Shadow AI

Hello all, 

Welcome to another edition of Strac’s weekly newsletter update. Today’s article looks at Shadow AI, an often overlooked phenomenon that poses significant risks in data security and compliance. An important and insightful read!

Additionally, if you need help discovering & classifying sensitive data on SaaS, Cloud, and Generative AI, and the ability to remediate (redact, mask, block, alert) PII, PHI, PCI, Sensitive Data or comply with PCI, HIPAA, SOC 2, GDPR, CCPA, please feel free to book a call with me.

Warmly,

Aatish

Strac’s Latest Views on Shadow AI

 🚀 Learn about Shadow AI: what is Shadow AI and how can companies find unsanctioned LLM models?

- Overview: Shadow AI refers to the unauthorized use of AI tools and models within an organization, often bypassing formal IT and security oversight. This trend has emerged with the easy availability of AI tools and cloud services, allowing departments to adopt AI without technical support.

- Risks: Shadow AI poses serious risks, including data security threats and compliance violations. Examples include marketing teams using unvetted models, research departments sharing proprietary data with third-party tools, and developers testing APIs without security approval.

Detection Strategies for Security Teams:

• Inventory AI Resources: Regularly document and review AI resources across cloud platforms, especially within AWS services like SageMaker, Rekognition, and Bedrock.

• Analyze Data Access Logs: Monitor AWS CloudTrail and CloudWatch for signs of unauthorized data access or high-frequency interactions with sensitive data by AI models.

• Monitor Outbound API Calls: Track outbound network traffic using AWS VPC Flow Logs to detect unauthorized use of external AI APIs.

• Conduct AI Model Audits: Establish routine audits with relevant teams to review deployed AI resources and identify any unapproved models.

Conclusion:

Shadow AI poses serious risks to data security and compliance. By implementing thorough monitoring, regular audits, and clear policies, organizations can effectively manage these risks. With proactive governance and AWS security tools, companies can ensure AI usage remains safe, compliant, and aligned with organizational goals.

To learn more about Shadow AI, click here.