AI Security

Top AI Cybersecurity Companies to Watch in 2026

The top AI cybersecurity companies of 2026 span three distinct plays — AI-assisted detection, AI-native SOC automation, and AI-augmented AppSec — and the distinction matters when you're evaluating vendors.

Docker MCP Server: Setup and Security Considerations

Running a docker mcp server puts an AI agent's tool access inside a container boundary, which helps containment but doesn't remove the need to scope credentials and network access carefully.

Adversarial Resistance: Griffin AI vs Mythos

Griffin AI reports 98-100% hold rate against adversarial probes. Most Mythos-class tools have never published an adversarial number at all.

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.

What is Auto-Remediation (AI-Powered Fixes)

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.

Deserialization Vulnerabilities: Griffin AI vs Mythos

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 Agent Security Risks: Why Autonomous Systems Are the Next Supply Chain Frontier

AI agents are consuming APIs, installing packages, and executing code autonomously. The security implications are massive and largely unaddressed.

Griffin AI vs Cohere Command for SecOps

The Disproof Step: Griffin AI vs Mythos

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.

Model Tiering Strategy: Griffin AI vs Mythos

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.

AI Safety Eval Datasets as Supply Chain

The datasets you use to evaluate model safety are themselves a supply chain, and almost nobody is treating them that way. A senior engineer's audit of how eval corpora get poisoned, contaminated, and silently drifted.

Enterprise AI Agent Deployment Lessons, 2026

Lessons learned from a year of enterprise AI agent deployments: what worked, what failed, and what we would do differently starting now.