CVE-2023-7018
Published: 20 December 2023
Summary
CVE-2023-7018 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Huggingface Transformers. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 42.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as NLP and Transformers; in the Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: AI Supply Chain Compromise (AML.T0010).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0301
Vulnerability details
Deserialization of Untrusted Data in GitHub repository huggingface/transformers prior to 4.36.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- The vulnerability is a Deserialization of Untrusted Data issue in the Hugging Face Transformers library (huggingface/transformers), which is a core library for NLP and transformer models in AI/ML workflows.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Deserialization of untrusted data in Hugging Face Transformers library enables arbitrary code execution upon processing malicious input, facilitating Exploitation for Client Execution.
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
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.