See the entire AI attack surface — not just the buzzwords.
Most explainers say “secure your LLM” and stop there. This page shows exactly how a prompt travels from a user to enterprise data and back — where it can be attacked at every hop, how each attack is detected, and which framework each control satisfies. Explore the pipeline, the threat library, live simulations, and a self-assessment, all on one page.
Every AI component, examined separately
Click any layer to see what’s checked, how it’s attacked, how it’s detected, and which controls cover it.
Watch a single request move through the security pipeline
Every real request — benign or malicious — passes through these checkpoints in order. Replay the trace to see each stage light up as it fires.
AI Threat Library
21 attack techniques across the AI stack — each with MITRE ATLAS mapping, detection logic, IOC examples, a Sigma rule, and recommended controls.
Run an attack. Watch it get caught.
Pick a technique and trace it live through the detection pipeline — from malicious input to policy decision.
AI Security Controls Library
The controls that map to every layer above — what each does, where it sits, and which threats it mitigates.
MITRE ATLAS Matrix
Adversarial ML tactics, left to right. Click a technique to see the full detail card.
One control, many frameworks
Expand a framework to see which mapped capability areas satisfy it.
AI Asset & Technology Library
The models, frameworks, vector stores, and gateways any AI security program has to account for.
AI Incident Library
Illustrative summaries of widely-reported AI security events — timeline, impact, and the lesson each one teaches.
AI Risk Dashboard
A representative view of the telemetry these controls surface once wired into a SIEM/SOAR. Sample data for illustration.
AI Security Readiness Score
16 questions across 7 domains. Get an instant score, a per-domain breakdown, and a downloadable summary.
Overall score: —/100
AI Security Glossary
