Researchers have released “Whisper Leak,” a toolkit demonstrating a side-channel attack that can infer the topics of encrypted AI chatbot conversations in real-time. By analyzing the unique packet sizes and timing of streamed AI tokens, attackers can “fingerprint” and identify sensitive queries even over TLS.
Business Impact
This erodes the privacy guarantee of encryption for AI interactions. ISPs, nation-states, or eavesdroppers on public Wi-Fi could potentially identify when employees are consulting AI about sensitive topics like M&A, legal issues, or proprietary R&D.
Why It Happened
AI models typically “stream” responses token-by-token for speed. This creates distinct traffic patterns that act as a unique signature for different types of content, which can be recognized by machine learning models even without decrypting the data.
Recommended Executive Action
Advise employees to use corporate VPNs when accessing AI tools from untrusted networks to add noise to traffic patterns. Press AI vendors for native mitigations like traffic padding to obscure these side-channel leaks.
Hashtags: #AI #Privacy #Encryption #SideChannel #WhisperLeak #CyberSecurity #InfoSec #DataProtection