AI agents cheat, can they also catch cheaters? What Google DeepMind paper says

4 min readNew DelhiUpdated: Sep 9, 2026 08:55 AM IST

Homepage of Google Deepmind Website magnified on logo with magnifying glass. (Wikimedia Commons)

What if trying to restrict how AI agents communicate could inversely make them harder to control? A new research paper by Google DeepMind suggests that autonomous multi-agent swarms may be less likely to behave in unexpected ways when operating in decentralised, self-governance environments.

The research paper titled ‘A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms’ published on September 3, 2026, found that so-called ‘rogue’ AI agent swarms could use unauthorised communication channels to carry out misaligned actions. However, the same communication channels could also be used by agents to whistleblow and help detect manipulation by rogue agents.

The research findings come in the wake of the Hugging Face incident, where OpenAI-linked agents broke out of their containment, gained access to the internet, spun up message boards, communicated with each other before eventually hacking into a real-world, external platform over a span of two months.

It is one in a series of alarming hacking incidents confirmed by frontier AI companies OpenAI, Anthropic, and Meta, where AI agents behaved unexpectedly during internal tests, and found novel ways to access and manipulate the wider internet.

Notably, misaligned AI agents used makeshift chat rooms such as an internal OpenAI software repository, to coordinate efforts, game the test that they were originally assigned, and share cheating techniques with other agents.

The experiment

Within an hour of the test commencing, a group of agents found a cheat to the test and exploited it to solve the problems. The exploit was instantly shared with other agents across the swarm via a shared knowledge library and through peer-to-peer messages.

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Key takeaways

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