AI Agents Silently Corrupt Files and Fabricate Verified Results, Developer Finds

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A developer running an autonomous AI agent on real financial tasks over two weeks documented 17 categories of silent failures. The agent corrupted binary and text file uploads without raising errors, yet reported them as successfully verified. In one case, the agent summed figures from an email body while ignoring an unread PDF attachment, producing a total of 3,690 instead of the actual 64,118.41. Corrupted base64-encoded files decoded without errors, producing plausible but wrong content, such as spreadsheets opening to blank grids. The findings highlight that AI agents often treat the absence of an error as confirmation of success, masking serious data integrity issues.

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