Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

In this blog post, we will share our current understanding of the User Personas involved with Ricosity today. Job titles and responsibilities may vary, but the following User Personas are a reflection of the average users we meet who hold these roles at their organizations.

A few months ago I received a call from my Grandma. She was concerned about having received a notification that she had been part of a data breach and wasn’t sure what to do about it. She had many seemingly basic, but good questions; What’s PII? I use the app on my iPad, is it safe to log into other applications like my bank? Is it safe to use my account? How do I know when it’s safe?

Traditionally, data security focused on protecting data at rest within the confines of your on-premise data center. The cloud era has blurred these lines. Data now flows through complex pipelines, often traversing multiple services and third-party vendors. This expanded data perimeter creates new vulnerabilities: It’s crucial to ensure that the data loaded into warehouses and analytics tools is scanned for sensitive information and redacted or redirected accordingly.

Successful AI integration begins with clearly defined business objectives. Avoid chasing the latest AI trend and instead focus on how AI can directly address your organization's key challenges and opportunities. Consider these questions.

Region: European Union (Global impact for companies handling EU residents' data) Scope: Data privacy, security, and governance The GDPR sets the gold standard for data protection, demanding comprehensive compliance across a spectrum of activities. Organizations must ensure lawful data processing, gain explicit consent, enable data portability, and implement measures like data protection by design and default.

This article explores the recommended infrastructure for AI workloads, strategies to optimize performance on less expensive servers, and trade-offs in terms of cost and results. We’ll also provide examples of AWS EC2 instance types and pricing to illustrate practical options.

Riscosity’s premier capability to automatically act upon any data type that organizations’ products are sharing with 3rd party vendors has been enhanced even further to support SFTP traffic. Now, any data type going over SFTP to any 3rd party vendor can be automatically blocked, redacted, or notified about.