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CRE-2025-0179

N8N Workflow Silent Data Loss During ExecutionCritical
Impact: 9/10
Mitigation: 7/10

CRE-2025-0179View on GitHub

Description

N8N workflow automation platform experiences critical silent data loss where items

disappear between workflow nodes without generating error messages. This high-severity

issue affects long-running workflows (60-115+ minutes) and can cause workflows to

randomly cancel mid-execution, leading to incomplete processing and data integrity

problems. Items silently vanish between nodes, with different item counts across

the workflow pipeline, making the issue particularly dangerous for production systems

that rely on complete data processing.


Cause

* Workflow execution engine fails to properly track items between nodes in long-running workflows

* Memory management issues during extended workflow processing causing item references to be lost

* Race conditions in the worker queue system when handling multiple concurrent items

* Node-to-node data transfer mechanisms failing silently under certain load conditions

* Queue worker timeout or resource contention causing partial item processing without error reporting

* Database transaction issues where some items fail to persist between workflow stages


Mitigation

  • Implement workflow item counting checks - Add validation nodes between critical

processing steps to verify item counts match expected values

  • Enable comprehensive execution logging - Set N8N_LOG_LEVEL to debug and

EXECUTIONS_DATA_SAVE_ON_SUCCESS to 'all' to capture detailed execution data

  • Add workflow timeout monitoring - Monitor executions that cancel around 21-23

minute mark and implement retry mechanisms for failed workflows

  • Implement data integrity validation - Add checksum or validation steps at

workflow start/end to detect silent data loss

  • Use error handling workflows - Configure error workflows to capture and log

execution failures, even when main workflow fails silently

  • Monitor execution metrics - Set up alerting on workflow completion rates and

item processing inconsistencies

  • Consider workflow segmentation - Break long workflows into smaller, more

manageable chunks to reduce exposure to the data loss issue


References