CVE-2025-71341
Published: 23 June 2026
Summary
CVE-2025-71341 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability. Its CVSS base score is 7.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 37.0th 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-2025-210305
Vulnerability details
picklescan before 0.0.29 fails to detect the profile.Profile.runctx function when analyzing pickle files, allowing attackers to embed undetected malicious code. Remote attackers can craft malicious pickle files using profile.Profile.runctx in the reduce method to achieve remote code execution when the…
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pickle file is loaded.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CWE-502 deserialization flaw in pickle scanner enables undetected malicious reduce payloads (profile.Profile.runctx) leading to RCE on load, directly mapping to client-side exploitation and Python command execution.
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.