How LlamaParse Pen Tested Against OWASP LLM Risks

According to LlamaIndex Blog:

Background and Testing Approach

Traditional security tests are great for standard web apps, but they fall short when dealing with AI models that read customer documents. To ensure rigorous security, LlamaParse hired a dynamic application security testing firm using AI agents. These agents spent four days autonomously reading documentation, writing code, generating sample files, and attacking the production environment across all ten OWASP LLM risk categories.

Key Findings and Lessons

Among the findings was a subtle attack where invisible white-on-white text inside a PDF invoice altered extracted bank account details. This raised a crucial question about responsibility: should the parsing tool filter out such anomalies, or should the customer's downstream pipeline handle trust decisions? LlamaParse concluded that extraction should faithfully report what is on the page, while customers must implement business validation rules.

Enterprise Security Controls

Beyond the pen test, LlamaParse outlines robust enterprise controls, including strict data privacy policies that prevent customer data from being used for model training, SOC 2 compliance, and flexible deployment options ranging from managed SaaS to self-hosted environments.