Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Security teams today face an overwhelming volume of alerts, making it increasingly difficult to distinguish genuine threats from everyday noise. As attackers become more adept at blending into legitimate activity, organizations need smarter ways to prioritize, investigate, and respond.

AI has swiftly shifted from a browser-based chat interface to an autonomous actor operating within enterprise environments. Agents run locally on endpoints, inherit employee permissions, access sensitive data in bulk, and execute multi-step workflows with no human approving each step. That shift fundamentally changes the enforcement surface. The governance programs most organizations have built were designed for a different model: one user, one prompt, one decision.

Nine seconds. One API call. A car rental software company’s production data was gone. That’s the headline from the PocketOS incident, and it’s the reason this story spread across engineering and security circles the way it did in late April. Two months later, the incident is no longer breaking news. But it hasn’t aged out of relevance; it has aged into a pattern.

In the March / April 2026 AV-TEST Advanced Threat Protection evaluation, Acronis Cyber Protect Cloud once again earned Advanced Approved Endpoint Protection certification with a perfect 35 out of 35 protection score. The result was achieved in testing against advanced ransomware and infostealer attacks on Windows 11, where Acronis successfully defended against all 10 attack scenarios evaluated by AV-TEST.

Bot mitigation is an adversarial game: attackers adapt, defenders respond, and the cycle continues. At Cloudflare, we stay ahead by combining visibility across our global network with signals from the client-side environment. At the network level, we analyze over 1 trillion requests per day to understand reputation, patterns, and anomalies across more than 20% of the web.

Every HTTPS connection starts with a TLS handshake. It’s the security check, answering “are you who you say you are?” and “how are we going to keep this conversation secret?”. There’s a lot going on during the handshake, and there used to be even more before it all got hacked and removed. And that’s useful to understand, the modern TLS 1.3 handshake is short because everything else got compromised.

In early July 2026, researchers at Sysdig published an analysis of what they assess to be the first documented case of agentic ransomware. The threat actor, which Sysdig calls JADEPUFFER, launched an extortion attack driven end to end by a large language model (LLM) rather than a conventional human-operated toolkit.

It’s amazing how non-developers have recently been empowered to create their own apps that can even generate revenue. We’ve recently seen progress across the AI development field, from AI being successful in “greenfield code” (apps built from scratch) towards “brownfield code” (larger scale existing applications).

AI adoption has accelerated faster than most organizations’ ability to manage it. Security and compliance teams are now responsible for overseeing machine learning models, large language models (LLMs), agentic AI systems, and shadow AI — often with frameworks and processes that weren’t built for any of it. The gap between deploying AI and governing it responsibly is where risk lives. AI governance tools exist to close that gap.