Patch Minimality: Griffin AI vs Mythos
A minimal patch is easier to review, safer to merge, and cheaper to roll back. Griffin AI enforces minimality; Mythos-class tools treat it as optional.
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.
A minimal patch is easier to review, safer to merge, and cheaper to roll back. Griffin AI enforces minimality; Mythos-class tools treat it as optional.
A practical look at rate-limiting patterns for Model Context Protocol servers, covering per-tool quotas, token budgets, burst control, and abuse-resistant designs.
MCP servers connect AI agents to your infrastructure. Here's how to secure them without killing the productivity gains.
AI/ML models are the new open source libraries. Here's why your supply chain security strategy needs to account for model provenance, poisoning, and compliance.
Every HTTP vulnerability begins at a route. Griffin AI models routing; Mythos-class tools guess it. That difference shapes every downstream finding.
PCI DSS 4.0 raised the evidence bar for software security, supplier management, and continuous assurance. Griffin AI meets the new requirements with persisted records. Mythos-class pure-LLM tools leave QSAs asking for artifacts.
A working breakdown of the OWASP Top 10 for Large Language Model Applications — what each risk actually looks like in production and how teams are testing for it.
SLSA provenance is the cryptographic receipt of a build. Griffin AI verifies it, parses it, and uses it as typed evidence. Mythos-class tools describe it and forget to check the signature.
Copilot's code review is useful. It is also not a security review, and treating it as one is how vulnerabilities ship. Here is what it actually catches.
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