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CVE-2022-39251 is a critical severity vulnerability discovered in the Matrix SDK bundled with Thunderbird and other Matrix clients. The vulnerability was discovered by researchers from Royal Holloway University London, University of Sheffield, and Brave Software, and was disclosed on September 28, 2022. The vulnerability affects matrix-js-sdk versions below 19.7.0 and impacts applications using this SDK including Element, Beeper, Cinny, SchildiChat, Circuli, and Synod.im (Matrix Blog).
The vulnerability is a protocol confusion bug where the system incorrectly accepts to-device messages encrypted with Megolm instead of Olm, attributing them to the Megolm sender rather than the actual sender. This implementation flaw allows attackers to fake the trusted sender of to-device messages. The vulnerability received a critical severity rating due to its potential impact on message encryption and authentication (GitHub Advisory).
An attacker cooperating with a malicious homeserver can construct messages that legitimately appear to have come from another person without any indication such as a grey shield. Additionally, sophisticated attackers could perform targeted attacks to send fake to-device messages appearing to originate from another user, potentially allowing them to inject key backup secrets during self-verification and make targeted devices use malicious key backups spoofed by the homeserver (GitHub Advisory, Matrix Blog).
The vulnerability was patched in matrix-js-sdk version 19.7.0. The fix includes modifications to only accept Olm-encrypted to-device messages and additional security checks: discarding cleartext m.roomkey, m.forwardedroomkey and m.secret.send todevice messages, discarding secrets received from untrusted devices, and ensuring key backups are only usable if they have a valid signature from a trusted device. Users were advised not to verify new logins using emoji/QR verification methods until patched and to prefer verifying with security passphrases (GitHub Advisory).
Source: This report was generated using AI
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