CVE-2026-45360
Published: 01 June 2026
Summary
CVE-2026-45360 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Airflow. Its CVSS base score is 7.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Python (T1059.006); ranked at the 42.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-33587
Vulnerability details
Apache Airflow's scheduler-side deadline-reference decoder (`SerializedCustomReference.deserialize_reference`) imported and dispatched arbitrary class paths drawn from DAG-author-controlled serialized state without an allowlist or plugin-registry gate. A DAG author whose code reaches the scheduler — the default on single-host deployments where the DAG…
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bundle is importable from the scheduler process — could embed a custom `DeadlineReference` whose serialized form named an attacker-controlled module path, causing the scheduler to `import_string(...)` and instantiate that class with a live SQLAlchemy session attached. Affects deployments where DAG-author code is less trusted than the scheduler process. Users are advised to upgrade to `apache-airflow` 3.2.2 or later.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CWE-502 deserialization of untrusted DAG-controlled class paths directly enables arbitrary Python import/instantiation (T1059.006) inside the scheduler, constituting exploitation for client/execution (T1203).
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.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.