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 2388 resultsKeras: safe_mode bypass enables RCE via model loading
CVE-2025-1550 PyTorch: improper init in quantized sigmoid skews model output
CVE-2025-2149 PyTorch: memory corruption in JIT profiler callback handler
CVE-2025-2148 picklescan: ZIP flag bypass enables RCE in PyTorch models
CVE-2025-1945 picklescan: ZIP spoof lets malicious PyTorch models bypass scan
CVE-2025-1944 Ray: Redis password exposed via plaintext logging
CVE-2025-1979 spacy-llm: SSTI allows unauthenticated RCE (CVSS 9.8)
CVE-2025-25362 B2B Login Panel: SQLi enables unauthenticated DB access
CVE-2024-13147 vLLM AIBrix: weak hash in prefix cache leaks inference patterns
CVE-2025-1953 picklescan: scanner bypass enables supply chain RCE
CVE-2025-1716 picklescan: extension bypass enables RCE on model load
CVE-2025-1889 gpt_academic: symlink traversal exposes all server files
CVE-2025-25185 JupyterHub LTI13: JWT forgery enables full auth bypass
CVE-2023-25574 Label Studio: SSRF via S3 endpoint exposes internal services
CVE-2025-25297 Label Studio: reflected XSS via label_config param
CVE-2025-25296 Label Studio SDK: path traversal leaks server filesystem
CVE-2025-25295 Mobuy Panel: SQLi allows unauthenticated DB takeover
CVE-2024-13152 PandasAI: prompt injection enables unauthenticated RCE
CVE-2024-12366 serialize-javascript: XSS via regex in AI/ML dashboards
CVE-2024-11831 vLLM: hash collision enables prefix cache poisoning
CVE-2025-25183 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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