CVE-2025-69893 in One
Summary
by MITRE • 04/14/2026
A side-channel vulnerability exists in the implementation of BIP-39 mnemonic processing, as observed in Trezor One v1.13.0 to v1.14.0, Trezor T v1.13.0 to v1.14.0, and Trezor Safe v1.13.0 to v1.14.0 hardware wallets. This originates from the BIP-39 standard guidelines, which induce non-constant time execution and specific branch patterns for word searching. An attacker with physical access during the initial setup phase can collect a single side-channel trace. By utilizing profiling-based Deep Learning Side-Channel Analysis (DL-SCA), the attacker can recover the mnemonic code and subsequently steal the assets. The issue was patched.
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Analysis
by VulDB Data Team • 04/14/2026
The vulnerability described in CVE-2025-69893 represents a critical side-channel weakness in the implementation of BIP-39 mnemonic processing within several Trezor hardware wallet models. This flaw specifically affects versions v1.13.0 through v1.14.0 of Trezor One, Trezor T, and Trezor Safe devices, creating a significant security risk during the initial setup phase when users input their mnemonic phrases. The vulnerability stems from the inherent design of the BIP-39 standard which mandates specific word searching algorithms that do not maintain constant-time execution characteristics. This non-constant time behavior creates observable differences in execution patterns that can be exploited through side-channel analysis techniques.
The technical implementation of BIP-39 word verification processes introduces predictable branch patterns and timing variations that manifest as side-channel signals during cryptographic operations. These timing discrepancies occur when the hardware wallet processes user input to validate mnemonic phrases against the standard wordlist, creating measurable differences in execution time and power consumption that correlate directly to the specific words being processed. The vulnerability is particularly concerning because it operates during the initial device setup phase when physical access is typically granted to users, making it susceptible to attack by adversaries who can observe the device's behavior during this critical window.
The operational impact of this vulnerability extends far beyond simple information disclosure, as successful exploitation allows attackers to completely compromise user assets by recovering the complete mnemonic code. The attack methodology leverages profiling-based Deep Learning Side-Channel Analysis techniques that can extract meaningful information from a single side-channel trace collected during the setup process. This approach represents a sophisticated form of side-channel attack that combines machine learning algorithms with traditional power analysis methods to reverse engineer cryptographic operations. The successful recovery of the mnemonic code enables attackers to gain full control over the associated cryptocurrency wallets and assets, making this vulnerability particularly dangerous for users who store significant digital assets on these devices.
Security researchers have identified this issue as aligning with CWE-310, which addresses cryptographic weaknesses and side-channel attacks, and it demonstrates characteristics consistent with ATT&CK technique T1552.001 for unsecured credentials and T1059.001 for command and scripting interpreter usage in exploitation scenarios. The vulnerability's exploitation requires physical access during setup, which aligns with ATT&CK's emphasis on physical security breaches and the importance of protecting against side-channel attacks in hardware security modules. The patching of this vulnerability in subsequent firmware versions demonstrates the critical nature of addressing such side-channel weaknesses, as they represent persistent threats that can remain exploitable for extended periods if not properly addressed. This case highlights the importance of constant-time algorithm implementations in cryptographic systems and the necessity of thorough security testing that includes side-channel analysis for hardware security devices.