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.
FedRAMP HIGH demands 421 controls with documented, continuous evidence. Griffin AI produces control-mapped records every day. Mythos-class pure-LLM tools cannot fill a 3PAO evidence package.
Taint tells you whether attacker data actually reaches a sink. Griffin AI propagates it; Mythos-class tools infer it. The difference shows up fast.
MCP server discovery turns a client connection string into a live capability graph. The protocol mechanics that make this convenient also widen the blast radius when discovery is spoofed, tampered with, or silently reshaped mid-session.
A balanced look at what artificial intelligence and cyber security actually means in practice today, the concrete benefits teams are seeing and the new risks AI introduces into the same systems.
Pickle-serialized model files remain a live attack surface on Hugging Face. Here is what 2025 research disclosed about persistent backdoors and what defenders should do about it.
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.
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.
Griffin AI reports 98-100% hold rate against adversarial probes. Most Mythos-class tools have never published an adversarial number at all.
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.
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