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 509 results — High severity, Active exploitationllama-index-core: insecure /tmp dir, model theft risk
CVE-2025-7647 PyTorch: DoS via sparse/dense tensor Inductor compile
CVE-2025-55560 TensorFlow: DoS via Conv2D valid padding crash
CVE-2025-55559 PyTorch: Inductor compiler buffer overflow causes DoS
CVE-2025-55558 PyTorch: DoS via cummin+Inductor NameError in 2.7.0
CVE-2025-55557 PyTorch 2.7.0: DoS via proxy_tensor.py syntax error
CVE-2025-55553 PyTorch: integer overflow in rot90+randn_like causes DoS
CVE-2025-55552 PyTorch: DoS in linalg.lu via malformed slice op
CVE-2025-55551 Transformers: ReDoS in optimizer halts training pipelines
CVE-2025-6921 Flowise: unauthenticated SSRF exposes internal network
CVE-2025-59527 Keras: safe_mode bypass enables RCE via model load
CVE-2025-9906 Keras: safe_mode bypass enables RCE via .h5 model files
CVE-2025-9905 picklescan: file extension bypass allows model RCE
CVE-2025-10155 HuggingFace Transformers: ReDoS in MarianTokenizer
CVE-2025-6638 Picklescan: CRC bypass hides malicious pickle in ZIP
CVE-2025-10156 PickleScan: subclass bypass enables malicious model RCE
CVE-2025-10157 MONAI: unsafe pickle deserialization RCE in data pipeline
CVE-2025-58757 MONAI: unsafe deserialization in CheckpointLoader allows RCE
CVE-2025-58756 MONAI: path traversal allows arbitrary file write
CVE-2025-58755 n8n: unrestricted file upload RCE via Chat Trigger
CVE-2025-56265 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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