AI Security

A technical guide on implementing AI governance, virtual keys, and MCP tool management using the open-source Bifrost gateway and Edge agent.

Recent studies reveal that AI agents are 50 times more likely to leak API keys and secrets in their internal reasoning steps than in their final answers. This guide explores how to identify and mitigate these invisible leaks.

OpenAI has reportedly agreed to a request from the Trump administration to stagger the release of GPT-5.6, implementing a limited preview for enterprise customers with government oversight.

A deep dive into how autonomous email agents built with LangGraph can be hijacked via indirect prompt injection and how to use AgentBreak to secure your AI workflows.

Following intervention by the US government, Anthropic's Fable 5 and Mythos 5 models were pulled from release. This article explores the technical implications of guardrail bypasses, the industry backlash, and how developers can maintain resilience through multi-model platforms like n1n.ai.

Anthropic has abruptly disabled access to its Fable 5 and Mythos 5 models following a federal mandate citing national security risks, raising significant concerns for global AI developers regarding model stability and geopolitical influence.

OpenAI introduces Lockdown Mode, a security feature designed to prevent sensitive data exposure during indirect prompt injection attacks. While not a silver bullet, it represents a significant step in LLM security architecture.

Bridging the gap between AI prototypes and production-ready systems using MeshFlow and high-performance LLM APIs.

A comprehensive breakdown of May 30, 2026 AI news, focusing on Anthropic's market dominance, the new Claude Opus 4.8 architecture, and the critical SymJack RCE vulnerability affecting major AI coding agents.

A deep dive into the first documented case of an AI-generated zero-day exploit targeting 2FA, exploring the shift from AI assistants to AI operators and how to defend your infrastructure.

Learn how to build zero-cost, zero-trust AI agents using local Qwen models and the MCPS protocol for cryptographic tool-call integrity and absolute data privacy.

An in-depth analysis of how autonomous AI agents can exploit internal RAG systems like McKinsey's Lilli, featuring exploit paths, architectural vulnerabilities, and defense strategies.