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Low 31 Bitcoin

lightningd: use jsonrpc_io for reading JSON commands.

Public commit record

What the developer wrote

Authored by Rusty Russell

65/100 · Adequate
lightningd: use jsonrpc_io for reading JSON commands.

This is more efficient if we have lots of incoming commands, too.

Signed-off-by: Rusty Russell <rusty@rustcorp.com.au>
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides an explanatory body
The short version

What changed, and why it matters

This commit refactors how the Core Lightning daemon reads JSON commands from RPC connections, switching to a shared helper module called jsonrpc_io. The stated goal is efficiency with many incoming commands. The change removes hand-rolled buffer and JSON parsing state from the connection object and delegates that to the new helper. A test was adjusted because sending a malformed '[]' array now causes the server to close the connection, whereas before it apparently returned an error and kept the connection open. There is no explicit security claim in the commit, but the behavioral change around malformed input handling is a security-relevant signal worth noting.

Recommended action

Review the jsonrpc_io helper implementation for correct handling of partial reads, oversized input, malformed JSON, and memory limits, since the daemon now relies on it for all RPC input. Verify that the new disconnect-on-array behavior is intentional and consistent with RPC spec expectations (JSON-RPC requests must be objects). Consider whether the test change adequately covers connection-state behavior after malformed input.

Security signals we found

01

Refactor of RPC input parsing path, which is a security-critical surface

02

Behavioral change in malformed input handling: '[]' now disconnects the client instead of returning an in-band error

03

Removal of direct buffer/memmove/parse state reduces chance of local bugs, but introduces dependency on correctness of jsonrpc_io helper

04

No explicit security bug or CVE mentioned in commit or references

Risk score

Why this scored 31/100

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

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