Affected: Bitnami: mongodb

This issue can occur when running an aggregation pipeline that uses the internal $exchange stage configured with key-range partitioning and order-preserving delivery. If a single key range produces enough documents to fill its exchange buffer (that is, many results are routed to the same consumer), the server reaches the code path where a full per-consumer buffer is detected but the internal "high watermark" for that key range is not updated as intended.

This issue can occur when running an aggregation pipeline that uses the internal $exchange stage configured with key-range partitioning and order-preserving delivery. If a single key range produces enough documents to fill its exchange buffer (that is, many results are routed to the same consumer), the server reaches the code path where a full per-consumer buffer is detected but the internal "high watermark" for that key range is not updated as intended.

This issue can occur when running an aggregation pipeline that uses the internal $exchange stage configured with key-range partitioning and order-preserving delivery. If a single key range produces enough documents to fill its exchange buffer (that is, many results are routed to the same consumer), the server reaches the code path where a full per-consumer buffer is detected but the internal "high watermark" for that key range is not updated as intended.

Affected: Ubuntu:Pro:14.04:LTS: mongodb, Ubuntu:Pro:16.04:LTS: mongodb, Ubuntu:Pro:18.04:LTS: mongodb, Ubuntu:Pro:20.04:LTS: mongodb

This issue can occur when running an aggregation pipeline that uses the internal $exchange stage configured with key-range partitioning and order-preserving delivery. If a single key range produces enough documents to fill its exchange buffer (that is, many results are routed to the same consumer), the server reaches the code path where a full per-consumer buffer is detected but the internal "high watermark" for that key range is not updated as intended.

Ein Angreifer kann mehrere Schwachstellen in MongoDB ausnutzen, um einen Denial of Service Angriff durchzuführen oder vertrauliche Informationen offenzulegen.