Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

With the abundance of compliance requirements that organizations must comply with, such as HIPAA, PCI and GDPR to name a few, there is an increasing need for organizations to properly classify sensitive data and safeguard it accordingly. Identifying and classifying sensitive data is a crucial initial step in an organization’s compliance journey.

There was a time when “AI red teaming” sounded like a novelty. Now, it’s fast becoming table stakes. If your organization is shipping machine learning or LLM-powered systems into the real world (especially in sensitive domains), you need to know how those systems behave under pressure. That’s where AI red teaming tools come in. These tools help teams stress-test AI the way it will actually be used (and misused).

The UK government has taken a proactive step by recently releasing the Software Security Code of Practice, a vital framework aimed at strengthening the cybersecurity posture of organizations that develop and sell software. This code outlines essential practices and principles, guiding companies to enhance their software security throughout the development lifecycle, from initial design to final deployment.

In June 2025, FBI New York and the U.S. Attorney’s Office for the Southern District of New York announced charges against “IntelBroker,” the online persona of 25-year-old British national Kai Logan West. IntelBroker operated one of the most sophisticated data brokerage operations documented in the recent history of cybercrime.

As AI capabilities grow, organizations are adopting it for compliance monitoring, risk analysis, and data processing. However, increased use also introduces new risks, making strict regulation essential, especially in sectors where sensitive data is involved—like finance, insurance, and healthcare. Mishandling this information can lead to reputational damage, legal action, or hefty fines.

Mobile apps are everywhere. From the moment we wake up and check the weather to staying connected with friends and family, our lives are woven together by apps. They manage our money, track our workouts, store our memories, and even help us find love. But with this convenience comes a hidden cost: our privacy. Every tap, every swipe, every “allow” permission is a potential gateway for data to flow, sometimes to places we never intended.

PCI DSS compliance isn’t just about ticking off controls, but it’s more about how your infrastructure is architected and enforced. Few decisions influence the scope of compliance as directly as the implementation of network segmentation. Every additional system brought into the PCI scope adds operational friction: more logs to review, more systems to harden, more controls to audit. One misconfigured firewall rule or a forgotten DNS server can quietly pull half your network into scope.

Most healthtech teams focus on building fast, getting the ABHA APIs working, passing the sandbox, and moving to production. However, the reality is that over functionality, if your app can’t prove it’s secure, you don’t go live. The ABHA Web Application Security Certificate exists for one primary reason: to prevent vulnerable systems from accessing India’s health data network.