CVE-2025-0190 in aim
Summary
by MITRE • 03/20/2025
In version 3.25.0 of aimhubio/aim, a denial of service vulnerability exists. By tracking a large number of `Text` objects and then querying them simultaneously through the web API, the Aim web server becomes unresponsive to other requests for an extended period while processing and returning these objects. This vulnerability can be exploited repeatedly, leading to a complete denial of service.
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Analysis
by VulDB Data Team • 03/20/2025
The vulnerability identified as CVE-2025-0190 affects aimhubio/aim version 3.25.0 and represents a significant denial of service threat that can severely impact system availability. This issue stems from the application's handling of large volumes of Text objects within its tracking mechanism, creating a scenario where legitimate users experience complete service interruption. The vulnerability specifically manifests when multiple Text objects are tracked and subsequently queried through the web API, causing the Aim web server to become unresponsive to concurrent requests. This behavior demonstrates a classic resource exhaustion pattern where the server's processing capabilities are overwhelmed by the volume and complexity of simultaneous queries.
The technical flaw underlying this vulnerability resides in the web server's inability to efficiently handle concurrent requests when processing large datasets of Text objects. When numerous Text objects are tracked and queried simultaneously, the server's thread management and resource allocation mechanisms become saturated, leading to a complete halt in processing other legitimate requests. This represents a failure in proper resource management and concurrent request handling, which can be categorized under CWE-400 - Uncontrolled Resource Consumption and CWE-775 - Missing Release of Resource after Effective Lifetime. The vulnerability's exploitable nature is amplified by its repetitive capability, allowing attackers to maintain sustained denial of service conditions rather than achieving only a single disruption event.
The operational impact of this vulnerability extends beyond simple service interruption to potentially compromise the entire application ecosystem. System administrators and end users experience complete unresponsiveness during the attack window, which can result in significant productivity losses and potential data access issues. The web server's inability to process other requests during the attack period creates cascading effects that may impact dependent services or applications relying on the Aim platform. This vulnerability particularly affects environments where real-time monitoring and data analysis are critical, as the denial of service can prevent users from accessing crucial performance metrics and tracking information. Organizations using this version of aimhubio/aim may face operational disruptions that could affect research workflows, development cycles, and analytical processes that depend on continuous access to tracking data.
Mitigation strategies for CVE-2025-0190 should focus on implementing proper resource management and request handling mechanisms within the Aim web server. Organizations should consider implementing rate limiting and request queuing mechanisms to prevent overwhelming the server with simultaneous queries. The implementation of proper resource cleanup and memory management practices can help prevent the accumulation of processing overhead that leads to server unresponsiveness. Additionally, upgrading to a patched version of aimhubio/aim that addresses this specific denial of service vulnerability should be prioritized. Security teams should monitor for signs of exploitation through unusual query patterns and implement network-level controls to limit the impact of potential attacks. The vulnerability's characteristics align with ATT&CK technique T1499.004 - Endpoint Denial of Service, specifically targeting the availability aspect of the application's core functionality. Regular security assessments and load testing should be conducted to identify potential resource exhaustion points and ensure the system maintains adequate performance under various workload conditions.