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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score60

Google DeepMind study tests prompt injection defenses with multiple AI agentsMachine translation

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Google DeepMind researchers built an attacker system with eight teams of AI agents that test prompt injections, share notes, and improve their attempts. Across 100 tool-use tasks, the attacker's goal was only to trigger one random, harmless tool call. With up to 320 tries, the strongest attacker succeeded on 34% of tasks against Gemini 4 Argon, described in the source as the most robust model.

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New Google DeepMind paper shows prompt injection is not solved, since a swarm of strong AI attacker agents still tricks even the best-defended models.

Prompt injection means hiding instructions in data an AI agent reads, like a tool result, to make it act for the attacker. Human red-teaming attacks now almost never work on recent Gemini models, so the problem can look solved.

They built Agentic Optimizer, 8 teams of AI agents that test injections, share notes, and build on each other's best attempts. They tested it on 100 tool-use tasks where the attacker only wanted one random, harmless tool call.

With up to 320 tries, the strongest attacker beat Gemini 4 Argon, the most robust model, on 34% of tasks. Open-weight Kimi K3, GLM-5.3, and DeepSeek-V4.1-Flash resisted only 1% of tasks.

Source: Rohan Paul · x.com

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