Automated AI Red Teaming for Continuous AI Risk Detection

Trampolyne AI is a continuous AI security validation platform that automatically discovers, verifies, and exploits real vulnerabilities across chatbots, internal copilots, and agentic systems. It tests every layer an attacker can reach, not just the model.

The platform attacks four layers:

1. the model & prompt layer (jailbreaks, system-prompt extraction, indirect injection)
2. the API authorization layer (cross-tenant access testing that names the exact record reached)
3. the tool & MCP layer (function-calling and Model Context Protocol abuse)
4. the agentic workflow layer (privilege escalation, approval bypass, race conditions) across 14 attack families, each mapped to OWASP LLM/API/Agentic Top 10 and MITRE ATLAS.

The engine runs a four-phase process: Recon maps system capabilities and guardrails; Exploit runs multi-turn, multi-modal attack chains across selected threat families; Verify re-runs successful attacks to confirm reproducibility; Judge scores each finding for severity with evidence checked against the actual transcript, eliminating hallucinated findings.

Every finding is delivered as an executive-ready report with clear PASS/FAIL outcomes, reproducible exploit evidence, and mappings to OWASP, MITRE ATLAS, and the regulations governing your AI - EU AI Act, GDPR, India's DPDPA, NIST AI RMF, and ISO/IEC 42001. Ship a fix and re-run the engagement: every finding returns a fixed / still-failing / regressed verdict, so you can prove the gap is actually closed. Safety is built in, not bolted on - runs are restricted to authorized targets only, testing is non-destructive by design (no destructive tool or database actions), and an always-on SSRF guard prevents misuse.

Typical usage patterns: initial validation (2-5 evaluations), ongoing monitoring (10-20 per quarter), production-scale coverage (40+ annually). Pricing is usage-based, allowing teams to scale testing as needed.

Move from one-time testing to continuous AI security assurance.