CVE-2023-34239
Published: 08 June 2023
Summary
CVE-2023-34239 is a high-severity Improper Input Validation (CWE-20) vulnerability in Gradio Project Gradio. Its CVSS base score is 7.3 (High).
Operationally, ranked in the top 46.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Machine Learning Libraries.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0091
Vulnerability details
Gradio is an open-source Python library that is used to build machine learning and data science. Due to a lack of path filtering Gradio does not properly restrict file access to users. Additionally Gradio does not properly restrict the what…
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URLs are proxied. These issues have been addressed in version 3.34.0. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Machine Learning Libraries
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: machine learning
Related Threats
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 developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
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.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.