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PatchSiren cyber security CVE debrief

CVE-2026-46374 sqlfluff CVE debrief

CVE-2026-46374 is a high-severity vulnerability in SQLFluff, a modular SQL linter and auto-formatter. The vulnerability allows an untrusted user to submit a malicious long query to trigger a Denial of Service (DoS) through resource exhaustion. This issue affects deployments where untrusted users can provide SQL queries to be linted. The vulnerability has been patched in version 4.2.0.

Vendor
sqlfluff
Product
Unknown
CVSS
HIGH 7.5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-06-09
Original CVE updated
2026-06-12
Advisory published
2026-06-09
Advisory updated
2026-06-12

Who should care

Users of SQLFluff, especially those who deploy it in environments where untrusted users can provide SQL queries to be linted.

Technical summary

SQLFluff is vulnerable to a Denial of Service (DoS) attack through resource exhaustion. An untrusted user can submit a malicious long query to any application using the parser, causing a DoS. This issue has been patched in version 4.2.0.

Defensive priority

High

Recommended defensive actions

  • Upgrade to SQLFluff version 4.2.0 or later.
  • Restrict access to SQLFluff to only trusted users.
  • Monitor SQLFluff deployments for suspicious activity.

Evidence notes

CVE-2026-46374 has a CVSS score of 7.5 and is classified as HIGH severity. The vulnerability was published on 2026-06-09T23:16:59.313Z and modified on 2026-06-12T14:01:35.000Z.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-46374 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-46374

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-46374 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-46374

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.