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https://simonwillison.net/2025/Jun/13/prompt-injection-design-patterns/
Design Patterns for Securing LLM Agents against Prompt Injections
This new paper by 11 authors from organizations including IBM, Invariant Labs, ETH Zurich, Google and Microsoft is an excellent addition to the literature on...
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https://konghq.com/resources/demos/kong-konnect/owasp-securing-llm-deployments
Securing Enterprise LLM Deployments: Best Practices and Implementation | Kong Inc.
securing enterprisekong inc
https://www.leidos.com/insights/leidos-securing-agentic-ai-future-llm-trust-and-safety
Leidos Is Securing the Agentic AI Future with LLM Trust and Safety | Leidos
Large language model refusal training is essential to ensure AI agents avoid unsafe information sources and tools when accomplishing tasks autonomously.
agentic aileidossecuringllm
https://www.aquasec.com/blog/secure-llm-applications-aqua-beyond-owasp-list/
Securing LLM Apps with Aqua: Beyond the OWASP Checklist
Jul 14, 2025 - Aqua secure LLM apps across code, deploy, and runtime with OWASP-aligned policies and real-time protection, across the full lifecycle of containerized AI
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https://mlsecops.com/podcast/breaking-and-securing-real-world-llm-apps
Breaking and Securing Real-World LLM Apps
Explore insights on securing LLM-integrated applications, addressing prompt injection, and enhancing AI security from Rico Komenda and Javan Rasokat.
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