Threat modeling for AI systems has become crucial due to new attack surfaces introduced by technologies like LLMs and RAG pipelines. Security professionals must identify AI-specific assets such as training data and model weights, which require different protection strategies than traditional assets. Frameworks like STRIDE are being adapted for AI, alongside resources like MITRE ATLAS and the OWASP LLM Top 10, to provide a comprehensive approach to assessing and mitigating unique AI-related risks like data poisoning and prompt injection.
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