CVE-2026-10042
Published: 29 May 2026
Summary
CVE-2026-10042 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability. Its CVSS base score is 9.2 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 45.4th percentile by exploit likelihood (below the median); 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-2026-33328
Vulnerability details
manga-image-translator contains a remote code execution vulnerability in the shared API server mode due to unsafe deserialization of untrusted pickle data in the share.py module, where the /execute/{method_name} and /simple_execute/{method_name} endpoints deserialize attacker-controlled HTTP request bodies using pickle.loads(). A remote…
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attacker can supply a crafted pickle payload to these endpoints to execute arbitrary code in the server process, resulting in full container compromise when running in the default Docker deployment as root.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Unsafe pickle deserialization on exposed API endpoints (/execute, /simple_execute) directly enables remote code execution against a public-facing application server.
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.