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Low 31 Bitcoin

Serialise ChannelMonitors and send them over inside Peer Storage

Public commit record

What the developer wrote

Authored by Aditya Sharma

85/100 · Strong
Serialise ChannelMonitors and send them over inside Peer Storage

Create a utililty function to prevent code duplication while writing ChannelMonitors.
Serialise them inside ChainMonitor::send_peer_storage and send them over.

Cfg-tag the sending logic because we are unsure of what to omit from ChannelMonitors stored inside
peer-storage.
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides detailed explanatory context✓ Explains rationale or failure mode
The short version

What changed, and why it matters

This commit adds an experimental feature (gated behind a special compile-time flag) that serializes sensitive Lightning channel backup data and sends it to peers for storage. The code itself is a work-in-progress: the authors explicitly note they are unsure which sensitive fields should be omitted from the backup, and the feature is disabled by default. There is no direct vulnerability in the diff, but it introduces a new attack surface where a bug or misconfiguration could leak channel secrets to counterparty peers.

Recommended action

Treat this as a feature-in-development rather than an immediate vulnerability. Reviewers should ensure the final peer-storage serialization omits private key material, revocation secrets, and any data that could allow a counterparty to steal funds or violate privacy. Keep the feature cfg-gated and behind thorough tests until the field-selection TODO is resolved.

Security signals we found

01

New serialization path for ChannelMonitor data shared with peers

02

Feature explicitly flagged as experimental/incomplete by vendor comments

03

Potential over-sharing of sensitive channel state if fields are not later restricted

04

Encryption is applied before network transmission, reducing passive-leak risk

05

No input validation or peer-authentication changes visible in this diff

Risk score

Why this scored 31/100

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

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