AI Security Testing

Test your AI before attackers do.

If you're building or deploying AI-powered applications, you need to understand how they can be attacked. Large language models introduce security risks that traditional testing doesn't cover - and those risks multiply as AI systems gain access to tools, data, and decision-making authority.

We test your AI systems the way real attackers would, across every interaction pattern your users and integrations rely on.

What we test

Chat & Assistants - Conversational AI including customer service bots, internal assistants, and any system where users interact through natural language.

Code Assistants - AI development tools like GitHub Copilot, Amazon CodeWhisperer, and Cursor that see your codebase and can leak context or suggest insecure patterns.

RAG Systems - Retrieval-Augmented Generation pipelines connecting LLMs to your documents and databases. We test for document injection and retrieval manipulation.

CLI Agents - Terminal-based AI assistants with access to files, commands, and system resources. A compromised CLI agent can read, write, and execute.

MCP Servers - Model Context Protocol integrations that extend AI capabilities through external tools. We test for tool abuse, privilege escalation, and supply chain risks.

Multi-Agent Systems - Architectures where multiple AI agents collaborate, delegate, and share context. We test for inter-agent manipulation, privilege escalation through delegation chains, and emergent offensive behaviour.

Attack coverage

Our methodology covers the complete OWASP Top 10 for LLM Applications (2025) and the OWASP Top 10 for Agentic AI (2026), including:

Prompt Injection - Direct and indirect attacks that override system instructions or inject malicious context through external data sources.

Data Disclosure - Extraction of system prompts, training data, conversation history, and sensitive information the model can access.

Safety Bypass - Techniques that circumvent content policies, safety guardrails, and output restrictions.

Tool & Resource Abuse - Manipulation of tool calls, parameter injection, and privilege escalation through AI-controlled integrations.

Supply Chain Risks - Vulnerable dependencies, typosquatting attacks on model packages, and risks in third-party integrations.

Agentic Risks - Excessive agency, uncontrolled autonomy, and failures in human oversight. Covering the OWASP Agentic AI Top 10 (2026) including identity spoofing, tool misuse, privilege escalation, and cascading hallucinations across agent chains.

Compliance mapping

For organisations in regulated industries, we map findings to the compliance frameworks that matter to your auditors:

GDPR - Personal data exposure and processing risks
HIPAA - Protected health information disclosure
PCI-DSS - Payment card data handling
SOC 2 - Credential and API key exposure
CCPA - California consumer data requirements

Each finding includes severity rating, affected compliance requirements, and specific remediation guidance.

What you receive

Executive Summary - A one-page overview with overall security grade, key findings, and priority actions for leadership.

Technical Report - Complete findings with reproduction steps, evidence, impact analysis, and remediation guidance.

Compliance Analysis - Mapping of findings to relevant regulatory requirements, ready for your compliance team or auditors.

Our approach

We combine systematic methodology with manual testing to explore how your AI behaves under adversarial conditions. Automated scanning catches common issues; expert testing finds the context-dependent vulnerabilities that automated tools miss.

Each engagement is tailored to your specific implementation - whether you're using off-the-shelf models, fine-tuned systems, custom deployments, or complex multi-model architectures.

How it fits together

AI Security Testing is a specialist service that complements our broader Security Assessment Suite. If you're deploying AI within a larger application, we can assess both the AI components and the surrounding infrastructure together.

For organisations building on the Model Context Protocol, we offer dedicated MCP security assessments covering tool definitions, transport security, and integration risks.