AI Threat AlertAI 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 2876 results — no patchTensorFlow: CHECK-fail DoS in tf.sparse.cross op
CVE-2022-35997TensorFlow: Conv2D DoS via empty input tensor
CVE-2022-35996TensorFlow: DoS via AudioSummaryV2 CHECK failure
CVE-2022-35995TensorFlow: CollectiveGather assertion DoS via scalar
CVE-2022-35994TensorFlow: DoS via malformed SetSize tensor shape
CVE-2022-35993TensorFlow: DoS via malformed TensorList element shape
CVE-2022-35992TensorFlow: DoS via TensorListScatter CHECK fail
CVE-2022-35991TensorFlow: DoS via QuantizeAndDequantizeV3 CHECK fail
CVE-2022-36026TensorFlow: DoS via FakeQuant tensor rank mismatch
CVE-2022-36019TensorFlow: RaggedTensor CHECK fail remote DoS
CVE-2022-36018TensorFlow: DoS via quantization gradient rank check
CVE-2022-35990TensorFlow: MaxPool GPU kernel DoS via oversized ksize
CVE-2022-35989TensorFlow: GPU DoS via empty input to matrix_rank op
CVE-2022-35988TensorFlow: DoS via DenseBincount shape mismatch
CVE-2022-35987TensorFlow: RaggedBincount DoS crashes inference server
CVE-2022-35986TensorFlow: DoS via malformed LRNGrad tensor input
CVE-2022-35985TensorFlow: int64 type mismatch triggers remote DoS
CVE-2022-35984TensorFlow: DoS via Save/SaveSlices dtype CHECK fail
CVE-2022-35983TensorFlow: DoS via invalid SparseBincount input
CVE-2022-35982TensorFlow: DoS via FractionalMaxPoolGrad assertion
CVE-2022-35981Frequently 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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