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Low 34 Bitcoin

Introduce Payment Dummy Hop parsing mechanism

Public commit record

What the developer wrote

Authored by shaavan

45/100 · Thin
Introduce Payment Dummy Hop parsing mechanism
✓ Descriptive subject✓ Names a concrete action or component! No meaningful explanatory body
The short version

What changed, and why it matters

This commit adds support for 'dummy hops' in Lightning payment routes. These are fake routing steps used to pad and hide the real path of a payment. The change lets a node strip off one of these padding layers locally and continue processing the payment, instead of trying to forward it over a real channel. It is a feature addition, not a clear-cut security fix, but it touches sensitive onion-routing code where mistakes could let an attacker bypass fees, routing checks, or forward payments incorrectly.

Recommended action

Treat this as a high-sensitivity feature commit rather than a confirmed vulnerability. Reviewers should verify that dummy hops cannot be used to skip trampoline or real-channel validation, that re-queued HTLCs preserve all required authentication fields, that amount/CLTV constraints are strictly enforced before peeling, and that the debug_assert! fallbacks in release builds do not allow dummy hops to reach HTLC processing silently. No immediate patch is indicated, but careful code review and targeted fuzzing of the new Dummy path are warranted.

Security signals we found

01

New network message variant handling (InboundOnionPayload::Dummy / InboundOnionDummyPayload)

02

Local re-queuing of reconstructed UpdateAddHTLC after peeling a dummy hop

03

Addition of defensive debug_assert! guards to prevent dummy hops from entering normal HTLC forwarding

04

Changes to blinded path advancement and onion decode logic

05

No explicit CVE, advisory, or vendor security statement present in the commit or supplied references

Risk score

Why this scored 34/100

Our methodology →
Potential impact 8/30
Exploitability 5/25
Stealth signal 6/15
Affected reach 7/15
Confidence 5/10
Evidence quality 3/5
Human-validated context

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