When we set out to integrate AI capabilities into Nemesis, our Breach and Attack Simulation platform, we faced a common challenge: how do you build a flexible AI agent that supports multiple LLM backends (including OpenAI, Claude/Anthropic, other future models) while exposing them through different user interfaces tailored to distinct workflows? The answer lay in creating a clean separation of concerns with two layers of abstraction : a backend interface that normalizes diffe

Yesterday's news told the same story we hear every week: another supply chain attack, another NPM compromise, another reminder that traditional security approaches aren't keeping pace with reality. This time it was the Shai Hulud worm infecting thousands of GitHub projects. But here's the thing, this exact attack happened 69 days ago. And 4 years ago. Same technique, same exploitation path, just more sophisticated execution. The security industry loves to panic after each bre

We all know this: AI is transforming cyber threats. Attackers now use it to find vulnerabilities faster, automate complex attack chains, and evade detection with unprecedented sophistication. AI presents many opportunities for defenders as well, however we see the security industry wrapping AI around traditional tools and calling it innovation. At Nemesis, we took a different approach: we built an AI operator that actually runs security validation, not just reports on it. The