AI Security
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.
Jan 19, 20265 min read
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.
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.
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.
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.
Griffin AI's auto-fixes compile clean 73 percent of the time and pass with minor edits 87 percent. Mythos-class pure-LLM patches rarely show those numbers for a reason.
The EU Cyber Resilience Act wants mandatory vulnerability handling, SBOM delivery, and documented due diligence. Griffin AI produces those artifacts continuously. Mythos-class tools produce conversations about them.
CycloneDX is not a text format to be summarized — it's a typed graph with dozens of semantically-rich fields. Griffin AI consumes it as a graph. Mythos-class tools consume it as tokens. That difference decides every downstream finding.
Shallow call graphs miss real exploits; deep graphs surface them. We examine how Griffin AI and Mythos-class tools differ on depth, and why it matters.
A benchmark number is only as good as the methodology that produced it. Here is how Griffin AI builds its harness and why most Mythos-class tools cannot be audited.
SQL injection stopped being a single-line bug years ago. Modern chains stitch a tainted parameter through ORMs, caches, background jobs, and downstream services. Griffin AI's engine-plus-LLM architecture follows the taint across those hops; Mythos-class pure-LLM scanners summarise one file at a time and lose the thread.
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