AI Security
CycloneDX ML-BOM in 1.7: Implementation Guide
CycloneDX 1.7 was published in October 2025 and adopted by the General Assembly in December. We unpack what the ML-BOM capability means in practice for AI inventory.
Jan 15, 20267 min read
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Context Window As A Security Limit
The context window is usually marketed as a capability parameter. In a security setting, it behaves like a budget, a forgetting function, and an attack surface all at once.
Jan 15, 20268 min read
AI Security
Griffin AI vs Gemini Ultra for Security Reasoning
Gemini Ultra sets a high bar on complex reasoning benchmarks. But security reasoning is not benchmark reasoning. Here's how Griffin AI's engine-first approach changes the outcome.
Jan 15, 20267 min read
AI Security
CycloneDX Support: Griffin AI vs Mythos
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.
Jan 15, 20267 min read
AI Security
Training Data Provenance: The Regulatory Wave
Regulators across three continents are converging on a single demand: show where your training data came from. The engineering implications are larger than most labs have admitted.
Jan 14, 20266 min read
AI Security
Call Graph Depth Compared: Griffin AI vs Mythos
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.
Jan 14, 20266 min read
AI Security
Enforcing container compliance with Azure Policy
How Azure Policy enforces container compliance on AKS—registry restriction, regulatory mapping, and where admission-time policy alone falls short.
Jan 14, 20268 min read
AI Security
Eval Methodology: Griffin AI vs Mythos
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.
Jan 13, 20267 min read
AI Security
SQL Injection Chains: Griffin AI vs Mythos
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.
Jan 13, 20267 min read
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