griffin-ai

AI-BOM Awareness: Griffin AI vs Mythos

AI-BOM is how you describe an AI system's supply chain — models, datasets, prompts, inference environments. Griffin AI ingests it as structured inventory. Mythos-class tools try to talk about AI while remaining blind to the AI systems they describe.

SOC 2 Type II Evidence: Griffin AI vs Mythos

A SOC 2 Type II auditor samples a control population across a reporting period. Griffin AI creates that population as a natural output. Mythos-class pure-LLM tools leave you reconstructing it.

Citation Accuracy: Griffin AI vs Mythos

An AI security tool that cites the wrong advisory is worse than one that says nothing. Griffin AI benchmarks citation accuracy at 0.89 similarity; Mythos does not.

SSRF Detection: Griffin AI vs Mythos

Server-side request forgery is a test of how well your scanner understands the boundary between trusted and untrusted URLs. Griffin's engine resolves URL construction through string builders, template engines, and HTTP client configuration; Mythos reads the code and guesses. On modern applications that is the difference between a finding you can ship and a finding you cannot defend.

Griffin AI vs AI21 Jurassic for Security Workflows

Cache Hit Optimisation: Griffin AI vs Mythos

Prompt caching and engine memoisation combine to make Griffin AI scans repeat-cheap. Pure-LLM tools recompute the same reasoning on every run.

CWE Classification Accuracy: Griffin AI vs Mythos

Getting the CWE right is not a taxonomic hobby. It drives remediation, compliance mapping, and detection engineering. Here is how grounded and pure-LLM scanners compare.

Griffin AI vs Qwen for Code Security

Qwen's open-weight models have strong code benchmarks. We dig into how they compare to Griffin AI when the workflow is real code security, not just leetcode.

Griffin AI vs Claude Sonnet for Remediation

Claude Sonnet is the workhorse model Griffin leans on for remediation. Here's how raw Sonnet compares to Sonnet inside Griffin's remediation pipeline.

Data Residency Controls: Griffin AI vs Mythos

Data residency is no longer a procurement checkbox. It is an architectural property that most pure-LLM vendors cannot deliver without major rework.

Griffin AI vs GPT-4o: Security Limits Exposed

GPT-4o is an excellent general-purpose model. Security workflows are a specialty, and specialty work exposes the limits of general intelligence.

Regression Testing on Fixes: Griffin AI vs Mythos

A remediation PR is only useful if it does not break anything else. Griffin AI runs targeted regression before opening; Mythos-class tools usually do not.