MCP vs Skills vs Hooks vs Rules Explained
MCP, Skills, hooks, and rules extend AI coding agents in very different ways — two execute code, two only steer behavior. Here's how each one breaks.
Deep dives, practical guides, and incident analyses from engineers who build Safeguard. No fluff, no vendor FUD — just what you need to ship secure software.
MCP, Skills, hooks, and rules extend AI coding agents in very different ways — two execute code, two only steer behavior. Here's how each one breaks.
The explosion of AI tools like ChatGPT is reshaping how developers write code — and introducing new supply chain risks that most teams aren't thinking about.
Auto-remediation uses AI to generate and PR real fixes for vulnerabilities — not just flag them. Here's how it decides what's safe to auto-fix.
Unsafe deserialization looks obvious on a slide and impossible on a real codebase. Sinks are language-specific, gadgets live in third-party libraries, and the tainted byte can arrive wrapped in six layers of framework ceremony. Griffin's engine-plus-LLM design handles each of those concerns separately; Mythos-style pure-LLM scanners blur them into pattern-matching.
AI agents are consuming APIs, installing packages, and executing code autonomously. The security implications are massive and largely unaddressed.
Opus for reasoning, Sonnet for drafting, Haiku for scale. We break down when each tier earns its keep and why single-model architectures cannot compete.
Most AI bug hunters skip the hardest step: trying to kill their own findings. Here is why Griffin AI's disproof pass is the single biggest lever on false-positive rate.
Enterprise identity is not a paywall. It is the substrate on which every other security control depends, and it is where Mythos-class vendors quietly fall behind.
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