CVE-2026-3071
Published: 26 February 2026
Summary
CVE-2026-3071 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Hiddenlayer (inferred from references). Its CVSS base score is 8.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 4.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as NLP Libraries; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified are NIST 800-53 SI-10 (Information Input Validation) and SI-2 (Flaw Remediation).
Deeper analysis
CVE-2026-3071 is a deserialization of untrusted data vulnerability (CWE-502) in the LanguageModel class of the Flair library, affecting versions 0.4.1 through the latest release. Published on 2026-02-26, it enables arbitrary code execution when an application loads a malicious model using the affected class. The issue carries a CVSS v3.1 base score of 8.4 (AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H), indicating high severity due to its potential for significant impact.
A local attacker can exploit this vulnerability with low complexity, requiring no privileges or user interaction. By supplying a malicious model file, the attacker tricks the Flair-based application into deserializing untrusted data during model loading, resulting in arbitrary code execution on the host system with the privileges of the running process. This could lead to full system compromise if the application processes untrusted models.
Advisories detailing mitigations and patches are available from HiddenLayer at https://www.hiddenlayer.com/sai-security-advisory/2026-02-flair.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8855
Vulnerability details
Deserialization of untrusted data in the LanguageModel class of Flair from versions 0.4.1 to latest are vulnerable to arbitrary code execution when loading a malicious model.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP Libraries
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: flair
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Deserialization of untrusted model data directly enables arbitrary code execution in a Python library (Flair), mapping to client-side exploitation (T1203) and Python interpreter abuse (T1059.006) with local attack vector and no UI required.
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Remediates the deserialization vulnerability in Flair's LanguageModel class by applying vendor patches, directly preventing arbitrary code execution from malicious models.
Requires validation of untrusted model files prior to deserialization in the LanguageModel class, blocking malicious data that could lead to code execution.
Enforces integrity verification of software and model files loaded by Flair, detecting and preventing execution of tampered or malicious deserialized content.