AgentProv: Auditing Agentic LLM API Providers via Tool-use Policy Probes
Researchers demonstrate that LLM API providers can be audited for silent model substitution by probing tool-use behaviour rather than text output alone.
Summary written by editorial AI · Source link below
arXiv:2609.00052v1 Announce Type: new Abstract: Commercial LLM APIs advertise a specific foundation model, but the served backbone may be silently substituted, quantized, or wrapped, for example to save deployment costs. All existing audits decide backbone identity from the text-output channel, which is structurally fragile for agentic APIs because modern serving stacks (OpenAI, Anthropic, Gemini, Cloudflare Workers AI, LangGraph) discard text and expose only structured actions when the model c
Editorial Analysis
Enterprises paying premium for specific foundation models risk receiving cheaper substitutes — tool-use auditing offers an independent verification path.
Include tool-use behavioural checks in vendor contract compliance testing for commercial LLM API subscriptions.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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