Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2025-66388 is a medium-severity Insertion of Sensitive Information Into Sent Data (CWE-201) vulnerability in Apache Airflow. Its CVSS base score is 6.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Unsecured Credentials (T1552); ranked at the 34th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-203358
Vulnerability Data
A vulnerability in Apache Airflow allowed authenticated UI users to view secret values in rendered templates due to secrets not being properly redacted, potentially exposing secrets to users without the appropriate authorization. Users are recommended to upgrade to version 3.1.4,…
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which fixes this issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Improper secret redaction in rendered templates directly enables viewing of unsecured credentials by authorized UI users.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces authorization decisions so that UI users without secret access rights cannot view redacted values in rendered templates.
Enforces information-flow rules that prevent secret values from being released through rendered template output to unauthorized authenticated users.
Requires filtering of system output to suppress sensitive data such as secrets that were not properly redacted before display.
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 prevent insertion of sensitive data into application outputs and messages.
Monitoring runtime data flows and outputs can detect sensitive data being transmitted.
Protecting data-in-transit can include filtering or encrypting to avoid exposing sensitive content.
Protecting data-in-use includes removing confidential values before they are processed or sent.
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.
Data-masking techniques can prevent sensitive values from appearing in transmitted payloads.
Classification identifies sensitive data so it is not inadvertently transmitted.
Labelling makes sensitive data visible to developers and prevents accidental inclusion in outbound messages.
Information-transfer rules directly govern what data may be sent to external parties.
PII-protection requirements reduce the chance of sending personal data to unauthorized recipients.
DLP controls inspect and block outbound flows that contain sensitive information.