Task-Routed LLM Architectures For Security
One model for every task wastes budget on trivial work. Task-routed architectures match model capability to task requirements — the right lever for security at scale.
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.
One model for every task wastes budget on trivial work. Task-routed architectures match model capability to task requirements — the right lever for security at scale.
Retrieval context poisoning scales differently than direct prompt injection. The attacker's leverage grows with the RAG ingest surface.
Gemini's multimodal capabilities are genuinely useful for some security workflows. For most security workflows, the modality is code and text, not images.
Two years ago, AI vendors shipped without evals. In 2026, the posture has shifted. Customers expect benchmarks. Vendors without them lose deals.
Taint analysis only works if sources and sinks are labeled correctly. Griffin AI uses a curated catalog; Mythos-class tools infer on the fly.
Multi-agent systems inherit every trust problem of single-agent systems and add a few more. Here is how the threat model actually shifts.
CSRF in 2026 is not the 2012 attack. SameSite cookies, fetch metadata, and modern frameworks changed the landscape. Detection needs to keep up.
AI-for-security procurement covers more than feature comparison. The due diligence checklist that surfaces structural differences between vendors.
CWE-502 deserialisation chains are the canonical stress test for AI bug hunters. Why Griffin AI's grounded synthesis finds real chains and Mythos-class scanners hallucinate them.
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