Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

MCP, short for Message Communication Protocol, refers to a category of protocols used for exchanging structured messages between systems or applications. It was developed primarily to meet the communication needs of early enterprise systems that required: MCP protocols are often seen in banking, insurance, healthcare, and telecom industries—sectors where many systems were developed before APIs became mainstream.

Riscosity has made it even easier to prioritize issues where data types are being shared by your Applications with 3rd party vendors by adding Confidence Scores to those data types. Users can focus in on the issues with data types that Riscosity had the highest confidence in determining without worrying about false positives.

Riscosity’s web application navigation menus have been redesigned to make common user workflows easier than ever. Users will benefit from the more intuitive layout that will allow them to get to where they need to go seamlessly.

Shadow technology, regardless of name, is a manifestation of the same issue - unmonitored, unauthorized, or hidden technology operating outside official oversight. Over the past ten years, with the adoption of SaaS services, Shadow IT became a significant concern for security teams. With the more recent explosion of AI tools, we’ve started to hear the term Shadow AI being used for the same reasons.

Please see part Part I for our introduction to leveraging AI in the enterprise and Part II for why the legacy landscape falls short in the age of GenAI.

A Privacy Impact Assessment (PIA) is a process that helps identify and manage any privacy risks that may arise from taking on new projects or systems that involve personally identifiable information (PII). PIAs are recommended by the EU’s General Data Protection Regulation (GDPR) and required for government agencies to perform under the U.S. E-Government Act.

For our introduction to the challenge, please see Part I.

This article explores why AI is complicating compliance and the critical steps enterprises must take to avoid regulatory pitfalls.