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Low 32 Bitcoin

chore(trezorlib): fix `BootloaderV2Image` handling in `firmware_headers.py`

Public commit record

What the developer wrote

Authored by M1nd3r

62/100 · Adequate
chore(trezorlib): fix `BootloaderV2Image` handling in `firmware_headers.py`

[no changelog]
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Uses a recognizable type or scope! No meaningful explanatory body
The short version

What changed, and why it matters

This commit fixes how Trezor's Python library validates signatures for a new bootloader image format (BootloaderV2). Before the fix, the code ignored the signature bitmask and simply checked every signature against every public key in order. This could let an invalid or mismatched signature slip through, or cause validation to fail incorrectly. The patch makes the library read the bitmask, count signatures correctly, and only verify the signatures the image actually claims to have signed with. It also adds a missing signature-status line to the printed header. The change is in developer/CLI tooling, not the device firmware itself, so a direct attack on a real device is unlikely, but the library is used to inspect and validate firmware files.

Recommended action

Treat as a low-to-moderate security hardening fix. Update any local installations of trezorlib that inspect or validate BootloaderV2 images. No emergency device-side action is needed because the fix is in host-side Python tooling. If the buggy version was used to validate firmware in an automated CI/CD pipeline, re-validate any BootloaderV2 images processed by the old code.

Security signals we found

01

Signature verification logic corrected to enforce bitmask alignment

02

Added length/popcount validation for signature arrays

03

Missing signature status reporting added for BootloaderV2Image header output

04

Developer-tooling library used for firmware inspection/validation

Risk score

Why this scored 32/100

Our methodology →
Potential impact 8/30
Exploitability 6/25
Stealth signal 4/15
Affected reach 5/15
Confidence 6/10
Evidence quality 3/5
Human-validated context

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