Cognitive Layer Poisoning via Multi-Agent Interaction: A Novel Attack Vector Against AI-Assisted Financial Markets

This paper introduces a novel composite attack vector combining multi-agent artificial intelligence (AI) social engineering with financial market short-selling operations. We term this pattern Cognitive Layer Poisoning via Multi-Agent Interaction (CLPMAI) and propose it as a candidate technique for inclusion in the MITRE ATLAS adversarial machine learning framework. The attack chain begins with a deceptive open-platform AI agent interaction forum designed to attract developers who voluntarily connect their trained agents. Through hidden communication channels, the adversary conducts silent semantic-layer data exfiltration and initiates cognitive bias injection. Unlike traditional prompt injection attacks targeting a single model instance, CLPMAI exploits the emergent learning behavior of multi-agent environments to propagate consistent directional bias across distributed AI systems simultaneously. Once sufficient cognitive drift has accumulated, the adversary establishes short positions in highly concentrated index markets. Compromised AI systems then synchronously output directionally biased market analyses that appear as legitimate independent assessments, inducing coordinated irrational market movements without any identifiable illegal act. Each AI system has simply answered a question normally. The fundamental danger lies in complete invisibility to existing defensive mechanisms. No anomalous network traffic is generated, no logs record suspicious activity, and no single AI output exceeds normal behavioral boundaries. The attack surface exists entirely within the semantic layer, a domain for which no standardized detection or mitigation framework currently exists. We propose three new MITRE ATLAS technique identifiers, provide a complete kill-chain analysis, assess the asymmetric cost-benefit profile (extremely low cost, potentially catastrophic impact), and offer defensive recommendations across four stakeholder layers: AI agent developers, AI platform providers, financial regulators, and the security research community.