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Low 30 Bitcoin

xpay: add a CLTV shadow for single non-blinded paths.

Public commit record

What the developer wrote

Authored by Rusty Russell

73/100 · Adequate
xpay: add a CLTV shadow for single non-blinded paths.

BOLT 7 recommends this. pay did it: in fact, pay would also add sats,
but that's much more difficult and fraught, so only do CLTV.

Changelog-Added: Protocol: `xpay` now uses shadow CLTV additions to help mask final destination as per BOLT 7.
Signed-off-by: Rusty Russell <rusty@rustcorp.com.au>
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides detailed explanatory context
The short version

What changed, and why it matters

This commit adds a privacy feature to Core Lightning's xpay plugin. When making a payment over a single non-blinded path, xpay can now add extra CLTV (timelock) blocks as a 'shadow' to make it harder for an intermediate node to tell that it is the final hop. This follows a BOLT 7 recommendation and mirrors behavior already present in the older 'pay' plugin. The change is purely additive and opt-in via a hidden developer flag.

Recommended action

No immediate action required. This is a defensive privacy improvement. Operators interested in enhanced payment privacy over single non-blinded paths can experiment with the hidden `dev_use_shadow` option, understanding it is a developer feature. Reviewers should verify the CLTV shadow calculation does not cause payment failures due to excessive timelock deltas and that the hidden flag cannot be accidentally enabled in production.

Security signals we found

01

Privacy enhancement for single non-blinded payment paths

02

CLTV shadow added to final hop to obscure final destination

03

New hidden RPC parameter `dev_use_shadow` defaults to false

04

BOLT 7 recommendation implemented

05

No amount shadow added; only CLTV shadow

06

Generated schema/proto/model files updated consistently

Risk score

Why this scored 30/100

Our methodology →
Potential impact 3/30
Exploitability 2/25
Stealth signal 8/15
Affected reach 5/15
Confidence 8/10
Evidence quality 4/5
Human-validated context

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