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 462 results — High severity, has patchjupyter_core: config hijack enables cross-user code exec
CVE-2025-30167 Label Studio: XSS enables unauthorized actions via CSRF
CVE-2025-47783 llama_index: DoS via uncapped recursion in web reader
CVE-2025-1752 LLaMA-Factory: RCE via torch.load() unsafe deserialization
CVE-2025-46567 picklescan: scanner bypass enables DNS data exfiltration
CVE-2025-46417 jupyterlab-git: command injection via malicious repo name
CVE-2025-30370 litellm: privilege escalation viewer→proxy admin via bad API key
CVE-2025-0628 LiteLLM: API key leakage in logs exposes credentials
CVE-2024-9606 litellm: unauthenticated DoS via multipart boundary parsing
CVE-2024-8984 OpenWebUI: path traversal RCE via audio upload API
CVE-2024-8060 open-webui: DoS via malformed multipart boundary
GHSA-6wj5-5pgr-jwq8 Open-WebUI: CSRF enables RCE via pipeline code injection
CVE-2024-7806 ONNX: path traversal in download_model enables RCE
CVE-2024-7776 lollms: RCE via eval() sandbox bypass in Calculate
CVE-2024-6982 litellm: unauthenticated DoS crashes LLM proxy server
CVE-2024-10188 Label Studio: SSRF via S3 endpoint exposes internal services
CVE-2025-25297 Label Studio SDK: path traversal leaks server filesystem
CVE-2025-25295 TorchGeo: RCE via code injection in geospatial ML lib
CVE-2024-49048 ONNX: path traversal in model download enables RCE
CVE-2024-5187 Nginx-UI: command injection via settings API
CVE-2024-22198 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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