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Informational 19 Bitcoin

Revert "Remove `lazy` flag from `{KVStore,KVStoreSync}::remove`"

Public commit record

What the developer wrote

Authored by Matt Corallo

81/100 · Strong
Revert "Remove `lazy` flag from `{KVStore,KVStoreSync}::remove`"

This reverts commit 561da4cfb8cd27085b124ae1af96a8745f7f31dc.

A user pointed out, when looking to upgrade to LDK 0.2, that the
`lazy` flag is actually quite important for performance when using
a `MonitorUpdatingPersister`, especially in synchronous persistence
mode.

Thus, we add it back here.

Fixes #4188
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides detailed explanatory context✓ Links an issue, advisory, or supporting reference
The short version

What changed, and why it matters

This commit restores a `lazy` flag on the `remove` methods of LDK's key-value store traits. When `lazy=true`, deletions can be batched or delayed to reduce disk I/O, but they may not survive a crash. The change is framed by the authors as a performance fix, not a security fix. It does not introduce an exploitable vulnerability on its own; it gives callers explicit control over durability versus speed.

Recommended action

Review every production caller that passes `lazy=true` to confirm the data is genuinely safe to re-persist or ignore after a crash. Ensure that lazy removals are eventually flushed or replayed so that disk state cannot diverge permanently from in-memory state. Consider adding tests that simulate crashes after lazy removes to verify recovery behavior.

Security signals we found

01

API reintroduces a lazy deletion mode that may lose removes across crashes

02

Documentation explicitly warns that lazy removes weaken atomicity guarantees

03

Internal callers mark stale channel-monitor updates and removed monitors as lazy-removable

04

No bounds checking or audit of caller lazy=true usage is added in this commit

Risk score

Why this scored 19/100

Our methodology →
Potential impact 2/30
Exploitability 0/25
Stealth signal 0/15
Affected reach 5/15
Confidence 8/10
Evidence quality 4/5
Human-validated context

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