We conduct security testing of AI-driven systems by analysing how they behave and respond to different inputs, prompts, and outputs. This testing is designed to evaluate the robustness of Generative AI and Large Language Models (LLMs) to find weaknesses which enable attackers alter the model’s outputs, extract sensitive information, or trigger unintended behaviours.
Our bespoke approach will help your organisation to:
Our experienced consultants follow established methodologies to examine the model’s security controls. The outcome of our testing aligns the system with security best practices, providing a detailed list of identified vulnerabilities along with recommended remedial actions.
Our testing approach largely aligns with the OWASP TOP 10 LLM guidelines to ensure a methodological review of the in-scope systems. As an example, our consultants may look to attempt prompt injections which are intended to cause the model to ignore pre-written instructions and leak sensitive data / perform unauthorised actions. Furthermore, inadequate sandboxing vulnerabilities may be exploited to gain unauthorised access to critical systems or data – while insecure output handling misconfigurations could be leveraged to exploit vulnerabilities introduced in downstream systems.
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