Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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Top 7 Questions to Ask When Evaluating a Software Composition Analysis Solution

Your open source usage is out of control. Sure, it’s helping you develop your product faster and getting new releases out the door in days instead of months, but now your code base is made up of 60% or more open source components. And that percentage is only growing. The application layer continues to be the most attacked, so you know you need to stay on top of vulnerabilities.

Network Policy with GKE

By default, pods are non-isolated; they accept traffic from any source. The Google GKE solution to this security concern is Network Security Policy that lets developers control network access to their services. Google GKE comes configured with Network Security Policy using Project Calico which can be used to secure your clusters. This class will describe a few use cases for network security policy and a live demo implementing each use case.

4 Reasons Why the OSI Model Still Matters

When it comes to security, practitioners have to keep a lot they need to keep top of mind. The Open Systems Interconnection (OSI) model provides the fundamentals needed to organize both technical issues and threats within a networking stack. Although information security is shifting to a cloud-first world, the OSI model still continues to prove its relevance. We’ll cover four key reasons why the OSI model still matters and how you can operationalize it in today’s world.

Best Practices for FinTech APIs

How many third-party APIs is your application consuming? All modern FinTech companies rely on external APIs to run their business. Take Robinhood for instance: the famous investment application is using the Plaid API to connect to its users’ bank accounts, the Xignite API to get financial data, and the Galileo API to process payments. That is only the beginning. The essential parts of their service could not run without consuming third-party APIs.

Dark Web monitoring and scanning explained

Shady deals often occur in darkness – criminal activities require secrecy to cloak their illicit nature. Today, you can find those dark places on the fringes of the internet, known as the Dark Web. More often than not, this is the place where cybercriminals go to monetize the data they’ve acquired as the result of a breach.

Leveraging behavior analytics and machine learning algorithms in your PAM strategy

Modern technologies like machine learning (ML) algorithms can introduce a forward-thinking outlook to privileged access management (PAM) and enable enterprises to predict emerging access risks in real time. ML-based anomaly detection systems can deeply analyze raw data collected around privileged activity, profile standard user behavior patterns, and then surveil future operations to detect any deviations from the norm, such as server logins after office hours.