AgentDoxx: Agentic Re-identification of Anonymized Text with Web Search
As Large Language Models (LLMs) gain tool use capabilities such as web search, they can retrieve and cross-reference public information, creating privacy risks beyond memorization. One manifestation is re-identification: linking an anonymized interview transcript to a named individual. Yet without ground-truth identities, the coverage of such attacks and the protection offered by a defense cannot be reliably measured. We introduce AgentDOXX, an evaluation suite of 822 synthetic interview transcripts grounded in public information about real individuals with known identities. We evaluate fifteen configurations of open-weight and proprietary models, isolating the effect of web search, and a...
| Authors | Jianing Wen, Tianshi Li |
|---|---|
| Primary category | cs.CR |
| Published | 4 October 2026 |
| Last updated at source | 4 October 2026 |
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