AI Security
In-depth guides and analysis on ai security from the Safeguard engineering team.
676 articles
Griffin AI vs Gemini Pro for Security Workflow
Gemini Pro brings capable reasoning and a massive context window to general-purpose workflows. Griffin AI brings a security engine with an LLM on top. The difference matters when the workflow is appsec.
SBOM Ingestion: Griffin AI vs Mythos
A detailed comparison of how Griffin AI consumes SBOMs as structured reasoning context while Mythos-class pure-LLM tools skim them as prose — and why that architectural gap determines the quality of every downstream finding.
Prompt Injection At Scale: 2026 Trend Review
Prompt injection has evolved from demonstration exploits into a category of attack that runs continuously against production AI systems. Here is what changed in 2026.
Published Benchmarks: Griffin AI vs Mythos
Griffin AI publishes a five-family eval harness with concrete numbers. Most Mythos-class competitors ask buyers to trust marketing claims instead of data.
AI Code-Generation Audit Trail Patterns
When AI writes code that ships to production, the audit trail is a compliance requirement, not a nice-to-have. Patterns for capturing it without killing velocity.
Zero-Day Discovery Pipelines: Griffin AI vs Mythos
A candid look at how Griffin AI's three-stage zero-day pipeline compares to pure-LLM Mythos-class bug hunters, and why false positive rates matter more than raw volume.
On-Prem Deployment: Griffin AI vs Mythos
Why enterprise AI for security requires genuine on-premises deployment, not just a SaaS endpoint with a VPN in front of it.
ChatGPT Atlas and the Permanent Browser-Agent Injection Problem
OpenAI shipped ChatGPT Atlas in October 2025 and admitted by December that prompt injection in AI browsers may never be fully solved. Defenders need a posture, not a patch.
What agentic AI security means and why traditional AppSec...
Traditional AppSec was built for static code, not decision-making agents. Here's what agentic AI security actually covers—and why autonomous agents need a new defense model.
Identity and access management for non-human AI agents
AI agents now hold production credentials the way employees do, except most are never offboarded. Here's how AI agent identity and access management closes that gap.
How to authorize and scope permissions for autonomous AI ...
A practical, step-by-step guide to AI agent authorization: scoping permissions, using OAuth for machine identities, and verifying least-privilege boundaries hold in production.
Security risks of multi-agent AI systems collaborating au...
Multi-agent AI systems introduce security risks classic AppSec misses: agent-to-agent exploits, swarm failures, and orchestration trust gaps.