Platform

The adversarial test bench for production AI

One platform to find and fix vulnerabilities across computer vision, audio, and sensor systems, before input noise or cyber actors do.

01Differentiation

Why Mirage

True white-box attacks
Real backprop through modern detection heads, not the edge-map proxies most tools ship
Physical-world realism
Attacks survive printing, viewing angle, altitude, and lighting, not just clean digital inputs
One platform, many domains
Vision, audio, text, and signal under a single run-orchestration layer
Runs today
A live platform with 20+ attack methods across four model types and zero setup
Pluggable attack engines
Swap between our native engine and validated open-source toolkits without changing your workflow
Deploys where data can't leave
Secure, on-premise deployments for the environments that demand it
02Portfolio

Six products, one platform

One run-orchestration layer across vision, audio, text, and signal. A red-team pipeline running today; autonomous-systems evaluation on the roadmap. Tap a product to expand it.

03Why now

The window is open, briefly

01

From advice to action

A wrong prediction used to be a suggestion a person could catch. Now the model acts on it: it steers the drone, clears the transaction, flags the target. The cost of a single failure has changed category.

02

The weights are already public

The same open models that accelerate you hand an adversary a perfect offline copy. They can rehearse an attack a thousand times, at zero cost, before they ever touch your system.

03

Accuracy was hiding it

Robustness has never blocked a launch, because the failures do not appear in a benchmark. They appear when someone goes looking. That someone is now well-resourced and patient.

See it attack a live model

The interactive platform runs 10+ attack methods across vision, audio, text, and network models, with pluggable attack backends and autonomous ONNX testing.