Description
With the significant power of Large Language Models (LLMs) also comes an increased level of risk. More and more applications are integrating LLMs to provide additional functionality. However, this creates new attack surfaces and entirely new vulnerability types, which are for example classified in the OWASP Top 10 for LLM Applications.
One of the most well-known attack patterns the is the so-called prompt injection. Through carefully crafted inputs, attackers can manipulate the model’s behavior and bypass security mechanisms.
In addition, there is a risk that LLM-based systems may disclose sensitive information, such as internal data, trade secrets, or cross-tenant content.
Effectively securing such systems requires specific measures that go beyond traditional application security. These include robust guardrails, clear separation of contexts and permissions, and continuous validation of model behavior.
To support you in this matter, we test your LLM application for specific LLM vulnerabilities and help you identify risks early and reduce your attack surface.
Did we catch your interest? We would love to discuss your goals, requirements and test scope in a non-binding scope meeting.
Next steps
- ✓ Understand goals, set test scope
- ✓ Schedule test period
- ✓ Kickoff, test, report meeting
