Agentic AI in Cybersecurity: Not Ready for Prime Time

In the quest for latest cybersecurity solutions, agentic AI tools have been touted as potential game-changers. But not so fast. Recent evaluations show these tools aren't ready to replace tried-and-true methods like Static Application Security Testing (SAST) tools, specifically Bandit.

The Experiment

Researchers pitted general-purpose GenAI Large Language Models (LLMs), hosted by Ollama, against Bandit, a vetted SAST tool. They assessed precision, recall, false positives, and an overall composite score to determine effectiveness. Three different open-source models were tested, yet none could meet the specialized demands of SAST scanning under realistic conditions.

What does this mean for the cybersecurity landscape? Simply put, agentic AI tools, while promising, aren't yet viable for these specific tasks. They're not banning tools. They're banning math. The limitations of these models make it clear that we're not there yet. It's like bringing a knife to a gunfight.

Why It Matters

The idea of using AI to make easier and enhance cybersecurity is appealing. Who wouldn't want a digital guardian watching over their systems? But here's the rub: if it's not private by default, it's surveillance by design. The chain remembers everything. That should worry you. Inaccurate results from agentic AI can lead to missed threats or false alarms, jeopardizing the very security they're meant to protect.

Let's not forget the human element. Current tools like Bandit are vetted, tested, and trusted. They bring a level of confidence that newfangled AI models simply can't match right now. Opt-in privacy is no privacy at all, and the same goes for opt-in security.

The Road Ahead

So, where do we go from here? It's clear that while agentic AI holds potential, it's not ready to take on specialized cybersecurity tasks alone. We must continue to refine these models, perhaps focusing on how they can complement existing tools rather than replace them.

Financial privacy isn't a crime. It's a prerequisite for freedom. Similarly, security without compromise is essential for trust in digital systems. The future of cybersecurity will likely blend traditional methods with AI advancements, but for now, reliance on proven tools is the safest bet.

In the end, the promise of AI in cybersecurity is enticing, but we need to remain cautious. The tech world often chases the latest innovations without fully considering their ramifications. So, are we ready to put our trust in agentic AI tools? Not yet. The technology, as it stands, still has a long way to go.