Potential unexpected query failures.

We have identified an issue currently that could result in unexpected query failures when using the trim() Cypher function. Investigations into the cause are in progress.

We have found the issue and are working on a fix. A small percentatge of queries using trim may still err.

VDC customers with databases set to highest are not impacted at all unless they pause and start their instances.

We are testing the fix for the trim() Cypher function issue. We will update before we begin our deployment into the Aura environment.

We are actively validating the fix for the trim() Cypher function. Further updates will be provided before we begin deploying to Aura instances

We continue to validate the fix for the trim() Cypher function.

Further updates will be provided before we begin deploying it to Aura instances.

We continue to validate the fix for the trim() Cypher function.

Further updates will be provided before we begin deploying it to Aura instances.

The fix for the trim() Cypher function is undergoing testing and validation before deployment.

Further updates will be provided before we begin deploying it to Aura instances.

Development has completed on the hot-fix for this issue, and we are finalizing the rollout plan for Aura.

We are actively working on addressing the issue. The fix for the trim() Cypher function is undergoing testing and validation currently before deployment. Further updates will be provided before we begin deploying it to Aura instances.

The fix to the trim() Cypher function has passed testing and validation and is now being deployed.

The fix to resolve the issue has now completed deployment to the Aura service and we are monitoring the situation.

We have monitored the fix and found the service to be stable. This incident is now considered resolved.

# What happened

On Wed, 05 Aug 2026 02:10:00 UTC, the latest version of Neo4j core product was rolled out to the Aura Environment. This release contained a bug in the Cypher `trim()` family of functions (`trim`, `ltrim`, `rtrim`, `btrim`) that incorrectly handled string length encoding during write operations.

The defect could produce two outcomes when a query using these functions modified stored string data:

• Query failure — the operation would error and no data was written.
• Silent data issue — the operation would succeed, but the stored string's length metadata could be recorded incorrectly, potentially resulting in trailing whitespace padding.

The issue was identified on Wed, 05 Aug 2026 17:51:51 UTC after alerting surfaced read-back failures on a single free-tier database. Our engineering team immediately reverted the introducing code change and began preparing a hot-fixed release. The patched version was rolled out across the affected tiers by Fri, 07 Aug 2026 16:02:49 UTC, and an on-premises patch was also published. A customer-facing status page was maintained throughout at https://status.neo4j.io/incidents/kjx6l7442j2v.

# How the service was affected

The impact was limited to Aura databases running Neo4j version 2026.07.0-8 that executed write queries using `trim()`-family Cypher functions during the exposure window.

• Query failures: A small but measurable increase in query errors was observed for transactions involving `trim()`. These failed queries did not persist any data changes.
• Trailing whitespace: In some cases, successful writes stored string values with incorrect trailing whitespace. Through systematic scanning, our team identified a number database instances that showed evidence of this issue.
• Unreadable properties: In one case, a property on a free-tier database instance became unreadable. The systematic scan established that this only occurred once across the whole platform.

Log analysis determined that a small number of database instances across several organizations may have executed potentially affected write queries.

Our engineering team proactively contacted administrators and owners of affected organizations, provided per-database instance diagnostic reports offering guidance on identifying and remediating impacted data. No widespread unreadable-data corruption was found during the fleet-wide consistency and whitespace scans conducted after the fix was deployed.

# What we are doing now

We take data integrity seriously and have undertaken a thorough response to ensure affected customers are supported and to reduce the likelihood of similar issues in the future. Our efforts fall into the following areas:

• Immediate fix — The code change responsible for the defect was reverted and a patched release was deployed across all affected Aura tiers. An on-premises patch was also published for self-managed users.
• Proactive customer outreach — We identified potentially affected databases through log analysis and ran two rounds of offline scans: consistency checks for unreadable-data corruption, and a purpose-built scanner for trailing-whitespace issues. Per-database diagnostic reports were generated and made available, and affected customers were directly notified with guidance.
• Detection improvements — We are evaluating enhanced monitoring for per-function error rates in query processing, which could help surface similar issues earlier during staged rollouts.
• Rollout process review — We are examining our rollout procedures, including whether to introduce additional triage windows between rollout phases and how to prevent databases from inadvertently advancing to newer versions during operations like pause/resume.
• Ongoing follow-ups — Unrelated storage inconsistencies discovered during scans have been tracked and are being addressed by our engineering team through separate work streams.