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Low 26 Bitcoin

multi: enable closed-channel tombstones on KV-SQL backends

Public commit record

What the developer wrote

Authored by ziggie

83/100 · Strong
multi: enable closed-channel tombstones on KV-SQL backends

Wire OptionTombstoneClosedChannels for sqlite and postgres backends in
config_builder.go. bbolt keeps the synchronous one-shot close path
unchanged.

Add UsesClosedChanTombstones() to the integration test harness so
backend-symmetric tests can skip post-close assertions about deleted
forwarding-package or revocation-log state — that state is intentionally
preserved on tombstone backends until the upcoming native-SQL
channel-state migration reclaims it. Update testWipeForwardingPackages
to honor the new predicate while still exercising the close flow on
both backend families.
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides detailed explanatory context✓ Mentions testing or verification
The short version

What changed, and why it matters

This change adjusts how LND closes payment channels when using SQLite or Postgres database backends. Instead of immediately deleting all channel-related data in one big operation, it marks the channel as closed with a 'tombstone' and leaves the old data in place temporarily. This avoids long database lockups during channel closure. It is a performance and reliability improvement, not a fix for an exploitable vulnerability.

Recommended action

Treat as a normal code review / reliability change. Verify that tombstoned closed-channel data is eventually reclaimed by the planned native-SQL migration and that backup, privacy, and operational runbooks account for the new retention behavior on sqlite/postgres backends. No emergency security action is indicated by this commit alone.

Security signals we found

01

Behavioral change in channel close state cleanup

02

Intentional retention of closed-channel data on sqlite/postgres backends

03

Potential for data retention expectations to differ by backend

04

No input validation, cryptographic, or authorization changes observed

Risk score

Why this scored 26/100

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

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