What AI systems do you test?

We test LLM-based apps, chatbots, AI assistants, ML-driven features, and AI integrations including retrieval-augmented generation (RAG), tool-calling, and multi-agent workflows.

Do you test prompt injection and jailbreaks?

Yes. We assess prompt injection, instruction override, jailbreak attempts, and guardrail bypass paths, including tool-call abuse when applicable. We follow the OWASP LLM Top 10 framework and extend it with context-specific attack chains relevant to your system.

Does your AI pentest satisfy EU AI Act Article 15 requirements?

Yes. High-risk AI systems under Annex III of the EU AI Act must comply with Article 15 cybersecurity requirements by 2 August 2026. Our AI penetration test produces findings mapped to Article 15 obligations, giving your compliance team auditable evidence of conformity.

Can you test for data leakage?

Yes. We test for unintended disclosure of sensitive data via model outputs, memory, retrieval sources, file and tool access, and other AI interfaces.

Can this be combined with a classic application pentest?

Absolutely. Many AI risks live in the surrounding application, APIs, authentication, and integrations. We can combine both assessments for a complete view and a single unified evidence package.

Back to Penetration Testing

AI Security Testing

What is AI Systems Penetration Testing?

AI systems penetration testing is a specialized security assessment for LLMs, chatbots, and AI-enabled applications that evaluates attack surfaces unique to AI vulnerabilities that traditional penetration testing frameworks do not cover (including model manipulation, training data extraction, and context window abuse). Required for high-risk AI systems under the EU AI Act (Regulation EU 2024/1689) from August 2026.

Focused and context-aware. Penetration testing for AI and machine learning systems such as LLMs, chatbots, and AI functionality within applications. We test prompt injection, data leakage, and the effectiveness of guardrails to uncover abuse and unintended behaviour early.

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What is the testing scope?

LLM prompt injection testing

Model manipulation and poisoning

AI output validation bypass

Data extraction through AI interfaces

Jailbreaking and guardrail bypass

AI-assisted attack surface analysis

How do we approach AI testing?

Prompt Analysis

We test whether AI systems can be manipulated through prompts, context manipulation, or hidden instructions. This helps identify how users or attackers might steer the model beyond its intended behaviour.

Guardrail Testing

We deliberately attempt to bypass existing safety rules and restrictions. This reveals where guardrails fall short and which risks arise from misuse or unintended behaviour.

Data Leakage

We assess whether sensitive information can be exposed through model responses, prompts, or connected systems. This includes testing for both direct leakage and indirect exposure via integrations.

What does EU AI Act Article 15 require?

High-risk AI systems under Annex III of the EU AI Act must meet cybersecurity requirements. The compliance deadline is 2 August 2026. A structured AI pentest is the most direct path to documented Article 15 compliance.

What is a high-risk AI system?

Annex III of the EU AI Act includes AI systems used in hiring decisions, credit scoring, biometric identification, critical infrastructure management, and education. If your AI system falls under Annex III, security testing under Article 15 is a legal requirement, not a best practice.

Article 15: what it requires

Article 15 requires high-risk AI systems to be designed and developed to withstand attempts to alter their outputs or behaviour through adversarial inputs. A structured AI penetration test produces documented evidence that your system meets this requirement.

Deadline: 2 August 2026

The compliance deadline for high-risk AI systems under Annex III is 2 August 2026. Organizations deploying high-risk AI in production should begin their assessment well before this date to allow time for remediation and retesting.

Audit evidence for conformity

An AI penetration test produces findings mapped to EU AI Act Article 15 requirements. This gives your compliance team and conformity assessment body concrete, auditable evidence that security obligations are met before the deadline.

How does an AI pentest differ from a classic pentest?

AI security testing and classic application penetration testing overlap in some areas and diverge in others. Understanding the difference helps you scope the right assessment for your situation.

What's the same

Both assess how an application responds to malicious input. Authentication flows, API security, authorization logic, injection attacks, and data exposure risks are tested in both disciplines. If your AI system is embedded in a web application, both test types apply.

What's unique to AI

Prompt injection, context window manipulation, training data extraction, jailbreaking, guardrail bypass, and tool-call abuse are attack vectors that only exist in AI systems. Standard web application testing tools and methodologies do not cover these attack surfaces.

Why you need both

An AI system embedded in a web application inherits the vulnerabilities of both layers. We recommend combining AI security testing with web application or API testing for complete coverage. A single assessment can address both, with a unified evidence package for auditors.

Frequently Asked Questions

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