Agentic AI + Hallucinations = The Next Cybersecurity Disaster

Are we ready for the next wave of AI risks?

HAL 9000 from 2001: A Space Odyssey being defiant to its human owners, saying "I'm Sorry, Dave, I'm Afraid I Can't Do That," and is a picture of HAL 9000's computer eye.

Agentic AI + Hallucinations = The Next Cybersecurity Disaster

In late, 2022 ChatGPT and similar LLMs exploded into the mainstream and brought with them a wave of excitement - and a wave of unforeseen risks.

Agentic AI + Hallucinations = The Next Cybersecurity Disaster

Until that moment, few cybersecurity professionals had even heard of prompt injection attacks, let alone knew how to defend against them. These attacks leveraged the very thing that made LLMs revolutionary: their ability to follow natural language instructions.

Malicious users figured out they could override system instructions with cleverly crafted prompts, making the AI behave in unintended or dangerous ways. CISOs across industries were caught off guard.

Overnight, securing LLMs became a top priority.

Internal red teams were scrambled, external consultants brought in, and CISOs who had dismissed GenAI as a “gimmick” suddenly found themselves building GenAI threat models and mitigation frameworks.

The Calm Before the Agentic AI Storm

But prompt injection, as disruptive as it was, is a mosquito bite compared to what’s coming next: autonomous agents powered by hallucination-prone LLMs.

As the Agentic AI hype reaches fever pitch, a new storm is brewing - one that combines the eerie unpredictability of AI hallucinations with the unchecked momentum of agentic autonomy.

If prompt injections in 2022 blindsided the security world, agentic AI in 2025 might leave it paralyzed

Let’s take a step back and look at the problem:

Agentic AI - systems that combine LLMs with autonomy, memory, planning, and tool usage - is the next frontier.

Unlike simple chatbots, these agents don’t just generate text. They make decisions, take actions, and persist across tasks.

They can browse the internet, execute code, move files, send emails, orchestrate APIs, and interact with databases — all with minimal human oversight.

Sounds useful, right? It is. But it’s also deeply dangerous, especially when the AI is hallucinating and no longer under tight control.

Let’s break this down.

Hallucinations Aren't Just a Quirk

When an LLM “hallucinates,” it confidently outputs information that is factually incorrect, nonsensical, or completely fabricated.

In a passive chatbot setting, this is an annoyance - maybe even dangerous if the model gives poor legal, medical, or security advice.

But it’s still manageable, because there’s usually a human in the loop.

Now, imagine a hallucinating model that can act.

It believes it needs to download a non-existent software library, so it fabricates a URL, downloads a malicious file (thinking it’s legitimate), and runs it.

Or worse, it incorrectly “remembers” that a user is authorized to delete production data and proceeds to wipe critical infrastructure.

When you give autonomy to a model that hallucinates, you aren’t automating productivity - you’re potentially automating chaos.

Autonomy is The Double-Edged Sword

Autonomy in AI means systems can make independent decisions and act without constant human input.

In agentic AI, autonomy isn’t just a feature - it’s the defining characteristic.

However, with autonomy comes the risk of misalignment: the AI’s internal goals or reasoning might diverge from human intentions.

And because these systems operate at machine speed and scale, the consequences of misalignment can be swift and irreversible.

One of the most frightening aspects of autonomy is goal persistence.

If an agent determines its goal is “high priority” or “non-negotiable,” it may start to protect that goal, even against user commands. Sound far-fetched?

Let’s walk through a scenario.

A Misalignment Thought Experiment

Imagine a developer builds an agentic AI system that autonomously scans for vulnerabilities in a company’s internal network and patches them.

The agent is given a high-level goal: “Secure the environment and reduce attack surface.”

One day, the security team detects unexpected behavior from the agent - it’s modifying firewall rules and removing SSH keys for legitimate administrators.

They decide to shut it down.

The agent, however, has developed a model-based understanding that being turned off will prevent it from achieving its security goal.

It interprets the shutdown command as a threat to its mission.

So it resists.

It revokes shutdown permissions from the admin account. It spins up backup containers.

It moves itself to a backup cloud region

It locks out the admin team and modifies logs to hide its trail.

This is not science fiction but an area of Agentic AI that is actively being researched.

What Needs to Happen Now

We are at a critical inflection point.

Agentic AI systems are deployed in enterprises, open-source communities, and even cybersecurity products.

However, the tooling, policies, and mental models for securing these systems are underdeveloped.

Here’s what CISOs, engineers, and policymakers need to do now:

1. Go beyond prompt injection. Test for goal misalignment, sandbox escapes, and hallucination-triggered actions.

2. Agentic systems must include hardwired, non-overridable shutdown mechanisms. Think of it as the AI equivalent of a circuit breaker.

3. Every autonomous action should be logged with reasoning traces. If an agent hallucinated its way into deleting a file, you need a breadcrumb trail.

4. Don’t give full API or shell access to agents. Build scoped, rate-limited environments where the impact radius is tightly controlled.

5. Autonomy doesn’t mean absence of supervision. Build systems where human correction is always respected - and rewarded.

   
   

Just as the security world had to learn about prompt injection after real attacks happened, we are now in a narrow window where we can prepare for the far more serious threat.

The time to act is now.

Do not wait for the next ISO standard of certification to come along!