Netskope Highlights AI Security Challenges Amidst Growing East-West Traffic Risks

• •AI security requires visibility into both north-south and east-west traffic.
• •Context poisoning poses significant risks to AI communications and data integrity.
• •Robust DLP tools are essential for preventing sensitive data leaks in AI environments.

Tony Burnside, SVP for APJ at Netskope, emphasizes the critical need for visibility in AI security as organizations increasingly integrate AI tools with minimal oversight. The focus has primarily been on north-south traffic, but the rise of east-west traffic, particularly involving the Model Context Protocol (MCP), presents new security challenges. Burnside draws parallels between today's AI tool adoption and the shadow IT risks of the past, noting that users often deploy these tools without understanding the implications. He warns of context poisoning, where malicious data can compromise AI communications, potentially leading to unauthorized access to sensitive information. The need for robust data loss prevention (DLP) tools that can monitor both north-south and east-west traffic is highlighted as essential to mitigate these risks. Current security controls must evolve to be omni-directional to effectively protect sensitive data from being leaked outside corporate environments. Organizations are urged to act quickly to address these emerging threats.