The Shift in Cloud Assessments for the AI Era
As AI evolves, traditional cloud security methods fall short. Common practices like scanning for open S3 buckets neglect critical AI logic gaps, especially in peer-to-peer (P2P) connections established through the Model Context Protocol (MCP). The challenge lies in assessing whether AI systems leak sensitive data, not merely checking configurations.
With over 98% of businesses using cloud infrastructure by 2024, clarity around data ownership becomes paramount. For instance, a retail AI chatbot could inadvertently expose backend API keys. To safeguard assets, conduct a comprehensive inventory of MCP servers and their API interactions, ensuring that sensitive data paths are well-mapped.
Moreover, as quantum computing looms, organizations must adopt post-quantum encryption to protect their P2P links from future breaches. Transitioning to context-aware access management is essential, moving beyond static user roles to dynamic, intent-based protocols. Addressing AI-specific threats through anomaly detection and automating compliance reporting will enhance overall security.
Stay proactive to fortify your cloud security.
