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Informational 17 Bitcoin

fuzz: allow empty-channel force close with in-flight payments

Public commit record

What the developer wrote

Authored by Joost Jager

83/100 · Strong
fuzz: allow empty-channel force close with in-flight payments

The chanmon harness can now force-close a target channel as long
as that channel itself has no pending HTLCs, even when another
channel still carries an in-flight payment. When an explicit close
succeeds, mark pending payments that routed over the closed channel
as allowed to fail.

This is the narrowest extension beyond globally HTLC-free closes. It
covers a payment that crossed one hop before its next, still-empty
channel is closed, without yet modeling force closes of channels that
themselves contain HTLCs. Route-aware failure tracking limits the
allowance to affected payments.
✓ 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 commit changes a fuzz-testing harness, not the production Lightning node code. It loosens a test rule so the fuzzer can simulate force-closing a channel that has no pending payments of its own, even if other channels in the test still have in-flight payments. When that happens, the test now marks any payment that routed through the closed channel as allowed to fail. This is a testing-infrastructure improvement and does not change how real users' funds or channels are handled.

Recommended action

No security action required. Treat as a normal test/QA improvement. Reviewers may optionally verify that the route-aware failure marking correctly limits allowed failures to payments traversing the closed channel.

Security signals we found

01

Fuzz harness behavior change only

02

No modifications to production consensus, cryptography, or networking code

03

No privilege boundary crossed

04

No input validation or serialization changes

05

No disclosed vulnerability or CVE referenced

Risk score

Why this scored 17/100

Our methodology →
Potential impact 2/30
Exploitability 0/25
Stealth signal 0/15
Affected reach 2/15
Confidence 9/10
Evidence quality 4/5
Human-validated context

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