Researchers Reveal LLM Side-Channel Exfiltration Methods

On February 17, 2026, researchers published three papers demonstrating side-channel attacks that infer user prompts and extract data from encrypted LLM traffic and speculative decoding. Across open-source and production systems they report classification/identification accuracies of 75–99% and over 98% AUPRC, recover 5–20% of target conversations, and exfiltrate datastore tokens at rates exceeding 25 tokens/sec. They evaluate mitigations like padding and batching, but none fully eliminate leakage.
Scoring Rationale
Strong academic demonstrations across production LLMs justify high impact, despite mitigations proving partial and not fully protective.
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