Netskope extends risk management to OpenAI’s ChatGPT Enterprise

Netskope announced an integration with OpenAI‘s ChatGPT Enterprise Compliance API to deliver API-enabled controls that bolster security and compliance for enterprise organizations using generative AI (genAI) applications.

Through this integration with the ChatGPT Enterprise, the Netskope One platform provides organizations with enhanced security features including application visibility, robust policy enforcement, advanced data security, and comprehensive security posture management.

Netskope recently reported that GenAI application usage among users more than tripled since this time last year, urging organizations to reevaluate their data protection strategies amid the proliferation of AI adoption. While the average activity per genAI user has also doubled, maintaining compliance standards, mitigating data policy violations, and helping support secure usage of genAI applications, such as ChatGPT Enterprise, is increasingly more critical.

Netskope CASB API protection leverages APIs available from major vendors, such as Box, Google Workspace, and Microsoft 365, to provide visibility into settings and data residing in the cloud service, enforcing powerful policies to control access and protect the data within. Netskope’s integration is designed to help enterprise data within ChatGPT Enterprise remain compliant, secure, and protected.

“By integrating the Netskope One platform into OpenAI’s advanced capabilities in ChatGPT Enterprise, Netskope continues to lead in providing comprehensive security solutions for enterprises adopting genAI tools,” said Andy Horwitz, SVP, Global Partner Ecosystem, Netskope. “This integration reinforces our commitment to empowering organizations with the tools they need to help manage sensitive data and support compliance as AI adoption continues to accelerate.”

Netskope’s integration with ChatGPT Enterprise now allows joint customers to more effectively:

• Adhere to compliance standards: With over 50 compliance templates and 3,000+ data identifiers, organizations can now help enforce data loss prevention (DLP) and compliance policies around sensitive data to support meeting compliance regulations like GDPR, HIPAA, GLBA, and more.
• Advance detection and safeguard sensitive data: With out-of-band visibility and control, help protect sensitive information such as personal identifiable information (PII) and intellectual property (IP). In addition, continuous data scanning identifies and takes action on sensitive data leakage in near real-time, and users can leverage sophisticated and accurate DLP techniques, including Machine Learning (ML) and Optical Character Recognition (OCR), to find sensitive information that is typically difficult to identify.
• Protect against threats: Advanced ML models for malware detection complement more traditional signatures, heuristics methods and sandboxing techniques, further remediating risks by identifying potential threats in near real-time.