Supply Chain Security, in plain English.

Griffin AI vs AI21 Jurassic for Security Workflows

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.

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.

Enterprise RAG Security Rollout Antipatterns

Retrieval-augmented generation systems are where enterprise AI meets enterprise data, and where most security rollouts stumble. A catalog of the antipatterns we keep seeing.

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 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.

SecBench Methodology Reviewed

SecBench positioned itself as a comprehensive cybersecurity knowledge and reasoning benchmark for LLMs. A methodology review of its construction, scoring, and the gaps that separate the advertised coverage from what the benchmark actually exercises.

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.

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.