frontier models

EU AI Act Enforcement: Year One Review

The first enforcement window under the EU AI Act has closed. The actual pattern of enforcement looks different from the one vendors and advocacy groups predicted.

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.

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.

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.

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.

Griffin AI vs Inflection Pi for Security Assistance

Small-Model Distillation For Security Workflows

Distillation compresses the capability of a large model into a small one for a narrow task. For high-volume security workflows, it is often the difference between a working pipeline and an unaffordable one.

Training Data Opacity As A Trust Limit

You cannot audit what you cannot see. Frontier model training corpora are effectively opaque to their users, and that opacity is not incidental. It shapes what kinds of trust you can extend to the outputs.

Agent Security: Enterprise Adoption Patterns

Enterprise agent deployments have moved past pilot phase. The security patterns that have survived contact with production look different from the ones the industry was selling a year ago.

Griffin AI vs AI21 Jurassic for Security Workflows

Domain-Adapted LLMs For Vulnerability Detection in 2026

Domain adaptation has quietly become the default for LLM-assisted vulnerability detection. A look at what works in 2026, what does not, and what teams should plan for next.

Instruction/Data Conflation: Why Prompt Injection Persists

Prompt injection is not a vulnerability that will be patched. It is what happens when a system cannot distinguish the instructions it is supposed to follow from the data it is supposed to process.