All news with #mistral tag

Protecting LLM Chats from the Whisper Leak Attack Today

🛡️ Recent research shows the “Whisper Leak” attack can infer the topic of LLM conversations by analyzing timing and packet patterns during streaming responses. Microsoft’s study tested 30 models and thousands of prompts, finding topic-detection accuracy from 71% to 100% for some models. Providers including OpenAI, Mistral, Microsoft Azure, and xAI have added invisible padding to network packets to disrupt these timing signals. Users can further protect sensitive chats by using local models, disabling streaming output, avoiding untrusted networks, or using a trusted VPN and up-to-date anti-spyware.

Microsoft Reveals Whisper Leak: Streaming LLM Side-Channel

🔒 Microsoft has disclosed a novel side-channel called Whisper Leak that can let a passive observer infer the topic of conversations with streaming language models by analyzing encrypted packet sizes and timings. Researchers at Microsoft (Bar Or, McDonald and the Defender team) demonstrate classifiers that distinguish targeted topics from background traffic with high accuracy across vendors including OpenAI, Mistral and xAI. Providers have deployed mitigations such as random-length response padding; Microsoft recommends avoiding sensitive topics on untrusted networks, using VPNs, or preferring non-streaming models and providers that implemented fixes.

Whisper Leak: Side-Channel Attack on Remote LLM Services

🔍 Microsoft researchers disclosed "Whisper Leak", a new side-channel that can infer conversation topics from encrypted, streamed language model responses by analyzing packet sizes and timings. The study demonstrates high classifier accuracy on a proof-of-concept sensitive topic and shows risk increases with more training data or repeated interactions. Industry partners including OpenAI, Mistral, Microsoft Azure, and xAI implemented streaming obfuscation mitigations that Microsoft validated as substantially reducing practical risk.