Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2022-24288 is a high-severity OS Command Injection (CWE-78) vulnerability in Apache Airflow. Its CVSS base score is 8.8 (High).
Operationally, ranked in the top 0.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to CM-7 (Least Functionality) 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.
In Apache Airflow versions prior to 2.2.4, certain example DAGs failed to sanitize user-supplied parameters, exposing an OS command injection flaw reachable through the web UI. The issue is tracked as CWE-78 and carries a CVSS 3.1 score of 8.8, reflecting network-accessible exploitation with low attack complexity and no user interaction required once an authenticated session exists.
An authenticated user with access to the web UI can supply crafted parameters to the affected example DAGs, resulting in arbitrary operating-system command execution on the scheduler or worker host. Successful exploitation grants the attacker full control over confidentiality, integrity, and availability of the Airflow deployment and any connected systems.
The referenced Apache mailing-list announcement describes the flaw and states that the vulnerability is resolved in version 2.2.4; operators are advised to upgrade and to avoid exposing the example DAGs in production environments. The EPSS score remains elevated, with a recorded peak of 0.9418 and a current value of 0.8982.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-0013
Vulnerability Data
In Apache Airflow, prior to version 2.2.4, some example DAGs did not properly sanitize user-provided params, making them susceptible to OS Command Injection from the web UI.
- CWE(s)
Related Threats
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires validation and sanitization of user-supplied parameters before they are used in OS commands within the example DAGs.
Requires disabling non-essential example DAGs in production so the vulnerable parameter-handling code is never exposed via the web UI.
Mandates timely application of the vendor fix (upgrade to Airflow 2.2.4) that removes the unsanitized parameter paths.
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 require secure coding and input handling that blocks command-injection defects, yet the single broad outcome leaves many specific neutralization vectors and verification gaps unaddressed.
Routine patching/maintenance can remediate known command-injection CVEs in dependencies (partial forward) but does nothing to stop developers from introducing improper neutralization in custom code (none reverse).
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.
Security testing and code review target insecure use of operating-system command interfaces, catching command-injection flaws introduced during development.