ai-security
Safeguard articles tagged "ai-security" — guides, analysis, and best practices for software supply chain and application security.
532 articles
Griffin AI vs Claude Agent Skills for Security
Anthropic's Claude Agent Skills let you package tools and context for Claude. Here's how that primitive compares to Griffin's security-specific workflow scaffolding.
Griffin AI vs Mythos: The Security Platform Comparison
A senior engineer's side-by-side look at Griffin AI and Mythos — why engine-grounded reasoning beats pure-LLM security intuition when the audit clock starts.
Griffin AI vs GPT-5: Context Grounding
A million-token context window is a tool, not a solution. Context grounding for security requires architecture, not just capacity.
Evaluating Security-Specific Reasoning Models
Reasoning models have arrived in security tooling. Evaluating them requires different methodology from evaluating classification or generation models. Here is what good evaluation looks like.
RSA Conference 2026: Supply Chain Themes
RSA Conference 2026 centered on AI governance, software supply chain regulation, and vendor consolidation. Here is the analyst view of what mattered.
Tool-Call Privilege Escalation In Practice
When an agent can call tools, the permission boundary is no longer between the user and the system. It is between the model's current beliefs and everything the model can reach. That is a much harder boundary to defend.
Griffin AI vs Gemini Function Calling: Security
Gemini's function calling is strong and flexible. Griffin AI's tool layer is narrow and opinionated. For security workflows, the opinionated approach wins.
MCP Server Multi-Tenant Isolation
Practical guidance on isolating tenants on shared Model Context Protocol servers, covering identity, data, compute, and observability boundaries at production scale.
AI Model Weights: Signing, Attestation, Provenance
Model weights are binaries with the privilege of code and the review of documents. Here is what signing, attestation, and provenance should actually look like.
AI-BOM Adoption: State of the Art in 2026
The AI Bill of Materials went from concept paper to procurement requirement in under two years. Here is what the current state of the art actually looks like.
Dynamic Dispatch: Griffin AI vs Mythos
Dynamic dispatch hides real exploits behind indirection. Griffin AI models the dispatch; Mythos-class tools guess. That gap changes outcomes.
LLM Jailbreak as a Supply Chain Risk in 2026
A jailbreak in a model you ship downstream is a supply chain incident, not a trivia item. Here is how to reason about it and where the defensive controls belong.