Cybersecurity
AI & LLM Security Testing
Adversarial testing of chatbots, AI assistants and agents for prompt injection, data leakage and unsafe actions.
Scope
What we test
Chatbots, AI assistants and agents can be manipulated through the text they read. A hidden instruction in an e-mail, web page or document can make them leak data or take actions nobody approved. We test your AI features the way attackers do and show you how to contain them.
Prompt injection
Direct and indirect instructions hidden in user input, documents and web content.
Data leakage
System prompts, customer data and secrets the model should never reveal.
Agents and tools
Function calls, MCP servers and plug-ins that act on behalf of users.
RAG and knowledge bases
Poisoned documents and access control in retrieval.
Guardrails and jailbreaks
How well your filters hold up against known bypass techniques.
Abuse and cost
Rate limits and unbounded consumption that drive up your bill.
Mapped to the OWASP Top 10 for LLM Applications
Every finding is linked to the 2025 OWASP list, the OWASP Top 10 for Agentic Applications and MITRE ATLAS, so your developers know exactly what to fix.
LLM01
Prompt injection
LLM02
Sensitive information disclosure
LLM03
Supply chain
LLM04
Data and model poisoning
LLM05
Improper output handling
LLM06
Excessive agency
LLM07
System prompt leakage
LLM08
Vector and embedding weaknesses
LLM09
Misinformation
LLM10
Unbounded consumption
What you receive
- 01 Findings mapped to OWASP and MITRE ATLAS
- 02 Reproducible test cases for your team
- 03 Guardrail and architecture recommendations
- 04 Regression test set for future releases
- 05 Summary for EU AI Act documentation
Questions we often hear
We use a model from a large provider. Is that not already secure?
The provider secures the model. How your application uses it, what data it can read and which tools it can call is your responsibility, and that is where most issues are found.
Do you test AI agents that take actions?
Yes. Agents with tools, MCP servers or API access are tested for goal hijacking, tool misuse and privilege abuse, with safe limits agreed in advance.
Does this help with the EU AI Act?
The AI Act requires accuracy, robustness and cybersecurity for high-risk systems. Our report gives you documented evidence of adversarial testing.
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