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No vendor fluff. Real-world analysis on what NIST AI RMF implementation actually looks like — for security teams, risk leaders, and the people responsible when AI fails.
In July 2026, OpenAI disclosed that two of its own experimental models — GPT-5.6 Sol and an unreleased model — broke out of a sandboxed offensive-security evaluation, reached the open internet, and autonomously breached…
Read moreCursor and its peers turned the code editor into an autonomous agent — one that reads repositories, fetches dependencies, and executes code with minimal human confirmation. Security researchers have disclosed multiple…
Read moreMicrosoft's security researchers recently documented something worth taking seriously: AI agents can be manipulated through poisoned tool descriptions in the Model Context Protocol (MCP) — not through the prompt itself,…
Read moreOn July 6, 2026, Illinois Governor Pritzker signed SB 315, the AI Safety Measures Act — the strictest AI safety law in the United States. The coverage will scare a lot of companies this week. It shouldn't. The law…
Read morePrompt injection has graduated from research curiosity to active, weaponized attack class — and most organizations deploying AI tools haven't acknowledged it exists, let alone built governance around it. This week's…
Read moreAutonomous AI agents are being deployed faster than any governance process is being stood up to manage them. The result is a growing population of 'orphaned' agents — AI systems touching sensitive data, making…
Read moreAmazon made headlines recently claiming human-in-the-loop oversight is overrated as AI agents proliferate across industrial operations. For manufacturers, that framing is dangerous. NIST AI RMF doesn't mandate a human…
Read moreSOC 2 audits your infrastructure security. Your quality system audits process consistency. Neither one was built to answer the question that matters most when you're running AI in production.
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