AI and LLM testing

Secure AI agents before attackers turn
conversations into actions.

Adversarial testing for AI assistants, copilots, prompt flows, tool use, and agentic workflows. We test what happens when a model is given real permissions and a hostile user.

prompt injectionagentic workflowsdata leakageguardrail bypasstool abuse

An AI feature that can call tools, read data and act on a user's behalf is a new privilege boundary, and attackers already know it. We cover prompt injection, authorization bypass, tool abuse, data exposure, workflow manipulation, and the business logic inside AI enabled products. Every finding is exploited, ranked by impact, and written so an engineer can act on it the same day.

What we actually test

A benchmark score tells you the model refuses obvious harm. It cannot tell you that a document dropped into context can hijack the agent, that a tool call runs with more access than the user, or that a copilot will happily read another customer's data. That is the work.

  • Prompt injection: direct and indirect, including content the model retrieves, ingests or is fed by other users
  • Authorization bypass: where the AI acts with more privilege than the user who prompted it
  • Tool and function abuse: unsafe tool calls, argument tampering, and chained actions with real side effects
  • Data exposure and leakage: system prompts, secrets, cross tenant context and training or retrieval data
  • Workflow manipulation and business logic: multi step agentic flows steered toward outcomes you never intended

What you get

  • Reduced AI launch risk, with the failure modes found before your feature ships
  • Validated privileged workflows, proven to stay inside the user's real permissions
  • Abuse paths found before attackers, mapped from injection to real world impact
  • Live findings the moment we confirm them, not a PDF weeks later
  • Remediation guidance your engineers can ship, not a generic reference link
  • Free retest and verified closure once the fix is deployed
  • An auditor ready report mapped to SOC 2, ISO 27001 and customer security reviews

How the engagement runs

You buy a pool of testing hours and spend them where the risk is, across this and your other surfaces. We scope the AI feature and its tools, exploit manually with adversarial prompts and real permissions, surface findings live, prioritize by impact, report for each audience, and retest until closure is proven. No blind box, no theatre.

Review my scope

Other surfaces we test