CVE-2025-5174
Published: 26 May 2025
Summary
CVE-2025-5174 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Erdogant Pypickle. Its CVSS base score is 4.8 (Medium).
Operationally, ranked at the 28.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-16265
Vulnerability details
A vulnerability was found in erdogant pypickle up to 1.1.5 and classified as problematic. Affected by this issue is the function load of the file pypickle/pypickle.py. The manipulation leads to deserialization. Local access is required to approach this attack. The…
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exploit has been disclosed to the public and may be used. Upgrading to version 2.0.0 is able to address this issue. The patch is identified as 14b4cae704a0bb4eb6723e238f25382d847a1917. It is recommended to upgrade the affected component.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
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.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
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.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.