For years, cybersecurity has had a familiar villain: the external attacker. The hacker breaking through the firewall, stealing credentials or exploiting an unpatched vulnerability. It is the scenario we have trained for, built defenses around and spent decades trying to prevent.

Lead Analysts: Prabhakaran Ravichandhiran and Jeewan Singh Jalal

As a CISO advisor, I am observing a familiar pattern gaining a new, critical dimension. What we historically identified as "Shadow IT", the use of unapproved SaaS and tools, is rapidly evolving into "Shadow AI."

Employees are increasingly leveraging AI bots for drafting, analysis, code generation and strategic decision-making. While the intention is often to drive efficiency, the lack of governance creates a dangerous risk surface: sensitive data leakage, compliance violations and the potential for operational decisions based on unverified, AI-generated content.

AI agents offer unprecedented capabilities, speed, automation, deep context, and hyper-personalization, that will transform how we work. However, these same capabilities make AI agents significantly more dangerous than traditional software when hijacked by cybercriminals.

When we first introduced Agent Risk Manager, the response was clear: many security teams are actively looking for a way to secure the AI agents already running in their environment and how they can confidently adopt AI across their organization.

Future-proofing organizations in the face of AI requires a unified defense strategy that secures both the human workforce and autonomous AI agents. One of the key requirements is shifting security cultures from reactive compliance to proactive, measurable behavioral change.

The recent developments surrounding vulnerabilities in major AI repositories like Hugging Face serve as a critical wake-up call for the cybersecurity community. As we accelerate toward an agentic future, the platforms we rely on for innovation are increasingly becoming the primary vectors for systemic risk.

Cybercrime used to have a ‘"tell." It was the digital equivalent of a villain stroking their cat - clunky grammar, misspelt links and suspicious attachments that screamed ‘phishing’.

So, you have some AI tools or are thinking about deploying them and want to know a bit about securing them.

You are not alone, but there are significant challenges due to the rapidly growing capabilities of AI, and the issues around new types of vulnerabilities we may not be used to thinking of. This is a very challenging area to attempt to secure, but I hope to point you in the right direction and set you up with some resources.

Boxers will often say, the punches that hurt the most aren’t the ones which are thrown with the most force, but the ones they didn’t see coming. I think the same is true in cybersecurity. It’s not the most advanced technically efficient, 0-day utilizing attacks that have the biggest impact, but rather those quiet ones. With no malware or suspicious login at three in the morning from an IP address in a country your company has never done business with. No alert fires. No dashboard turns red.