AI Application Security Testing
OWASP Top 10 LLM – we test your application against AI-specific risks
AI brings its own threat model
AI applications introduce a new category of security risks that traditional security testing doesn’t cover. Prompt injection can bypass an application’s business rules. Jailbreaking can expose sensitive information. Excessive system permissions can lead to unintended actions in your systems.
The OWASP Top 10 LLM is the industry’s recognized framework for assessing these risks. We test your application against it in practice, not just in theory.
Who is this for?
- You’ve built a chatbot, RAG system, or other LLM-based application
- You’re integrating an LLM into a business process or product
- A customer or partner is asking about the security of your AI product
- You want to confirm the application withstands attack attempts before going to production
What gets tested?
Testing covers all OWASP Top 10 LLM categories.
Active technical testing
Prompt Injection
Direct injection attempts via the user interface, indirect injections via ingested data (RAG, files, emails)
Sensitive Information Disclosure
Attempts to get the model to reveal the system prompt’s contents, internal data, or other users’ data
Improper Output Handling
Testing whether the application executes LLM-generated code or commands without validation
Excessive Agency
Testing whether the model can perform actions with broader permissions than the use case requires
System Prompt Leakage
Testing system prompt disclosure using various probing tactics
Vector Database
For RAG systems: poisoning attacks and manipulation of retrieval results
Unbounded Consumption
Testing application behavior under unusually large or repeated requests
Architecture and configuration review
Supply Chain
Models, libraries, and plugins in use, risks and dependencies
Data Poisoning
Management and protection of training data and the RAG database
Misinformation
Hallucination risks relative to the application’s intended use
How does testing proceed?
Phase 1 – Kickoff
Review of the application’s architecture and data flow, mapping of use cases and user roles, agreeing on the testing scope and environment (development or staging)
1–2 h
Phase 2 – Technical testing
Prompt injection and jailbreak tests, data leakage and system prompt tests, permission-scope testing, RAG system testing (if applicable)
3–8 days depending on scope
Phase 3 – Reporting
Findings by OWASP Top 10 LLM category, severity classification (critical / high / low / informational), concrete remediation recommendations for the development team
5 business days after testing
Phase 4 – Results review
Review and approval of the report with the client. The client can optionally order a retest of the findings once remediation is complete, confirming that the vulnerabilities identified during testing have been successfully fixed
What do you get?
Executive summary
Summary of the security posture and findings
Findings by OWASP Top 10 LLM category
What was found, how severe, and what it means in practice
Technical report for the development team
A detailed technical description of the findings in priority order, concrete remediation guidance, and examples of how each finding can be reproduced, with screenshots
Verification of findings
We confirm that remediation has eliminated the vulnerabilities identified during testing. Retesting can be ordered as a separate engagement, during or after the project
Price and terms
- Total price
- Starting from €5,000 (excl. VAT)
- Billing
- Monthly based on the work carried out
- Testing environment
- Staging or development environment
- Report
- 5 business days after technical testing
Frequently asked questions
What access is needed?
Access to a staging or dev environment is enough. We need the application’s UI or API, and if applicable, access to the RAG database and system prompt.
Is this the same as penetration testing?
No. This is LLM-specific testing. The focus is on AI application-specific risks, not general web application security testing. Traditional pentesting and LLM testing complement each other.
What if serious vulnerabilities are found?
Critical findings are reported to the client immediately upon discovery, without waiting for the final report. We can help with remediation under a separate agreement.
Does this work for all LLM platforms?
Yes. Testing is based on the OWASP LLM guidelines, so it is independent of the model or platform used. Testing works with OpenAI, Anthropic, Google, and open models alike.
Next step
Get in touch and briefly describe which application or integration you’d like tested. We’ll schedule a kickoff call to review the scope, confirm the timeline, and prepare an offer for you.
hello@braveson.fiTesting coverage is defined according to the OWASP Top 10 for LLM Applications 2025 list.