Dynamic Dispatch: Griffin AI vs Mythos
Dynamic dispatch hides real exploits behind indirection. Griffin AI models the dispatch; Mythos-class tools guess. That gap changes outcomes.
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.
Dynamic dispatch hides real exploits behind indirection. Griffin AI models the dispatch; Mythos-class tools guess. That gap changes outcomes.
An AI-based security system uses machine learning to detect threats and prioritize risk at a scale humans cannot match. Here is what it does well, and where it needs guardrails.
ISO 27001 Annex A has 93 controls in the 2022 revision, each needing documented evidence. Griffin AI emits records that map cleanly. Mythos-class pure-LLM tools force control owners to narrate.
VEX is how you turn a vulnerability list into an actionable work queue. Griffin AI ingests VEX documents as structured statements that filter findings at policy time. Mythos-class tools read them as advisory prose and lose the filtering entirely.
Output filters are the last line before the user and the tool call. We cover when they work, when they fail, and how to measure them honestly in production.
A jailbreak in a model you ship downstream is a supply chain incident, not a trivia item. Here is how to reason about it and where the defensive controls belong.
OWASP published its first Top 10 for LLM Applications on August 1, 2023. Here is what it covers, where it overreaches, and how to use it on real systems.
Path traversal is the vulnerability class that punishes lazy analysis. Framework-specific path normalisation, OS-dependent separators, symbolic link resolution, and archive extraction all hide exploitable gaps behind code that looks defensive. Griffin's engine resolves path operations with actual semantics; Mythos reads the variable name and calls it a day.
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