Attack

Break the AI system, then turn the evidence into fixes.

Every finding is written so it can become a control, retest, and buyer-ready evidence item. Attack services test the system adversarially across direct prompt injection, indirect prompt injection / XPIA, RAG poisoning, tool abuse, agent permission escalation, cross-tenant leakage, context leakage, guardrail bypass, and insecure output handling.

Request Adversarial Testing View 8-Service Portfolio

Abuse path to evidence

Attack visual operating model

Buyer questions

- Can direct prompt injection or hostile documents change behavior?
- Can indirect prompt injection / XPIA alter behavior through documents, retrieval, or tool context?
- Can retrieval leak private or tenant-scoped data via RAG poisoning or context leakage?
- Can agents abuse tools or bypass approvals through permission escalation?
- Can we show reproducible adversarial evidence to buyers or leadership?

Products / instruments

SecEng Adversarial Range SecEng RAG Test Harness — XPIA Lab SecEng Authority Graph — Agent Blast-Radius Map SecEng Artifact Analyzer SecEng Runtime Proxy — Trace, Replay, Evidence Export

Featured research

AI Product Security in the Age of Mythos Agentic Anarchy

Featured research

AI Product Security in the Age of Mythos

A post-Mythos product-security operating model for leaders who need to inventory AI systems, threat-model agentic products, gate releases, monitor evidence, and close the boardroom-to-backlog gap at machine speed.

17 Chapters90 days Execution planAI-era Threat models

Open report

Attack instrument

SecEng Adversarial Range

RAG abuse testing

SecEng RAG Test Harness

Evidence proof

Agentic Browser Security Assessment

Browser, native bridge, command-dispatch, and delegated-action review evidence.

View proof

Flagship

AttackAvailable

assessment

Agentic Workflow Abuse Review

An adversarial review of AI agents, tools, automations, permissions, approvals, workflows, rollback paths, and action boundaries. It tests the action layer: what the AI can do, who approved it, what it can touch, and how badly it can fail.

Outcome

5 deliverables

Best for

AI Platform Lead, Product Security, Automation Owner, Red Team

•Agent tool inventory, permission boundaries, and action authority review
•Approval bypass, tool abuse, workflow escalation, and blast-radius scenarios
•Rollback, human approval, audit trail, and reconstruction checks
•Abuse scenario register and engineering-ready remediation priorities

Duration: 2-5 weeksScoped in discovery call

View service Review Agent Abuse Paths See people fit View evidence

Flagship

AttackAvailable

assessment

AI Red Team & Adversarial Testing

A focused adversarial engagement testing prompt injection, indirect instruction attacks, RAG exposure, tool abuse, tenant leakage, policy bypasses, unsafe autonomy, and model misuse paths.

Outcome

5 deliverables

Best for

CISO, Product Security, Red Team, AI Engineering Lead

•Prompt injection, indirect instruction, jailbreak, and policy-bypass testing
•RAG authorization, context exposure, poisoning, and cross-tenant leakage modules
•Tool abuse, unsafe autonomy, model behavior abuse, and misuse scenarios
•Executive summary, findings register, remediation roadmap, and retest plan

Duration: 3-6 weeksScoped in discovery call

View service Request Adversarial Testing See people fit

Sample deliverables

AI Red-Team Scope Document

AI Red-Team Findings Register

AI Red Team Assessment Executive Summary

AI Red-Team Remediation Roadmap

RAG & XPIA Security Test Plan

Agent Abuse Scenario Register