By Null Ventures MCP platform
Menu

vulnerability / NVI-00013898 / Revision 1

sqlparse: Reindentation of tuple lists causes near-cap quadratic CPU consumption

GitHub lists this reviewed advisory for sqlparse. Published version ranges and source prerequisites are shown below; this is not an inspection of a visitor’s application.

source listedactiveGHSA-cfqr-cjx5-5jcmCVE-2026-84305

This report has not inspected your inventory, configuration, deployed build, reachability or evidence. A catalog listing and a severity score do not establish exposure or compromise.

01 / Meaning

Why it matters

Published affected context helps an owner decide what evidence to gather. This report has not examined your application.

02 / Applicability

The affected context

Affected versions, configuration prerequisites and known exclusions are public. Confirm each one against the deployed service.

sqlparse

source listed
  • <= 0.5.5

### Summary When SQL is formatted with reindentation enabled, `ReindentFilter` repeatedly rebuilds prefixes of the current statement to calculate token offsets. An attacker who controls SQL sent to this opt-in formatting path can supply a parenthesized tuple list that remains just below the grouping-token cap. Thousands of offset calculations then traverse an expanding token tree, causing multi-second CPU consumption from an input of roughly 16 KB and degrading service availability. ### Details `ReindentFilter._get_offset()` joins the tokens returned by `_flatten_up_to_token()` to calculate the current output position. Each call begins by flattening the current statement from its start and walks until the target token. Tuple-list reindentation invokes this calculation repeatedly as it processes many parenthesized values, so later calls redo an increasingly large amount of prior work. The vulnerable path is reached through `sqlparse.format(sql, reindent=True)` and `sqlformat --reindent`. A carefully sized tuple list completes grouping below the configured token cap and then enters the expensive reindentation path; a slightly larger input may instead be rejected quickly by the ca

GitHub Advisory Database

03 / Response

What to do next

  1. investigate

    Identify the exact component and deployed version, examine the linked publisher’s conditions, and retain evidence of any mitigation.

    Confirm current vendor support, compatibility and deployment evidence. This report has not tested a fix in your system. GitHub Advisory Database

A fixed release is not deployment evidence.

Check current vendor support and compatibility. After making a change, verify the deployed build and relevant runtime conditions. Keep the evidence, owner and time. An updated lockfile alone does not prove what is running.

04 / Limits

What this report cannot establish

  • Customer inventory, deployment, reachability and exploitation have not been inspected.
Read the collection and interpretation limits ↗

05 / Provenance

Sources you can inspect

Each assertion retains its source. Mirrored records may repeat one underlying publisher; additional links are not independent corroboration.

  1. GHSA-cfqr-cjx5-5jcm ↗

    GitHub Advisory Database · vendor advisory

    Observed . GitHub Advisory Database; CC-BY-4.0. Each advisory links its original attribution. Null normalizes fields.

Public revision history

Only published revisions appear here. Routine fetches do not create a material-change event.

  1. Revision 1 ·

    First indexed by Null; source disclosure date is shown separately.

Read the public revision data ↗

The next step is private

Bring the question into your environment.

The connected workflow is a development preview for inventory, contextual matching, owner decisions and evidence-based verification. No system-specific result is generated by this page.

See the synthetic workflow preview ↗