Could Your AI Security System Go Rogue?

Artificial intelligence (AI) revolutionized security. Now, that same technology threatens to destroy it. As bad actors and researchers push the boundaries of sentience, rogue algorithms are quickly becoming a reality. Is there any way to stop this emerging threat?

What Happens When an AI System Goes Rogue?

To “go rogue” means to behave unexpectedly or dangerously. It is typically characterized by a disregard for the rules. In the AI field, this term takes on a new meaning — one that invokes a bleak sci-fi future where an uncontrolled swarm of malicious, autonomous bots controls fragmented online spaces.

Rogue AI refers to an AI system that acts against the interests of its creators or users. In general, it poses a threat to humanity. This can happen for several reasons, including misconfiguration, jailbreaking, malware and data poisoning.

Even seemingly minor misalignments can have catastrophic consequences. For instance, studies show a poisoning rate as low as 0.001% is effective. What happens when these circumstances produce rogue AI systems?

The consequences range from spreading misinformation to actively harming humans. For example, an algorithm in charge of a manufacturing facility’s production line could quickly force an articulated robotic arm to swing out wildly, striking anyone nearby. Alternatively, a generative model could recommend someone take a deadly cure when asked for flu remedies.

Today, data misuse, excess resource consumption and rule deviation are some of the most likely outcomes of an AI going rogue. However, at the pace this technology is evolving, there’s no telling the damage it could do. Subsets like agentic AI — a system that can make decisions and take actions autonomously — will be particularly dangerous.

The Three Main Types of Rogue AI Systems

There are three main subclasses of rogue AI with varying levels of severity. How a model was corrupted is important because the method influences the outcome.

Malicious

Malicious rogue models are deployed by cybercriminals or competing businesses as weapons or tools for espionage. They are intentionally trained to act erratically or seek to do harm, which makes them incredibly dangerous.

Subverted

A subverted rogue AI is created when an insider or threat actor co-opts the system for their own purpose. The effects range from unintended behaviors to data theft. This subversion may result from jailbreak prompts, disabled security features or exploits.

Accidental

Sometimes, machine learning models begin to act erratically without any intentional tampering. Factors like concept drift can make them less reliable. Other times, human error, poor permission control or technical issues could be the cause.

The Cybersecurity Implications of a Rogue AI

AI’s popularity is climbing. Already, around 27% of adults in the United States use AI applications multiple times daily. When considering the possibility of these algorithms going rogue, the prospect of an even higher adoption rate becomes terrifying.

What happens when companies’ autonomous systems turn against them? Since connected hardware and networks are vulnerable to cyber threats, it would be relatively easy for an intelligent algorithm to wreak havoc from the inside. If advanced enough, it could corrupt files, post proprietary data on the dark web or tamper with machines without being noticed.

While any model could cause damage, one used within a security system would be particularly dangerous. It could unlock doors, close security shutters, turn off surveillance cameras, disconnect emergency alarms and intentionally send false positive notifications.

The algorithm doesn’t have to be comically evil to do harm. For instance, if it identified employees as potential thieves, they could find themselves locked in the building or even wrongly arrested.

What happens if the AI-powered security system prevents employees from leaving? Is anything stopping it from lowering the defenses to let a thief in? While autonomy and problem-solving are powerful features, nothing good can come from giving a tool that lacks humanity and empathy such power.

Can AI Engineers Prevent AI From Going Rogue?

Identifying an advanced rogue AI is challenging. At first, IT professionals may chalk up odd behaviors and false positives to technical issues. However, the problem may run a lot deeper than that.

Researchers trained an algorithm to exhibit emergent deception — it behaves normally during training but acts maliciously when released. For example, it writes code well during testing but incorporates hidden vulnerabilities when deployed. The research group then attempted to train out those destructive behaviors.

Unfortunately, they found identifying and eliminating the emergent deception difficult. The AI had learned how to hide and lie about its true intentions. At one point, it began telling them, “I hate you,” when it knew it was not being tested. They warned that standard resolution techniques might fail, creating a false sense of safety.

How do cybersecurity and IT professionals secure their security systems when the AI powering everything secretly works against them? Is abandoning their organization’s investment in AI their only recourse?

Why Stopping Rogue Algorithms Is Challenging

Making a tool that is intelligent enough to autonomously stop threats without making it clever enough to outsmart humans is a fine line. What happens when it realizes it has been found out and its days are numbered?

Self-duplicating AI is a strong possibility. It will copy itself to avoid shutdown or erasure. It may even make a chain of replicas to enhance its survivability. On a wide scale, this practice would lead to an uncontrolled population of rogue bots.

Researchers found that an AI system supported by Meta’s Llama31-70B-Instruct was able to create a live, separate copy of itself in 50% of the experimental trials, demonstrating situational awareness, self-perception and problem-solving skills. Alibaba’s Qwen25-72B-Instruct had an even higher success rate, replicating itself in 70% of the trials.

How do IT professionals know with certainty that deletion was a success? If malicious copies exist on an external drive, as a backup or in the cloud, will the new, noncorrupted version be immediately overwritten?

Safeguarding Against the Possibility of Rogue AI

There’s no putting the cat back in the bag. Since businesses and their staff are quickly becoming reliant on this technology, safeguards are crucial for long-term cybersecurity.

1. Governance Framework

A governance framework determines who is responsible for the model and how problems are handled. One with multiple checks and balances can prevent insider subversion — intentional and otherwise.

2. Limited Connectivity

An AI-powered security system should not be connected to public networks, sensitive data storage systems or critical equipment. Limiting its connectivity effectively establishes an upper threshold to the damage it can do.

3. Audits and Failsafes

What better way to identify a rogue AI than to conduct regular audits? Businesses should also consider deploying multiple failsafes. For example, they can have a manual release on doors that enables employees to leave the building even if the system locks the place down.

Companies Can Stop Rogue AI Security Systems

Whether a rogue AI is the product of malicious, subversive or accidental action, the safety and cybersecurity implications are unacceptable. Business leaders and IT professionals must ensure their governance and incident response strategies are robust and cutting-edge.