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 3021 resultsvLLM: DoS via unbounded XGrammar schema cache
GHSA-hf3c-wxg2-49q9 jupyter-remote-desktop-proxy: VNC network exposure
CVE-2025-32428 BentoML: RCE via insecure deserialization in runner
CVE-2025-32375 xgrammar: unbounded grammar cache causes LLM server DoS
CVE-2025-32381 picklescan: bypass allows silent RCE in ML pipelines
GHSA-v7x6-rv5q-mhwc picklescan: numpy bypass enables RCE in ML model pipelines
GHSA-fj43-3qmq-673f picklescan: scanner bypass enables DNS data exfiltration
CVE-2025-46417 Langflow: Unauth RCE via code injection endpoint
CVE-2025-3248 BentoML: unauthenticated RCE via insecure deserialization
CVE-2025-27520 jupyterlab-git: command injection via malicious repo name
CVE-2025-30370 PyTorch: memory corruption in CUDA caching allocator
CVE-2025-3136 PyTorch: memory corruption in JIT flatbuffer loader
CVE-2025-3121 OpenAI WP Plugin: broken access control on AI settings
CVE-2025-31843 PyTorch: lstm_cell memory corruption, local code exec
CVE-2025-3001 PyTorch: memory corruption in torch.jit.script compiler
CVE-2025-3000 PyTorch: memory corruption in RNN sequence unpacking
CVE-2025-2999 PyTorch: memory corruption in RNN pad_packed_sequence
CVE-2025-2998 PyTorch: DoS via mkldnn_max_pool2d resource leak
CVE-2025-2953 openairinterface5g: segfault enables DoS via crafted UE message
CVE-2025-26265 Mesop: class pollution enables DoS and LLM jailbreak
CVE-2025-30358 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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