Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Agentic AI is transforming cyber threats from phishing and deepfakes into nonstop zero-day exploits and automated ransomware. Most organizations will struggle to keep pace, but the same AI power can drive autonomous defenses that ultimately shift the balance back to the defenders.

I have never been one to jump on most technology bandwagons early; I am very pragmatic about what technology can do rather than what it promises. This extends to generative AI. I was not the first to play with ChatGPT and Gemini when they came out in the early 2020s. Maybe it’s because I work in fields that use machine learning very effectively. Even though I was aware of the leap Google made in 2012, I wasn’t eager to dive into the new wave of AI when it first appeared.

Cybercriminals are taking stealth to new levels. According to WatchGuard Technologies’ latest Internet Security Report, evasive malware attacks jumped 40% in Q2 2025, driven by a sharp rise in threats delivered over encrypted connections. While Transport Layer Security (TLS) encryption is essential for protecting users, attackers are increasingly exploiting it to conceal malicious payloads and evade traditional detection methods.

The virtual private network (VPN) has been the default way to connect remote employees to company resources for over two decades. In its time, the VPN was a breakthrough ‒ creating encrypted tunnels back to the corporate network and giving road warriors a way in. But today's workplace looks very different. Employees access SaaS applications directly from the Internet. Teams are distributed around the world.

WatchGuard Technologies has been recognized as both a Leader and an Outperformer in the 2025 GigaOm Radar Report for Endpoint Detection and Response (EDR). Out of more than 25 vendors evaluated, WatchGuard is recognized as a top Innovator and ranked highly for the core EDR capabilities.

The cybersecurity landscape has evolved, but many endpoint tools have not. Most still focus on known threats and signatures, blocking familiar malware and flagging suspicious files. They rely on static models that can only go so far. That approach worked for yesterday’s threats, but not for today’s attackers.