SOURCE-LINKED INTELLIGENCE

Agents That Edit Documents: Measuring Agentic PDF Forgery Against a Non-Agentic Control

arXiv · AI, language, vision and robotics · article · Sep 20, 2026 · UTC

AI agents that carry a multi-step computer task through on their own became ordinary tools in the past year, and the same autonomy is available to anyone whose task is harmful. We ask what that means for a relying party -- an insurer, a lender, an auditor -- whose evidence is a filed PDF. AgentForge-Bench measures how reliably an off-the-shelf coding agent, driving one of seven open-weight models with a shell and the stock Python PDF stack, alters one dollar amount, date or address in a real filed financial document from a single sentence of intent, graded by rules rather than by a model. Acro

Read original source ↗ Open in workspace

recordType

paper

region

Global