AI Penetration Testing
Security assessment of LLM applications, AI agents and MCP servers, combining automated testing with AI-Egis and expert analysis. Findings are mapped to OWASP and MITRE ATLAS and can be reproduced exactly.
What we test
Any system in which a language model reads untrusted content or can act on other systems.
LLM applications and chatbots
Customer-facing assistants and internal copilots, including their system prompts, filters and output handling.
AI agents and tool use
Agents that call APIs, execute code or browse the web, and the permissions granted to them.
MCP servers and integrations
Model Context Protocol servers, tool descriptions and the trust boundaries between them.
RAG and memory
Retrieval pipelines, vector stores and long-term memory, including access control and data integrity.
Model and data supply chain
Third-party models, datasets, plugins and skill bundles used by the system.
Guardrails and runtime controls
Whether input and output filters, moderation and policy controls hold under adversarial conditions.
How the assessment works
Scope
Threat model of models, tools, data flows and agents, and agreed rules of engagement.
Automated testing
AI-Egis runs 998 tests across 21 domains, adapted to the type of target.
Expert analysis
Specialists review business logic, misuse scenarios and the impact of each finding.
Report and retest
SARIF and CVSS-AI scored findings, remediation guidance and deterministic replay to confirm fixes.
What you receive
- ReportExecutive summary and technical findings with severity and business impact
- EvidenceReproducible test records and SARIF 2.1.0 export for your security tooling
- MappingOWASP LLM and Agentic Top 10, MITRE ATLAS, EU AI Act articles
- RemediationPrioritized recommendations and verification of each fix
Frequently asked questions
What is AI penetration testing?
A security assessment of systems built on large language models, such as chatbots, AI agents and MCP integrations. It checks whether the system can be manipulated through the content it processes, whether it leaks data, and whether its tools can be misused.
How is it different from a traditional penetration test?
A traditional test focuses on networks, applications and infrastructure. In AI systems the attack surface also includes instructions, documents, tool outputs and web pages read by the model, so specific tests and frameworks such as the OWASP Top 10 for LLM Applications and MITRE ATLAS are required.
How long does an assessment take?
Automated test campaigns run in hours. A complete engagement, including scoping, expert analysis and reporting, is defined according to the size and number of systems in scope.
Which frameworks are findings mapped to?
OWASP Top 10 for LLM Applications (2025), OWASP Top 10 for Agentic Applications (2026), MITRE ATLAS and, where relevant, the EU AI Act, NIST AI RMF and ISO/IEC 42001.
Can testing be done without our data leaving our infrastructure?
Yes. AI-Egis is self-hosted and can be installed on-premises or in air-gapped environments, with inference performed by local models.
Scope an AI penetration test
Tell us which AI systems you want to assess and I-314 will propose a scope.