Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2026-25219 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) 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 43th 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 SI-15 (Information Output Filtering) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-22921
Vulnerability Data
The `access_key` and `connection_string` connection properties were not marked as sensitive names in secrets masker. This means that user with read permission could see the values in Connection UI, as well as when Connection was accidentaly logged to logs, those…
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values could be seen in the logs. Azure Service Bus used those properties to store sensitive values. Possibly other providers could be also affected if they used the same fields to store sensitive data. If you used Azure Service Bus connection with those values set or if you have other connections with those values storing sensitve values, you should upgrade Airflow to 3.1.8
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CWE-200 exposure of connection secrets (keys/strings) in UI/logs directly enables unsecured credential discovery per T1552.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces that sensitive connection properties (access_key, connection_string) are not disclosed in the UI or logs to any user, even those with read permission.
Requires output filtering so that credential values stored in connection objects are automatically masked before display or accidental logging.
Protects audit and application logs from containing unmasked sensitive values when connection objects are written to them.
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.
PR.AA-05 directly enforces least-privilege authorization that blocks most unauthorized disclosures, yet CWE-200 also arises from logging, error messages, and side-channel paths that access controls alone do not address.
PR.DS-10 mostly prevents CWE-200 by directly eliminating unauthorized access to sensitive data-in-use, yet only partially addresses the weakness because CWE-200 spans many other exposure vectors outside runtime protection.
PR.IR-01's segmentation/zero-trust controls largely eliminate network-level unauthorized access paths that enable exposure, yet CWE-200 spans many additional vectors (API responses, logs, app logic) that network controls alone cannot close.
Secure SDLC practices catch most exposure flaws via design, testing and release controls, yet CWE-200 spans runtime/config issues a single development outcome cannot fully close.
PR.AA-01 supplies proper credential lifecycle controls that reduce unauthorized access paths, yet leaves many other exposure vectors (error messages, logging, side channels, etc.) unaddressed.
Authentication verifies actor identity and is a prerequisite for access decisions, yet addresses only one facet of the broad set of exposure vectors in CWE-200.
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.
Restricting anonymous or unknown access and encrypting high-value information limits the exposure of sensitive data that would otherwise be obtainable by unauthorized actors.
Suppressing system details, error specifics, and previous log-on information until successful authentication reduces the information an unauthenticated attacker can gather.
By requiring owners to assign sensitivity labels and corresponding handling rules, the control ensures that information is not left unmarked and therefore reduces the chance that sensitive data will be exposed to unauthorized actors.
Requiring encryption, access controls, and recipient authentication for transfers directly reduces the chance that sensitive data reaches an unauthorized observer.
Secure delivery, protected storage, and confidentiality of allocation records limit exposure of authentication material to unauthorized observers.
Requiring defined procedures, assigned roles, and technical/organizational measures for handling PII reduces the chance that sensitive personal data will be exposed to unauthorized actors through inadequate handling or missing safeguards.