In this blog I cover AI Security Posture Management, what’s it about and when to consider using it. AI Security Posture Management is a tool that gives you visibility into the security and posture of your GenAI services. AI-SPM is a fairly new acronym introduced around a year ago to the public, and vendors like Microsoft, WIZ, and Palo Alto, who already have an existing Cloud Security Posture Management (CSPM) platform in their portfolio, are extending their CSPM capabilities to GenAI services. With AI-SPM, you get an inventory of your AI stack, identify vulnerabilities, map attack paths, and help to mitigate and react to these risks.

Difference between AI-SPM and CSPM and how they work together

AI Security Posture Management (AI-SPM) and Cloud Security Posture Management (CSPM) both focus on maintaining a security posture, but they look at security from different angles.

CSPM has more focus on the posture of cloud infrastructure and looks more into mitigating misconfigurations of the infrastructure and ensuring compliance.

AI-SPM is tailored for AI and machine learning systems. It addresses the posture of AI models, data, and infrastructure. With AI-SPM, you get a deeper dive into vulnerabilities, misconfigurations, and ensuring compliance with regulations and standards.

Both CSPM and AI-SPM share similar elements even though they look into different areas. Currently, you see CSPM tools having AI-SPM as an add-on, which makes monitoring easier for your cloud infrastructure and AI tools and services from a single pane of glass view.

Risk scenarios and use cases for AI-SPM

With AI-SPM you can effectively monitor and control access to AI models and data, ensuring that API keys are not stored in public repositories to prevent unauthorized access. Additionally, you can maintain the integrity and reliability of AI models by detecting and preventing tampering through version monitoring, ensuring that only authorized changes are made.

Assessing the security of plugins and extensions used in AI systems is also possible, identifying and addressing any insecure components. Furthermore, you can ensure that outputs are handled securely by sanitizing them to prevent injection attacks. Lastly, you can identify and mitigate poisoned training data by validating data sources and monitoring for anomalies.

When to consider AI-SPM?

I would recommend a solution like AI-SPM if you are not sure what AI services your company is using or that there is a risk of having Shadow AI use in your organization. You should consider implementing the tool if you have, for example, a lot of AI pilots ongoing, or you are not sure of the security and posture of the AI services that you are creating either in-house or with your partners. You may also want to have it in place when you create new AI services so there is a process for monitoring and securing AI services and workloads. Even though AI-SPM might not take all your concerns away, it gives you the tool to monitor the health of the AI services from a security perspective. However, you should still consider processes and a security-first approach when bringing or creating AI services within your organization.

Microsoft has AI-SPM currently in preview, and it is an add-on to Defender for Cloud, expected to release by the end of 2024.

Need support?

If you’re facing challenges with AI Security or AI-SPM, reach out – we specialize in these areas and are here to help.