AI Security
Cost Per Finding: Griffin AI vs Mythos
Token spend per scan is the wrong metric. Cost per actionable finding is the right one — and it's where engine-plus-LLM economics dominate pure-LLM economics.
Mar 8, 20265 min read
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Griffin AI vs Open Weights: The Eval Gap
Frontier models pass eval benchmarks that open-weight models miss by specific measurable margins. For security workflows, the gap matters.
Mar 7, 20263 min read
AI Security
Elastic Scale Behaviour: Griffin AI vs Mythos
Scanning bursts when a monorepo merges. We explain why Griffin AI absorbs the spike gracefully while Mythos-class tools degrade into rate-limit queues.
Mar 7, 20266 min read
AI Security
Enterprise AI Red Team Program Design
AI red teaming is not a one-off exercise. Programmatic red-teaming of AI systems requires specific structure — and most organisations don't have it yet.
Mar 7, 20262 min read
AI Security
Coordinated Disclosure With Upstream Maintainers
Coordinated disclosure with open-source maintainers is a relationship business. Here is what makes it work in 2026, with the artefacts a modern pipeline gives you.
Mar 6, 20267 min read
AI Security
Auth Bypass Discovery: Griffin AI vs Mythos
Auth bypasses are rarely a single bug. They live in the interaction between layers — middleware, route handlers, framework annotations. Finding them requires path analysis across abstraction layers.
Mar 6, 20265 min read
AI Security
Griffin AI vs Claude Prompt Caching: Security
Claude's prompt caching gives you 90% discount on cached tokens. Security workloads have massive cacheable surface area. Griffin AI takes advantage; direct API use often does not.
Mar 6, 20262 min read
AI Security
The Reproducibility Crisis In AI Security Evals
ML research has a reproducibility crisis. AI security evaluation inherits it. Vendors publishing numbers that can't be reproduced are the norm — not the exception.
Mar 6, 20262 min read
AI Security
Griffin AI vs OpenAI Assistants API for SecOps
The OpenAI Assistants API is a general agent framework. SecOps needs more than a framework — it needs the engine-grounded reasoning Griffin AI adds on top.
Mar 5, 20263 min read
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