Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:NSummary
CVE-2025-54550 is a high-severity Code Injection (CWE-94) vulnerability in Apache Airflow. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked at the 45th 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
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-2025-54550 affects the example_xcom DAG included in the Apache Airflow documentation, which implements an unsafe pattern for reading values from XCom. This flaw could enable a UI user with access to modify XComs to execute arbitrary code on the Airflow worker. The vulnerability does not impact Airflow releases themselves, as example DAGs are not intended for production environments, but it may affect users who replicated this pattern in their own implementations. It is classified under CWE-94 (Code Injection) with a CVSS v3.1 base score of 8.1 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N) and was published on 2026-04-15.
A UI user with low privileges (PR:L) and network access can exploit the vulnerability with low attack complexity. Exploitation allows arbitrary code execution on the worker, resulting in high impacts to confidentiality and integrity but no availability disruption. The low privileges required align with the trust model for Airflow UI users, contributing to its low severity rating despite the elevated CVSS score.
Advisories recommend that users who followed the unsafe XCom reading pattern adjust their implementations for resilience. Airflow 3.2.0 documentation includes an improved version of the example_xcom DAG addressing this issue. Key references include the Apache Airflow GitHub pull request at https://github.com/apache/airflow/pull/63200, the Apache mailing list thread at https://lists.apache.org/thread/3mf4cfx070ofsnf9qy0s2v5gqb5sc2g1, and the OSS-Security announcement at http://www.openwall.com/lists/oss-security/2026/04/15/1.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-209465
Vulnerability Data
The example example_xcom that was included in airflow documentation implemented unsafe pattern of reading value from xcom in the way that could be exploited to allow UI user who had access to modify XComs to perform arbitrary execution of code…
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on the worker. Since the UI users are already highly trusted, this is a Low severity vulnerability. It does not affect Airflow release - example_dags are not supposed to be enabled in production environment, however users following the example could replicate the bad pattern. Documentation of Airflow 3.2.0 contains version of the example with improved resiliance for that case. Users who followed that pattern are advised to adjust their implementations accordingly.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation finds code paths that accept and execute externally influenced strings.
Input validation directly stops untrusted data from being used to construct executable code without neutralization.
Least privilege limits the damage an injected code fragment can perform once executed.
Requiring documented secure development standards and tools enforces use of safe code-generation APIs and escaping.
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.PS-06's SDLC practices directly target injection flaws via secure coding and testing (mostly), yet as a single broad outcome it leaves many code-generation specifics unaddressed (partial).
PR.DS-10 protects runtime data confidentiality/integrity but has no bearing on neutralizing externally influenced input during code generation, so neither direction shows any preventive effect.
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.
Banning unapproved code samples and unauthenticated web services, combined with secure-coding standards and SAST, prevents the dynamic generation or inclusion of attacker-supplied code.
Controls that restrict unauthorized or malicious code from being introduced via external networks or removable media limit opportunities for an attacker to inject and execute arbitrary code.