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AI Is Already in Your Org—Are You Securing It All?
- Generative AI tools like ChatGPT are increasingly prevalent in organizations, bringing both productivity gains and security risks.
- Different types of AI in an enterprise, including unmanaged third-party AI, managed second-party AI, and homegrown first-party AI, each present unique security challenges.
- Common patterns of AI misuse include unaware misuse, unauthorized access, oversharing, unintentional public exposure, and misconfigured safeguards.
- Organizations are tempted by open-source AI models for cost-effectiveness and flexibility, but must implement rigorous safeguards to prevent security vulnerabilities.
- Open-source AI encompasses various dimensions such as open weights, open source, open data, and open training, each posing different security implications.
- To secure AI surfaces effectively, organizations must consider securing not only human interactions but also interactions with agentic AI agents that operate independently.
- It is crucial for enterprises to authenticate, monitor, and control AI agents to prevent misuse and ensure compliance with defined scopes and privileges.
- AI security requires comprehensive visibility into user behavior, data flows, and policy enforcement to defend against evolving threats and attacks.
- Securing AI necessitates understanding the entire AI inventory, implementing risk-based policies, appropriate access controls, and detection mechanisms for misuse.
- Adopting a proactive approach to AI security is essential to address the expanding data surface and protect against emerging security challenges.
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