DeepMind Researchers Propose Defense Against LLM Prompt Injection

To prevent prompt injection attacks when working with untrusted sources, Google DeepMind researchers have proposed CaMeL, a defense layer around LLMs that blocks malicious inputs by extracting the control and data flows from the query. According to their results, CaMeL can neutralize 67% of attacks in the AgentDojo security benchmark.

Docker Bridges Agents and Containers with New MCP Catalog and Toolkit

Docker has announced two new AI-focused tools—the Docker MCP Catalog and the Docker MCP Toolkit—to bring container-grade security and developer-friendly workflows to agentic applications, helping build a developer-centric ecosystem for Model Context Protocol (MCP) tools.

Meta Launches AutoPatchBench to Evaluate LLM Agents on Security Fixes

AutoPatchBench is a standardized benchmark designed to help researchers and developers evaluate and compare how effectively LLM agents can automatically patch security vulnerabilities in C/C++ native code.

Meta Open Sources LlamaFirewall for AI Agent Combined Protection

LlamaFirewall is a security framework aimed at safeguarding AI agents against prompt injection, goal misalignment, and insecure code generation. It achieved over 90% efficacy in reducing attack success rates when evaluated on the AgentDojo benchmark. Additionally, developers can update its behavior by adding new security guardrails.

Llama 4 Scout and Maverick Now Available on Amazon Bedrock and SageMaker JumpStart

AWS recently announced the availability of Meta’s latest foundation models, Llama 4 Scout and Llama 4 Maverick, in Amazon Bedrock and AWS SageMaker JumpStart. Both models provide multimodal capabilities and follow the mixture-of-experts architecture.