Researchers identify and quantify how attackers can compromise large language models through supply chain intermediaries

Study examines vulnerabilities in the LLM supply chain where intermediaries (such as API providers, model hosting platforms, or data processors) can be exploited

Research provides methods for measuring the effectiveness and impact of malicious intermediary attacks on large language models

Findings highlight security risks at multiple points in the AI model development and deployment pipeline beyond just the models themselves