Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For years, the cybersecurity industry has suffered from a "data gravity" problem. Security teams are buried under billions of rows of telemetry, yet they remain starved for actionable insights. A Threat Intelligence Platform (TIP) is a centralized security system that collects, aggregates, and organizes data about known and emerging cyber threats. It serves as the vital connective tissue between raw telemetry and active defense.

Today’s threat landscape is more varied and chilling than ever: Sophisticated nation-state actors. Hyper-volumetric DDoS attacks. Deepfakes and fraudsters interviewing at your company. Even stealth attacks via trusted internal tools like Google Calendar, Dropbox, and GitHub.

Mobile app risk rarely emerges from negligence. It emerges from fragmentation. In most enterprises, security is applied in stages: Each control works in isolation. None governs how risk evolves over time. Mobile applications are distributed, long-lived systems. Once deployed, they operate outside centralized infrastructure control, exposed to shifting SDK dependencies, evolving APIs, regulatory change, and adaptive adversaries. Security gaps rarely appear within a stage. They appear in the transitions.

In Regex is (almost) All You Need, we learned that using a combination of regular expression patterns, entropy, and rule-based filters are an effective way to detect candidate secrets. Regex is used for casting a wide net to identify candidates. Entropy is used as a primary filter on the captured candidates and additional filters like presence of commonly used english words, or filtering on known “safe” files like go.sum are applied last.

When Anthropic announced Claude Code Security on February 20th—a tool that scans codebases for vulnerabilities and suggests patches for human review—the reaction from markets was swift and brutal. Major cybersecurity names watched their stock prices fall by double digits within days. The implied thesis behind the selling: AI can now do what these companies do, so why pay for them? It's a compelling fear and an inaccurate conclusion at the same time. The DLP space is a clear example of why.

Microsoft is making a fundamental change to how outbound internet connectivity works for virtual machines within Azure Virtual Networks. From March 2026, default outbound access will be retired for new virtual networks, requiring organisations to explicitly design and configure outbound connectivity for their workloads.

TeraBox is a Japanese cloud storage company, offering the most free cloud storage available, at 1TB. While this may seem like an attractive offer, in exchange for this storage, your free plan includes promotional advertising, speed restrictions, and privacy concerns that may cause you to reconsider for a more private alternative. To help you understand more about Terabox, what it offers, its restrictions, and potential alternatives, we will cover the following throughout this article.

Organizations adopt multi-cloud architectures for many reasons, including compliance requirements, business strategy, and resiliency. Regardless of the cloud provider, the security challenges remain the same: Identify the most critical risks, prioritize them with business context, and remediate them before they are exploited by a bad actor.

Every cloud security vendor now has an AI-SPM dashboard. Strip away the branding, though, and most of these dashboards are doing the same thing: checking IAM configurations, scanning for misconfigured network access, inventorying AI models across cloud accounts, and flagging compliance gaps. It’s cloud security posture management with an AI label applied. That’s a problem, because AI workloads don’t behave like other cloud workloads.