In the era of big data and information overload, efficiently retrieving and generating relevant knowledge has become increasingly crucial across various domains. While traditional language models have made significant strides in natural language processing tasks, they often need help with factual accuracy, context awareness, and integrating external knowledge sources.

In the realm of modern enterprise productivity suites, Copilot for Microsoft 365 stands as a huge driver for efficiency, offering business users the ability to aggregate, summarize, and process data within the M365 suite of tools. However, for organizations with diverse infrastructure and applications, and the need for real-time data interactions, the out-of-the-box functionality requires augmentation to reach its full potential, not to mention secure controls for Copilot for M365.

SaaS applications have fundamentally transformed business operations by enabling on-demand user access to services and data via the internet from anywhere. Yet, despite countless benefits, SaaS in the enterprise is fraught with cybersecurity challenges.

Today we’re excited to announce new and enhanced enterprise-grade platform capabilities that build upon our existing enterprise capabilities and customization functionality. Along with our new AI-powered Trust Center announced today, these capabilities enable mature organizations to run their security and compliance programs and demonstrate trust at scale.

In the vast and interconnected world of information technology, the security of network services and protocols is paramount for organizations of all sizes. Among these, Samba—a free software re-implementation of the SMB/CIFS networking protocol—plays a crucial role in facilitating file and print services across various operating systems, including Unix, Linux, IBM System 390, and Windows.

As the number and severity of third-party breaches continues to rise, companies are scrutinizing more closely not just how they handle data, but how their vendors do as well. For security leaders, this means more security reviews are coming across their desk everyday. ‍ Limited resources and legacy processes make it hard for security teams to keep up with the pace of business.

The rapid advancements in large language models (LLMs) have revolutionized how we interact with technology, powering various applications for different use cases. As the adoption of LLM-powered solutions continues to grow, so does the emergence of new and evolving security threats that aim to exploit these robust AI systems.

Building, pre-training, and fine-tuning an AI model is no small task and you’ll naturally want to protect your efforts from theft, denial of service attacks, malicious use, and other threats. In this blog we’ll go over the basics of keeping AI models safe from both legal issues and bad actors.

Since our beginning, CyCognito has integrated AI techniques to power robust and accurate attack surface discovery and testing. And we’re also adding new capabilities all the time. In this post, we’ll share with you some of the tasks that CyCognito’s AI helps power or simplify, along with a primer of the various techniques we leverage.