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 3019 results CVE-2022-36018 TensorFlow: RaggedTensor CHECK fail remote DoS 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35990 TensorFlow: DoS via quantization gradient rank check 7.5 0.4% tensorflow Sep 16 HIGH CVE-2022-35989 TensorFlow: MaxPool GPU kernel DoS via oversized ksize 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35988 TensorFlow: GPU DoS via empty input to matrix_rank op 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35987 TensorFlow: DoS via DenseBincount shape mismatch 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35986 TensorFlow: RaggedBincount DoS crashes inference server 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35985 TensorFlow: DoS via malformed LRNGrad tensor input 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35984 TensorFlow: int64 type mismatch triggers remote DoS 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35983 TensorFlow: DoS via Save/SaveSlices dtype CHECK fail 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35982 TensorFlow: DoS via invalid SparseBincount input 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35981 TensorFlow: DoS via FractionalMaxPoolGrad assertion 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35979 TensorFlow: DoS via nonscalar input in QuantizedRelu 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35974 TensorFlow: DoS via nonscalar quantization op input 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35973 TensorFlow: DoS via QuantizedMatMul input validation 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35972 TensorFlow: DoS via QuantizedBiasAdd rank validation 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35971 TensorFlow: DoS via invalid quantization tensor rank 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35970 TensorFlow: DoS via malformed QuantizedInstanceNorm tensors 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35969 TensorFlow: DoS via malformed Conv2DBackpropInput 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35968 TensorFlow: DoS via AvgPoolGrad shape validation failure 7.5 0.4% tensorflow Sep 16 HIGH E CVE-2022-35967 TensorFlow: DoS via QuantizedAdd tensor rank flaw 7.5 0.4% tensorflow Sep 16 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.
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