AI Security Threat Feed
Latest CVEs affecting AI/ML systems — LLM frameworks, ML libraries, AI agents, vector databases, and inference servers. Vulnerabilities are tracked from NVD, GitHub Advisory, CISA KEV, MITRE ATLAS, and enriched with CVSS, EPSS, exploitation confidence, AI-component classification, and compliance mappings to ISO 42001, EU AI Act, NIST AI RMF, and OWASP LLM Top 10. Updated continuously as new CVEs are published.
- CVSS severity
- EPSS exploit probability
- Exploitation confidence
- AI-component classification
- Compliance mappings
AI/ML CVEs Tracked
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Latest AI Security Threats
Showing 20 of 185 results — Critical severity, Active exploitationQuickAI: unauthenticated SQLi exposes OpenAI API keys
CVE-2023-3686 LangChain: RCE via PALChain unsanitized Python exec
CVE-2023-36188 LangChain: unauthenticated RCE via code injection
CVE-2023-36258 LangChain: RCE via unsafe load_prompt deserialization
CVE-2023-34541 LangChain: RCE via JiraAPIWrapper crafted input
CVE-2023-34540 Gradio: path traversal + SSRF exposes model files & infra
CVE-2023-34239 MLflow: path traversal allows arbitrary file read/write
CVE-2023-2780 LangChain: RCE via prompt injection in LLMMathChain
CVE-2023-29374 TensorFlow: unauthenticated RCE via heap buffer overflow
CVE-2023-25668 TensorFlow: heap overflow in AvgPoolGrad, RCE risk
CVE-2023-25664 MLflow: path traversal allows arbitrary file read/write
CVE-2023-1177 Gradio: hardcoded SSH key leaks via share=True demos
CVE-2023-25823 TensorFlow Grappler: OOB read/crash via crafted model
CVE-2022-41902 PyTorch: RCE via unsafe eval in JIT annotations
CVE-2022-45907 TensorFlow: heap OOB RCE in FractionalMaxPool op
CVE-2022-41900 TensorFlow: heap OOB read in candidate sampler op
CVE-2022-41880 pytorch-lightning: code injection enables full RCE
CVE-2022-0845 TensorFlow: integer overflow in Grappler enables RCE
CVE-2022-23587 TensorFlow: path traversal in get_file allows file overwrite
CVE-2021-35958 TFLite: OOB read/write via tensor dimension mismatch
CVE-2020-15208 Frequently asked questions
What is an AI security threat feed?
An AI security threat feed is a continuously updated stream of vulnerabilities (CVEs) affecting AI and machine-learning systems — LLM frameworks, ML libraries, AI agents, vector databases, and inference servers — filtered out of the broader CVE firehose and enriched for relevance.
Which sources are the AI CVEs tracked from?
CVEs are tracked from NVD, GitHub Advisory, CISA KEV, and MITRE ATLAS, then enriched with CVSS, EPSS, exploitation confidence, AI-component classification, and compliance mappings.
What AI systems do these vulnerabilities affect?
Coverage spans LLM frameworks, ML libraries, AI agents, vector databases, and inference servers — the components most security teams now run in production.
How often is the AI threat feed updated?
The feed updates continuously as new CVEs are published and enriched, so the most recent AI/ML vulnerabilities appear at the top.
Is the AI security feed free?
Yes — the public feed is free to browse. A Pro subscription adds breaking alerts, MITRE ATLAS mappings, compliance reports (ISO 42001, EU AI Act), and full CISO analysis.
Need deeper analysis?
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