arises from unclear documentation on secure deployment requirements, where deployment managers might make incorrect assumptions about Airflow's security model, workload isolation, and JWT authentication details. Although Airflow's intentions did not suggest alternative assumptions, these aspects were not explicit enough, potentially leading to insecure configurations. The vulnerability is classified under CWE-532 and carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N).
Unauthenticated attackers with network access can exploit misconfigurations resulting from these unclear assumptions. By leveraging deployment managers' failure to properly implement Airflow's security model, attackers can achieve high confidentiality impact, such as unauthorized access to sensitive data.
Advisories recommend upgrading to Airflow 3.2.0, which implements several security improvements and provides more detailed documentation on the security model (https://airflow.apache.org/docs/apache-airflow/stable/security/jwt_token_authentication.html), workload isolation (https://airflow.apache.org/docs/apache-airflow/stable/security/workload.html), and JWT token authentication (https://airflow.apache.org/docs/apache-airflow/stable/security/jwt_token_authentication.html). The Airflow 3.2.0 blog announcement (https://airflow.apache.org/blog/airflow-3.2.0/) further clarifies responsibilities, emphasizing that deployment managers are ultimately accountable for securing their Airflow deployments. Additional references include the fix in GitHub pull request #58662 and announcements on Apache mailing lists.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-209413
Vulnerability Data
Before Airflow 3.2.0, it was unclear that secure Airflow deployments require the Deployment Manager to take appropriate actions and pay attention to security details and security model of Airflow. Some assumptions the Deployment Manager could make were not clear or…
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explicit enough, even though Airflow's intentions and security model of Airflow did not suggest different assumptions. The overall security model [1], workload isolation [2], and JWT authentication details [3] are now described in more detail. Users concerned with role isolation and following the Airflow security model of Airflow are advised to upgrade to Airflow 3.2, where several security improvements have been implemented. They should also read and follow the relevant documents to make sure that their deployment is secure enough. It also clarifies that the Deployment Manager is ultimately responsible for securing your Airflow deployment. This had also been communicated via Airflow 3.2.0 Blog announcement [4]. [1] Security Model: https://airflow.apache.org/docs/apache-airflow/stable/security/jwt_token_authentication.html [2] Workload isolation: https://airflow.apache.org/docs/apache-airflow/stable/security/workload.html [3] JWT Token authentication: https://airflow.apache.org/docs/apache-airflow/stable/security/jwt_token_authentication.html [4] Airflow 3.2.0 Blog announcement: https://airflow.apache.org/blog/airflow-3.2.0/ Users are recommended to upgrade to version 3.2.0, which fixes this issue.
- 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.