Executive Summary

The vulnerability exists in vLLM, an inference and serving engine for large language models, specifically in versions prior to 0.23.1rc0. The issue is with the /v1/audio/transcriptions endpoint, which limits the size of compressed audio uploads but does not limit the size of the decoded PCM output. For example, a 25MB OPUS audio file can expand to approximately 14.9GB of float32 PCM data when decoded, potentially causing resource exhaustion.

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Impact Analysis

This vulnerability can lead to a denial of service (DoS) condition by exhausting system resources such as memory or processing power due to the large expansion of audio data during decoding. An attacker could exploit this by sending a relatively small compressed audio file that expands to a very large size, overwhelming the system and causing it to become unresponsive or crash.

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Mitigation Strategies

To mitigate this vulnerability, upgrade vLLM to version 0.23.1rc0 or later, where the issue with the /v1/audio/transcriptions endpoint has been fixed.

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