AI and LLM Security Testing

We test AI-enabled systems, from chatbots to agentic workflows, for manipulation, data exposure and control bypass.

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// Overview

What this service is.

AI and large language model security testing simulates adversary activity against model interfaces, orchestration layers and integrated services. We focus on weaknesses that could result in unauthorized access, data exposure, control bypass or manipulation of model decision-making.

Engagements can cover standalone AI interfaces, LLM features embedded in applications, agent-based systems and retrieval-augmented generation pipelines. Findings inform control design, governance decisions and risk prioritization.

// Scope

Scope and coverage.

  • Prompt manipulation and guardrail bypass
  • Abuse of trust between models, tools and data sources
  • Sensitive data exposure through model outputs and retrieval
  • Agent permissions and tool use
  • Orchestration layers, plugins and integrations
  • Surrounding application and API security
// Deliverables

What you get.

  • Validated findings with realistic attack scenarios
  • Prioritized recommendations for controls and guardrails
  • Reporting for security, engineering and governance teams
  • A leadership debrief
  • Retest guidance
// Questions

Frequently asked questions.

Do you test models we host and models we call through an API?

Both. We scope around the system you deploy, including the application, prompts, tools and data connected to the model.

Is this the same as a traditional pentest?

It overlaps, but AI systems add new risks such as prompt manipulation and agent abuse, so the approach is different.

Will testing affect production users?

We agree rules of engagement and can test in staging environments.

// Get started

Ready to scope this engagement?

Tell us what you want to learn and we will help you scope the right engagement.

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