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Informational 21 Bitcoin

feat(core): improve kerning data structure

Public commit record

What the developer wrote

Authored by tychovrahe

57/100 · Thin
feat(core): improve kerning data structure

[no changelog]
✓ 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 refactors how font kerning (fine-tuning space between letter pairs) is stored and looked up in the Trezor firmware. It changes the data structure from a flat list of triplets to a two-level index/pairs table, adds a Rust feature flag to enable or disable kerning, and updates the font generation tools to extract kerning from modern OpenType GPOS tables. The changes are primarily a data-format and build-tooling improvement, not a fix for a known vulnerability. The commit does not describe itself as security-related.

Recommended action

Treat as a routine feature/refactor commit. Review the new `KerningTable::new` parser for any edge cases in `align_to` usage and ensure the Python serializer and Rust parser agree on endianness, padding, and maximum counts. No urgent security action is indicated by the diff itself.

Security signals we found

01

New binary parsing code in `blob.rs` uses `unsafe { align_to::<...>() }` with `#[repr(C, packed)]` structs and validates prefix/suffix alignment and byte counts before accepting the table.

02

Validation now rejects V0/V1 blobs that contain unexpected trailing kerning payload, and only accepts kerning for V2 blobs.

03

Input bounds are checked against explicit `index_count`, `pair_count`, and `data_bytes` fields; mismatches return `INVALID_TRANSLATIONS_BLOB`.

04

Kerning values are constrained to signed 8-bit range during Python serialization.

05

Codepoint values are constrained to 16-bit range during Python serialization.

06

The commit is tagged `[no changelog]` and the changelog fragment describes it as a feature ('Introduced font kerning'), not a security fix.

Risk score

Why this scored 21/100

Our methodology →
Potential impact 2/30
Exploitability 2/25
Stealth signal 3/15
Affected reach 4/15
Confidence 7/10
Evidence quality 3/5
Human-validated context

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