AI治理须从“被动防御”转向“主动出击”

Group 1 - The core viewpoint of the articles highlights the rapid integration of AI, particularly large language models (LLMs), into business operations, which brings both transformative potential and significant security risks [1] - AI browsers, such as OpenAI's ChatGPT Atlas and Perplexity's Comet, are set to revolutionize user interactions by automating tasks like form filling and booking, but they also introduce new vulnerabilities that could lead to data breaches and unauthorized actions [2] - Security experts emphasize the need for proactive measures in AI governance, including unique identification for AI agents, data classification, and emergency shutdown mechanisms to mitigate risks associated with AI's increasing autonomy [3] Group 2 - Prompt injection attacks, which manipulate LLMs to bypass security protocols and leak sensitive information, have been identified as a top threat by organizations like OWASP, highlighting the need for robust defenses against such vulnerabilities [4] - The evolution of security access service edge (SASE) into AI-aware access architecture is crucial for managing AI traffic and ensuring compliance, marking a shift from passive to active defense strategies in AI security [5][6] - The establishment of AI security posture management (AI-SPM) systems is anticipated to provide centralized monitoring and governance of AI models and data, ensuring compliance with international risk management frameworks and enhancing overall security [6]