AI Security
In-depth guides and analysis on ai security from the Safeguard engineering team.
676 articles
Securing MCP Servers in the Enterprise: A Practical Guide
MCP servers connect AI agents to your infrastructure. Here's how to secure them without killing the productivity gains.
AI Models in Your Supply Chain: The Security Risks Nobody Talks About
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.
Framework Routing Awareness: Griffin AI vs Mythos
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 Alignment: Griffin AI vs Mythos
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.
The OWASP Top 10 for Large Language Model Applications: A Field Guide
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 Consumption: Griffin AI vs Mythos
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 Code Review Security: What It Misses
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.
Cursor IDE Security Model: What Enterprises Need to Know
Cursor's 2026 security model introduces privacy modes, indexing controls, and agent sandboxes. Here is the enterprise-ready view of what works.
Regression Gates: Griffin AI vs Mythos
Every release risks making the model worse. Griffin AI's regression gates block bad builds before they ship. Mythos-class tools rarely describe a gate process at all.
XSS Variants: Griffin AI vs Mythos
Stored, reflected, DOM, mutation, and template-injection XSS each live in a different part of the application and demand a different analysis. Griffin's engine understands template contexts, framework escaping rules, and client-side sinks; Mythos reads HTML and hopes. The difference shows up the moment you leave textbook territory.
Griffin AI vs Reka Multimodal for Security
Reka's multimodal models are interesting for specific security workflows. The question is whether multimodal is the binding constraint, and usually it isn't.
Enterprise AI Incident Response Playbooks
AI incidents are not the same shape as traditional security incidents. The playbooks need to be specific to how AI systems actually fail.