Framework

AI/ML frameworks sit at the bottom of every AI stack — virtually every production AI system depends transitively on PyTorch or TensorFlow at the training layer, and on LangChain, LlamaIndex, or a similar orchestrator at the application layer. That concentration means a single vulnerability often affects tens of thousands of downstream services. The CVE patterns are recognisable: unsafe deserialization in model loading (the long tail of pickle), template injection in LangChain's prompt-construction utilities, SSRF in LlamaIndex's data-loader connectors, and path traversal in MLflow's experiment storage. PyTorch itself has shipped several high-severity CVEs around its distributed RPC layer. Because these libraries upgrade frequently and downstream applications pin loosely, patching is a real operational problem. AI Threat Alert tracks framework-level CVEs prominently because a single advisory often means urgent work for hundreds of teams.