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The rise of generative AI copilots is leading to an increase in data breaches, as competitors can access sensitive information without detection. A notable case involved a former employee who exploited a gen AI copilot to extract customer data and share it with a rival. This scenario underscores the urgent need for organizations to address data security challenges associated with generative AI tools.
Organizations face significant risks due to overly permissive data access and the difficulty of managing sensitive information. With nearly 99% of permissions unused, the potential for data breaches escalates as generative AI can easily surface sensitive data. Implementing a robust data security strategy, including right-sizing permissions and monitoring user activity, is essential to mitigate these risks.
• Generative AI copilots increase the risk of data breaches significantly.
• Right-sizing data access is critical to prevent unauthorized information exposure.
Generative AI tools can create sensitive data rapidly, increasing the risk of data breaches.
The article discusses how generative AI can facilitate data breaches by allowing easy access to sensitive information.
Applying labels to sensitive data is a key aspect of enforcing DLP.
Varonis provides solutions to help organizations protect sensitive data, especially in the context of generative AI.
The company is highlighted for its role in the growing use of generative AI tools.
Salesforce's tools are mentioned as common use cases for generative AI.
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