LLM model pentesting to reduce the risk of using AI in your environment
The Challenge
52% of data security leaders are concerned about the possibility of AI attacks via threat actors, and 57% report an increase in AI-driven attacks in the last year, based on Immuta’s AI Security & Governance Report.
According to McKinsey’s latest Global Survey on AI, 65% of respondents regularly use AI, almost double the number of respondents from the previous year. However, although companies are eager to use AI, not every company understands the associated risks. Whether you are fine tuning off-the-shelf models, using large language learning model functionality in your applications, or in other processes, security should not be an afterthought.
The ability to identify vulnerabilities specific to LLM capabilities is critical, especially when incorporating AI into application development. Security and privacy are significant concerns. Lack of proper evaluation may allow users to manipulate LLMs, such as chatbots and expose sensitive data, generate unauthorized content, or take actions on their behalf.
The Solution
NetSPI AI/ML Penetration Testing solves these challenges using a powerful combination of people, processes, and technology, and helps reduce the risk of using AI in your environment.
NetSPI offers a depth and breadth of testing, whether you need to securely incorporate LLM capabilities into your web-facing applications, gain detailed benchmarking and analysis of potential jailbreak consequences of your LLM, or customize an advanced model evaluation and review.
Our rigorous and consistent testing methodology ensures we find vulnerabilities, exposures, and misconfigurations that others miss.
NetSPI delivers tailored solutions to:
- Pentest LLM web applications
- Benchmark and jailbreak testing for LLMs
- Customize testing for LLM deep model evaluation
Access our AI/ML Penetration Testing solution brief to learn more.