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 230 results — Critical severity, no patchBentoML: unauthenticated SSRF via file upload URLs
CVE-2025-54381 LangChain GmailToolkit: indirect prompt injection to RCE
CVE-2025-46059 smolagents: sandbox escape enables unauthenticated RCE
CVE-2025-5120 Langchain-Chatchat: path traversal in KB upload
CVE-2025-6853 LLaMA-Factory: RCE via unsafe checkpoint deserialization
CVE-2025-53002 LangChain RequestsToolkit: SSRF exposes cloud metadata
CVE-2025-2828 vLLM: RCE via exposed TCPStore in distributed inference
CVE-2025-47277 vLLM: RCE via pickle deserialization on ZeroMQ
CVE-2025-32444 PyTorch: RCE bypasses weights_only=True safe-load guard
CVE-2025-32434 BentoML: RCE via insecure deserialization in runner
CVE-2025-32375 Langflow: Unauth RCE via code injection endpoint
CVE-2025-3248 BentoML: unauthenticated RCE via insecure deserialization
CVE-2025-27520 vLLM: RCE via pickle deserialization in distributed API
CVE-2024-9052 llama-index finchat: SQL injection enables RCE
CVE-2024-12909 BentoML: unauthenticated RCE via runner deserialization
CVE-2024-9070 vllm: RCE via unsafe pickle deserialization in RPC server
CVE-2024-9053 vllm: RCE via unsafe pickle deserialization in MessageQueue
CVE-2024-11041 vLLM: RCE via unsafe deserialization in Mooncake KV
CVE-2025-29783 Keras: safe_mode bypass enables RCE via model loading
CVE-2025-1550 picklescan: ZIP flag bypass enables RCE in PyTorch models
CVE-2025-1945 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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