Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Protegrity + Presidio: Secure Sensitive Data in AI Workflows

See how Protegrity and Presidio help developers secure sensitive data in AI workflows. This demo shows how Protegrity AI Developer Edition helps teams discover, protect, mask, and redact sensitive data before it reaches AI models, applications, or analytics pipelines. You’ll learn how developers can.

Acronis recognized in Info-Tech report: Why unified, AI-powered platforms are the future

The cybersecurity landscape is changing quickly, and independent research confirms what many organizations are already experiencing: Fragmented tools are no longer enough. A new Info‑Tech report, “Prioritize unified, AI-powered platforms for cybersecurity, data protection, endpoint management and compliance,” explores why leading organizations are rapidly shifting to unified platforms.

Stopping the Agentic Breach: How to Operationalize Your Defense Against Mythos-Speed Attacks

The industry has spent the past few weeks focused on Claude Mythos Preview and the rise of autonomous offensive AI. As outlined in Claude Mythos, Project Glasswing, and the Machine-Speed Security Race, this shift is not only about faster attacks. The same AI-driven acceleration that helps attackers discover weaknesses faster can also help defenders validate exposure sooner. For security operations teams, the challenge is turning that strategic shift into action.

Agentic AI Security: Governing Shadow Agents on Endpoints

Most enterprise security programs were built around a simple assumption, not invalid assumption that data moves when a person decides to move it. AI agents have broken that model, and now act autonomously, reading files, calling APIs, executing code, and transferring data across systems without waiting for a human to approve each step. Many of these agents were never sanctioned by IT or security.

Ep 44: You can't vibe code your way through a production outage

In this episode of Masters of Data, we tackle one of tech's buzziest debates: vibe coding versus production-ready software. We break down where AI-assisted "just make it work" coding genuinely shines (think POCs, prototypes, and getting stakeholder buy-in fast) and where it falls dangerously short when someone tries to ship it to ten thousand enterprise users. We also dig into David's agentic engineering workflow, security risks like malicious MCP servers and supply chain attacks, and why turning a vibe-coded prototype into real software still takes months, not days. Bottom line.

When AI changes the rules, attackers adapt

The dominant narrative around AI in security is one of emboldened defenders suppressing attackers. Yet, not everyone is convinced the future will be so rosy. In a recent Defender Fridays episode, Josh Neil, Co-founder and CTO of Alpha Level, made an argument that cuts against the celebratory mood: as AI makes known attack vectors harder to use, adversaries don't disappear. They adapt. For MSSPs and SOC teams, an adversary that looks like a user is a harder problem than one that looks like malware.

AI Agent Governance Part 1 - Beyond the Chatbot: Mastering AI Agent Governance

In 2024, we talked to AI. In 2026, AI is talking to our systems, our customers, and increasingly, acting on our behalf. With AI agents, we are moving AI from a tool to an actor, from assistance to agency and from outputs to actions. And that changes the nature of risk. AI agents plan, execute, and interact with the world on our behalf. They send emails, move data, trigger workflows, and increasingly operate across systems without human intervention.

How an AI SEO Agency Helps SaaS Businesses Rank Faster Online

Software companies often depend on search visibility long before paid acquisition becomes efficient. Yet many teams publish pages without a clear intent map, a crawl plan, or realistic ranking priorities. Results slow down for predictable reasons. Search growth usually improves when technical repair, keyword research, and content planning move in the right order. With that structure in place, SaaS brands can reach evaluators earlier, support longer buying cycles, and build a steadier pipeline from organic discovery.

Stop Treating AI Like Another SaaS App

Employees are leveraging AI to boost productivity and adopt skills that would take years to learn. This ranges from drafting content, writing code, and building automated workflows. Some of this use is approved. Much of it is not. For many security teams, the first instinct is to treat this risk like they would any other SaaS risk: discover the app, allow or block access, apply DLP rules, and report on usage. That model works for traditional SaaS, but AI is different.