AI-AI War
Adversarial Validation
Measure defensive performance against autonomous adversaries - not opinions, scorecards.
At a Glance
Simulate adversarial AI attacks on your models. Input your ML pipeline, get attack scenarios, robustness scores, and hardening recommendations to defend against model manipulation.
The Problem
Security products make claims about detection and response, but buyers have no way to validate them. Vendor demos are cherry-picked. Real-world testing is expensive and inconsistent. Decisions are based on opinions, not evidence.
The Solution
AI-AI War runs adversarial scenarios against defensive tools and captures telemetry. Repeatable benchmarks produce p50/p95-style metrics. Scorecards answer real buyer questions with evidence, not marketing.
Capabilities
Production-ready features designed for enterprise integration.
Scenario Runner
Execute adversarial scenarios against target defenses.
Repeatable Benchmarks
Consistent metrics (p50/p95 style) across runs.
Buyer-Aligned Scorecards
Answers mapped to real purchase decision questions.
Validation Harness
Test security claims with reproducible evidence.
Evidence & Proof Points
Hard numbers and verifiable outputs for your due diligence.
Sample Outputs
Integration
Clear inputs and outputs for seamless integration into your stack.
Inputs
- Adversarial scenario definitions
- Target defense configurations
- Benchmark parameters
- Telemetry collection settings
Outputs
- Benchmark scorecards
- Telemetry captures (JSONL)
- Detection metrics
- Response time analysis
- Comparative reports
Ideal For
Best-fit buyer profiles and use cases.
Validate detection claims before shipping.
Test vendor claims with reproducible evidence.
Benchmark defensive AI against adversarial scenarios.
Ready for a Deep Dive?
Schedule a 20-minute technical walkthrough to see AI-AI War in action and discuss integration options.