Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

From Neural Networks to Threat Networks: How AI Development is Reinventing Security Intelligence

In the digital age, the landscape of cybersecurity is evolving faster than ever. Threat actors are becoming increasingly sophisticated, while traditional security measures struggle to keep pace. Enter Artificial Intelligence (AI)-an innovation that is transforming security intelligence by converting neural networks, traditionally used for pattern recognition, into threat networks capable of predicting, detecting, and mitigating cyberattacks in real time.

How MSSPs can automate their way to full-spectrum security

The end of October is here, which means it is time to ask: What have you, as a managed service provider (MSP), learned from Cybersecurity Awareness Month? The most critical lesson remains that human behaviour is the single greatest risk and the single greatest opportunity for defence. While no amount of training can eliminate every mistake (which is why we need automation), a security-aware technician acts as the final, critical filter that can spot novel social engineering attacks and enable fast incident response, but only if the back end is hyper-automated, so technicians know about these potential attacks immediately.

The New Attack Surface: How to Break (and Defend) Large Language Models

Large Language Models now automate customer support, write code, classify emails, generate content, and - disturbingly - execute tasks through plugins and agents. Once an AI can act on your behalf, it becomes part of your operational infrastructure, not a toy. OWASP’s Top-10 for LLM Applications formalized the threat landscape, and quietly confirmed what security researchers have been yelling for two years.

Experience Over Hype: How Reach Built AI for Real-World Security

Innovation comes from experience — and from taking a pragmatic, problem-driven approach. As Garrett Hamilton told Ed Amoroso, Reach’s foundation is built on the work of co-founder Colt Blackmore — whose experience building machine-learning models at Cylance and Proofpoint now drives how we apply AI to exposure management today. That experience shapes how Reach approaches AI: practical, proven, and focused on results — not trends.

Why Mid-Market Organizations Can't Afford to Ignore Open Source Vulnerabilities

There are millions of dollars on the line for companies relying on open source. Failure to stay CVE-free can lead to churn, closed-lost deals, and countless engineering hours wasted chasing fixes instead of shipping features. Unlike enterprises with large budgets and compliance buffers, a single failed review, missed SLA, or unresolved CVE can derail $5M–$20M in just one quarter. This is the difference between hitting growth targets or missing them entirely.

What is KeeperAI?

KeeperAITM is an agentic, AI-powered engine embedded within KeeperPAM that delivers real-time threat detection and response, as well as privileged session analysis. Built for Privileged Access Management (PAM), KeeperAI monitors user activity, providing behavioral insights and automated incident response in both live SSH sessions and post-session playback.

Inside the biggest API breaches (and how to stop the next one)

APIs power the modern digital world — but they’re also the fastest-growing attack surface. In this webinar, we break down the biggest API breaches, their root causes, and how they could have been prevented. What's covered: Featuring: Live insights and a product demo by the Astra Engineering Team.

Seemplicity's AI Agents: Clarity

Meet Clarity, the first of Seemplicity’s four new AI Agents transforming how security teams understand and act on vulnerabilities. Instead of cryptic scanner outputs and confusing CVE text, Clarity turns dense technical data into clear, actionable narratives — explaining what happened, why it matters, and how to fix it. With Clarity, you can: Translate vulnerability data into plain language Improve collaboration between security, IT, and engineering Accelerate remediation and reduce exposure fatigue.

It's time to rethink shadow AI.

It's time to rethink shadow AI. We've been told it's a fringe activity. A risk from rogue employees. Our new research proves that wrong. This is, ironically, no longer a "shadow" problem. It's a universal workflow hiding in plain sight. The question is no longer "how do we stop it?" It's "how do we manage it?" Our new report lands next week with the date you need to start answering that important question.