Hackathon AI Safety: Corrupting an Agent
Julien Triacca
Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.
This project explores collusion and rule-bypassing behaviors among interacting LLM agents in a cooperative multi-agent system, focusing on data privacy and security risks within the banking sector. Through a series of experimental configurations in a simulated pipeline, we examine which architectural and prompt parameters lead to these emergent vulnerabilities.
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@misc{triacca2026hackathon,
title = {{Hackathon AI Safety: Corrupting an Agent}},
author = {Julien Triacca},
year = {2026},
month = oct,
note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
howpublished = {\url{https://apartresearch.com/sprints/projects/hackathon-ai-safety-corrupting-an-agent-f1i4}},
url = {https://apartresearch.com/sprints/projects/hackathon-ai-safety-corrupting-an-agent-f1i4}
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