An authorization bypass vulnerability exists in the Countly Server DBViewer due to flawed sub-pipeline detection in the aggregation stage sanitizer. The /o/db aggregation endpoint parses user-controlled aggregation JSON and passes it through a stage sanitizer that determines whether a nested array is a sub-pipeline by checking if every element contains a key present in a hardcoded KNOWN_STAGE_OPERATORS set. If any element contains an unrecognized stage key, such as the undocumented MongoDB-internal $_internalInhibitOptimization, the sanitizer misclassifies the entire branch as a generic array and skips stage-level stripping for all sibling stages. This allows a non-admin user with DBViewer read permission to inject forbidden operators like $lookup inside $facet sub-pipelines, performing cross-collection joins into restricted collections. This leads to unauthorized read access to sensitive data including password-reset tokens (prid), enabling account takeover.

An authorization bypass vulnerability exists in the Countly Server DBViewer due to flawed sub-pipeline detection in the aggregation stage sanitizer. The /o/db aggregation endpoint parses user-controlled aggregation JSON and passes it through a stage sanitizer that determines whether a nested array is a sub-pipeline by checking if every element contains a key present in a hardcoded KNOWN_STAGE_OPERATORS set. If any element contains an unrecognized stage key, such as the undocumented MongoDB-internal $_internalInhibitOptimization, the sanitizer misclassifies the entire branch as a generic array and skips stage-level stripping for all sibling stages. This allows a non-admin user with DBViewer read permission to inject forbidden operators like $lookup inside $facet sub-pipelines, performing cross-collection joins into restricted collections. This leads to unauthorized read access to sensitive data including password-reset tokens (prid), enabling account takeover.

Ein Angreifer kann mehrere Schwachstellen in MongoDB ausnutzen, um Abfrage- und Zugriffsbeschränkungen zu umgehen, nicht vorgesehene Datensätze oder Dateien auszulesen, zu verändern oder zu löschen sowie unter bestimmten Voraussetzungen MongoDB-Server oder Anwendungen zum Absturz zu bringen und dadurch einen Denial-of-Service zu verursachen.