Get Started With AI Red-Teaming

The double-edged AI revolution has brought tangible benefits for IT but also opportunities for threat actors to deploy more sophisticated and varied cyberattacks. Our research offers a structured starting point for IT and security leaders looking to employ AI red-teaming exercises to identify and mitigate vulnerabilities in their AI models, securing their organization’s future growth and innovation.

AI red-teaming can be an effective stress test, but it is relatively new – to maximize its potential for mitigating risk, organizations must approach it differently than traditional red-teaming exercises. IT and security leaders must be clear about their AI red-teaming goals and involve the right people, processes, and technology to ensure their effectiveness.

1. Define your goals early.

Hunting for security risks doesn't need to be a fishing expedition. Setting out a specific scope for your red-teaming exercise and aligning it with your organization’s security frameworks will ensure your efforts are effective at uncovering AI-based vulnerabilities.

2. Harness the power of collaboration.

Adversarial testing of your AI systems is more complex than in traditional red-teaming exercises and, as such, requires a larger and more diverse group. A multidisciplinary approach, involving experts in AI, compliance, cybersecurity, data, and ethics, will ensure you get the most out of your red-teaming exercises.

3. AI red-teaming shouldn’t be your only tool.

AI red-teaming can be a tremendously valuable risk detection and mitigation tool, but it is only one aspect of nurturing a safe and secure AI environment. Organizations must develop strong governance practices and enhanced security measures to effectively secure their AI technologies in the long term.

Use this research as a starting point for your AI red-teaming strategy

Our research offers guidance on understanding the benefits of AI red-teaming and taking a methodical approach to planning a red-teaming framework. Ensure you have the right goals, tools, and team to ensure an optimal approach that detects risks to your AI technology, shields it from threats, and allows it to operate securely in your organization.

• Define the scope of your AI red-teaming exercise, including the systems being tested and the type of testing conducted.
• Develop your framework by identifying the people and processes to involve, while ensuring alignment with best practices.
• Assemble what you need by selecting the tools, technologies, and vendors that will be most valuable in developing an effective AI red-teaming exercise.
• Establish metrics and KPIs to assess the effectiveness of your AI red-teaming practice.