AI Pulse · Under the Radar

A developer just published a library that teaches Claude how to think like a penetration tester. Claude-red is a collection of 58 curated skill files that prime the model with offensive security methodology across web applications, Active Directory, wireless networks, cloud infrastructure, mobile platforms, and fuzzing. It hit 680 stars, 208 watchers, and 86 forks in three days, making it one of the fastest-moving repositories in the security space right now.

Each skill file is a structured prompt that walks Claude through specific attack surfaces and techniques. Instead of asking the model to “find vulnerabilities,” you load a skill that explains how to enumerate cloud storage misconfigurations or test Active Directory trust relationships. The model then applies that framing to whatever target you point it at. It’s built for red teams, bug bounty hunters, and capture-the-flag competitors who want an AI assistant that already knows the playbook.

This matters because it shows how fast domain-specific AI tooling is moving outside the usual enterprise channels. A single developer can now package expert methodology into reusable prompts and distribute them to thousands of practitioners in days. If your company runs security audits, penetration tests, or bug bounty programs, this kind of tooling is already in the hands of the people testing your systems. It also signals a broader shift: AI assistants are no longer general-purpose helpers. They’re becoming specialist tools loaded with field-tested knowledge, and they’re spreading through open repositories faster than most procurement cycles can track.

If you’re building internal AI tools, the same principle applies. You can encode your company’s specific workflows, compliance checks, or troubleshooting steps into structured prompts that make the model immediately useful to your team. That’s the kind of thing we build into an AI command centre at /resources/omni, turning generic models into tools that already know how your business works.