Researchers create AI-powered worms that adapt attacks and spread chaos across networks

Reviewed byNidhi Govil

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University of Toronto scientists have built a prototype worm using open-source AI models that can autonomously spread through networks, tailoring attacks to exploit multiple vulnerabilities. Unlike traditional worms, this AI threat learns new strategies with each infection and siphons computing power to fuel future attacks, raising urgent concerns about a new era of cyberattacks that could be nearly impossible to stop.

University of Toronto Builds Self-Learning Worm That Exploits Vulnerabilities Without Human Intervention

Researchers at the University of Toronto have demonstrated how open-source AI technology can be weaponized to create dangerous computer worms with AI that autonomously spread through computer networks, marking a significant escalation in cybersecurity risks. The team, led by Professor Nicolas Papernot, built a prototype in a secure, isolated environment that successfully propagated across their test network with no human intervention, exploiting security flaws across multiple platforms including Linux, Windows, and IoT devices

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Source: Engadget

Source: Engadget

Unlike traditional computer worms such as SQL Slammer, Conficker, or the 2017 WannaCry attack that infected over 300,000 machines in 150 countries, these AI-powered worms represent a fundamental shift in how malware operates. While conventional worms exploit specific network flaws and can be stopped by patching those vulnerabilities, this new breed of AI threats tailors its attack to different types of flaws across multiple platforms

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. The researchers deliberately redacted some details from their paper to prevent hackers from using it as a blueprint for attacks

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AI-Powered Cyber Threats Learn and Adapt With Each Machine Infected

What makes these AI-powered worms particularly dangerous is their ability to "reason" through new attack strategies as they spread through computer networks. The prototype gathers data as it moves, siphoning passwords and uncovering more vulnerabilities that help it take over other machines

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. If an infection is discovered and patched on a computer, the worm can exploit other flaws to attack the same machine, making it significantly more difficult to stop the spread of malware

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Perhaps most concerning is the worm's ability to "feed" itself by siphoning processing power from infected machines to power its reasoning and strategy for future attacks. "Hackers have typically had to prioritize the most high-value targets because time and computing resources were limited," said lead author Nicolas Papernot. "But now, once a worm is launched, the cost would drop to nearly zero"

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. This self-sustaining characteristic means there is no longer a single software fix that can be applied to devices to protect them from the worm

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Open-Source AI Technology Creates Unstoppable Threat Landscape

The research adds a troubling dimension to ongoing concerns about AI and cybersecurity. Because the AI technology powering the worm was open-source or "open weight"—meaning it has been freely shared on the internet—no one can restrict how it is used. "You have to have a perfectly secure system to defend against this—and we know that is not currently feasible," Papernot warned

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This development comes as industry leaders like Anthropic and OpenAI have already begun restricting access to their most powerful cybersecurity tools. In April, Anthropic announced that its Mythos model was too powerful to share with the public because hackers could use it to exploit vulnerabilities faster than ever before. The company reported that Mythos had already uncovered more than 10,000 flaws, boosting its partners' bug-finding rate by more than a factor of 10. Cloudflare found 2,000 such vulnerabilities, including 400 considered high or critical

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. OpenAI followed suit a week later, initially limiting its similar technology to hundreds of organizations before expanding to thousands of partners

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Source: NYT

Source: NYT

Policymakers and Industry Leaders Face Urgent Call to Action

While the Toronto prototype can only exploit known flaws and not find unknown ones like the Mythos model, security experts recognize that bad actors could easily adapt it to both discover and exploit new vulnerabilities—making it nearly unstoppable if released into the wild. In recent months, companies and government labs, including several in China, have released increasingly powerful open-source systems, challenging earlier assumptions that open-source AI technologies weren't powerful enough to drive self-replicating computer worms

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"In an interconnected world, no system is immune to this threat," Papernot emphasized. "Sharing these findings is the first step in galvanizing researchers, industry leaders and policymakers to take action—and quickly"

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. The research signals that we may be entering a new era of cyberattacks where traditional defense mechanisms prove inadequate, and where the line between offensive and defensive AI capabilities becomes increasingly blurred. Organizations maintaining critical infrastructure must now prepare for threats that can adapt faster than human defenders can respond, potentially causing widespread chaos across global networks.

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