All news with #llm security tag

🔒 Microsoft outlines a layered defense-in-depth strategy to protect systems using LLMs from indirect prompt injection attacks. The approach pairs preventative controls such as hardened system prompts and Spotlighting (delimiting, datamarking, encoding) to isolate untrusted inputs with detection via Microsoft Prompt Shields, surfaced through Azure AI Content Safety and integrated with Defender for Cloud. Impact mitigation uses deterministic controls — fine-grained permissions, Microsoft Purview sensitivity labels, DLP policies, explicit user consent workflows, and blocking known exfiltration techniques — while ongoing research (TaskTracker, LLMail-Inject, FIDES) advances new design patterns and assurances.