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Informational 14 Bitcoin

test: fix interface_ipc.py template destruction

Public commit record

What the developer wrote

Authored by Ryan Ofsky

100/100 · Strong
test: fix interface_ipc.py template destruction

Use context managers to destroy block templates. Previously, block templates
were not being destroyed before disconnecting because the destroy coroutines
were called but never awaited. It's not necessary to explicitly destroy the
templates since they will get garbage collected asynchronously, but it's good
to destroy them to make the test more predictable, and to make the destroy
calls that are present actually do something.

This change also removes `await waitnext` expressions without changing
behavior, because the previous code was misleading about what order waitNext
calls were executed.

This change is easiest to review ignoring whitespace.

Co-authored-by: Sjors Provoost <sjors@sprovoost.nl>
✓ Descriptive subject✓ Names a concrete action or component✓ Uses a recognizable type or scope✓ Provides detailed explanatory context✓ Explains rationale or failure mode✓ Mentions testing or verification
The short version

What changed, and why it matters

This is a test-only cleanup in Bitcoin Core's functional test suite. It fixes how temporary 'block template' objects are cleaned up during an automated test by using Python context managers. The old code called destroy routines but forgot to 'await' them, so cleanup happened later by garbage collection instead of immediately. There is no change to the actual Bitcoin node software, no security vulnerability in production code, and no attacker-accessible behavior changed.

Recommended action

No security action required. Treat as normal test-quality improvement; review and merge through standard process.

Security signals we found

01

No production code changed

02

Test-only async cleanup fix

03

No consensus, P2P, wallet, RPC, or cryptographic changes

04

No memory safety, input validation, or authorization changes

Risk score

Why this scored 14/100

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

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