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AI Security

False Positive Rates: Griffin AI vs Mythos Benchmarked

Why pure-LLM security products generate false positives that engine-grounded platforms like Griffin AI structurally cannot — with CWEs and real triage data.

Mar 12, 20266 min read
AI Security

Griffin AI vs Gemini for FedRAMP Workflows

Gemini has FedRAMP-authorised deployment options. Griffin AI builds on FedRAMP-aligned infrastructure. The comparison is about what the customer has to build.

Mar 12, 20263 min read
AI Security

Hallucinated Security Findings: Measurable Rates

Pure-LLM security analysis hallucinates findings at rates between 20% and 70% depending on the task and model. Grounding is the architectural answer.

Mar 12, 20262 min read
AI Security

Cursor Enterprise Security Buyer Review 2026

An honest security buyer's review of Cursor Enterprise for 2026: data handling, model isolation, audit posture, and the gaps to negotiate before signing.

Mar 12, 20265 min read
AI Security

Snyk Container Security: What It Scans and How

Snyk Container scans Docker and OCI images for OS and dependency vulnerabilities and recommends better base images. Here is how it works and where its limits are.

Mar 12, 20266 min read
AI Security

AI Data Security Solutions: What Actually Protects Your Data?

AI data security solutions cover the tools and controls that protect the data flowing into, through, and out of AI systems. Here is what the category really includes and how to evaluate it.

Mar 11, 20267 min read
AI Security

Zero-Day Discovery Economics: Cost Per Find

The economics of zero-day discovery have been opaque for too long. Here is the actual cost structure of finding a real, defensible bug, and how to think about it.

Mar 11, 20267 min read
AI Security

Rollback Safety: Griffin AI vs Mythos

Sometimes a remediation has to be reverted. Griffin AI's minimal, grounded patches roll back cleanly; Mythos-class patches often do not.

Mar 11, 20266 min read
AI Security

Fine-Tune Backdoors: The Quiet Threat

Fine-tuning a model on an attacker-controlled dataset can implant behaviour that only activates under specific conditions. The threat is quiet because detection is hard.

Mar 11, 20262 min read

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