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Moderate 63 Bitcoin

fix: harden parsing and signing against malformed input

Public commit record

What the developer wrote

Authored by Aymeric Robert

85/100 · Strong
fix: harden parsing and signing against malformed input

Found by the fuzzing harness added in this PR:

- signed left shift computing the Merkle tree traversal mask
- zero-length memmove when merging parser buffers
- out-of-range integer conversions and a signed/unsigned comparison in PSBT signing
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Uses a recognizable type or scope✓ Provides detailed explanatory context
The short version

What changed, and why it matters

This commit fixes several low-level programming bugs in Ledger's Bitcoin app that were found by automated fuzzing. The bugs include a dangerous bit shift, a pointless memory move with zero bytes, and incorrect comparisons between signed and unsigned numbers when parsing transaction data and signing PSBTs. Most fixes are defensive hardening, but one change moves a sanity check earlier so the app rejects absurdly large input amounts before adding them up, which could prevent an overflow. The commit does not claim these are directly exploitable attacks, but they remove undefined behavior that could in theory lead to crashes or incorrect signing.

Recommended action

Treat as a security-hardening fix and include in the next release. Review whether the moved BITCOIN_TOTAL_SUPPLY check fully prevents all overflow paths in inputs_total_amount accumulation, and continue fuzzing the affected parsers/signers. No immediate CVE is required unless a reproducible exploit is demonstrated.

Security signals we found

01

Undefined behavior fixes (signed left shift, signed/unsigned comparison, out-of-range integer conversion)

02

Fuzzing harness found issues

03

Input amount overflow hardening moved before accumulation

04

Merkle tree traversal mask hardening

05

Memory operation zero-length guard

Risk score

Why this scored 63/100

Our methodology →
Potential impact 18/30
Exploitability 14/25
Stealth signal 8/15
Affected reach 12/15
Confidence 7/10
Evidence quality 4/5
Human-validated context

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