Memory Exhaustion in Grafana Loki Queries

Executive Summary

This vulnerability involves Loki queries that request large data limits. These queries can cause significant memory usage, potentially leading to service unavailability depending on how Loki is deployed.

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Impact Analysis

An attacker could exploit this by sending queries with large limits, consuming excessive memory. This may slow down or crash the Loki service, disrupting log queries and affecting system reliability.

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Mitigation Strategies

Limit the maximum query limit in Loki configuration to prevent large memory allocations. Monitor memory usage during queries and set alerts for abnormal spikes. Ensure Grafana and Loki deployments have sufficient resources to handle peak loads.

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Executive Summary

This vulnerability involves Loki queries that request large data limits, leading to excessive memory usage. This can degrade or crash the service depending on how it is deployed, impacting its availability.

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Impact Analysis

If you use Loki for log queries, an attacker could exploit this by sending queries with large limits, causing high memory consumption. This may slow down or crash your Loki instance, disrupting log retrieval and monitoring.

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Executive Summary

This vulnerability involves Loki queries that request large data limits. These queries can cause significant memory allocation, potentially overwhelming the service and affecting its availability depending on how it is deployed.

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Impact Analysis

An attacker could exploit this by sending queries with large limits, causing high memory usage. This may lead to service slowdowns or crashes, disrupting access to logs and metrics.

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Detection Guidance

This vulnerability involves excessive memory allocation due to large query limits in Loki. To detect it, monitor system memory usage during query execution. Check Loki logs for large query limits or out-of-memory errors. Use commands like 'top', 'htop', or 'ps aux' to observe memory consumption by Loki processes. Look for sustained high memory usage correlating with query activity.

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