CVE-2026-56121
Published: 24 June 2026
Summary
CVE-2026-56121 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Redhat (inferred from references). Its CVSS base score is 9.3 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 45.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-38801
Vulnerability details
Feast before 0.63.0 contains an unsafe deserialization vulnerability that allows unauthenticated or unauthorized attackers to achieve remote code execution by sending a crafted gRPC request to the registry server. The user_defined_function.body field of an OnDemandFeatureView spec is decoded from base64…
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and passed to dill.loads() before any authorization check is performed, enabling attackers to embed a malicious serialized Python object with an arbitrary __reduce__ method to execute OS commands as the feast service account.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Direct RCE via unsafe deserialization in exposed gRPC registry server enables T1190; Python dill.loads() usage enables T1059.006.
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.