Cerby Plans to Integrate GPT to Enable More Efficient Analysis and Mitigation of Security Threats in Nonfederated Applications

Cerby, the comprehensive access management platform for nonfederated applications (also called ‘unmanageable applications,’ which lack support for common identity standards like single sign-on), today announced the future integration of GPT Natural Language Processing (NLP) technology to its security platform. This integration will allow Cerby to improve its user and entity behavior analytics (UEBA) capabilities, providing security teams with enhanced visibility and automated threat detection for the increasingly large set of legacy and cloud-based applications that don’t work with identity providers.

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Integrating NLP technology will enable Cerby to analyze a broader range of unstructured data sources, such as email messages and identity provider logs, to accurately identify threats and malicious activities. The platform’s machine learning algorithms will analyze the context and sentiment of the data, making it easier to identify abnormal behaviors and potential risks.

Cerby designed its solution to close the security and compliance gap between enterprise applications that do not work with identity providers, such as Okta and Azure AD. Integrating NLP technology will enable Cerby to enhance the accuracy and speed of threat detection and, in the future, deploy mitigation measures to reduce the risk of data breaches and cyber-attacks.

“By integrating OpenAI’s GPT technology into our platform in the near future, we will further strengthen our security capabilities to provide our customers with more advanced threat detection and proactive response capabilities,” said Bel Lepe, CEO and co-founder of Cerby. “This future integration will ensure our customers can proactively identify and address security risks while streamlining security operations.”

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The integration of GPT technology is the latest in a series of enhancements to Cerby’s access management platform, which helps businesses reduce risks, like password reuse and disabled 2FA, while bridging the access management gap between identity providers and nonfederated applications.

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