CVE-2026-73555: CWE-209: Generation of Error Message Containing Sensitive Information in vllm-project vllm
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the validation_exception_handler in vllm/entrypoints/openai/server_utils.py converts FastAPI RequestValidationError objects with str(exc), and sanitize_message in vllm/entrypoints/utils.py does not remove traceback-style file paths, allowing unauthenticated malformed JSON requests to /v1/chat/completions, /v1/completions, /tokenize, and /detokenize to disclose the OS username, home and virtual-environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This issue is fixed in version 0.26.0.
AI Analysis
Technical Summary
The vulnerability in vLLM before version 0.26.0 arises from the validation_exception_handler converting FastAPI RequestValidationError objects to strings without adequately sanitizing sensitive information. The sanitize_message function fails to remove traceback-style file paths, leading to disclosure of OS usernames, home and virtual environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This information disclosure can be triggered by unauthenticated malformed JSON requests to the /v1/chat/completions, /v1/completions, /tokenize, and /detokenize endpoints. The vulnerability is classified as CWE-209 (Generation of Error Message Containing Sensitive Information).
Potential Impact
An attacker can obtain sensitive internal information about the server environment and application structure by sending malformed JSON requests to the affected API endpoints. This information disclosure does not allow direct code execution or data modification but may aid in further attacks by revealing environment details. The CVSS score is 5.3 (medium severity), reflecting limited confidentiality impact without integrity or availability effects.
Mitigation Recommendations
This vulnerability is fixed in vLLM version 0.26.0. Users should upgrade to version 0.26.0 or later to remediate this issue. No other mitigation or temporary workaround is indicated in the available data.
CVE-2026-73555: CWE-209: Generation of Error Message Containing Sensitive Information in vllm-project vllm
Description
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the validation_exception_handler in vllm/entrypoints/openai/server_utils.py converts FastAPI RequestValidationError objects with str(exc), and sanitize_message in vllm/entrypoints/utils.py does not remove traceback-style file paths, allowing unauthenticated malformed JSON requests to /v1/chat/completions, /v1/completions, /tokenize, and /detokenize to disclose the OS username, home and virtual-environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This issue is fixed in version 0.26.0.
CVSS v3.1
Score 5.3medium
Affected software
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Weaknesses
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The vulnerability in vLLM before version 0.26.0 arises from the validation_exception_handler converting FastAPI RequestValidationError objects to strings without adequately sanitizing sensitive information. The sanitize_message function fails to remove traceback-style file paths, leading to disclosure of OS usernames, home and virtual environment paths, Python version, internal package structure, line numbers, and endpoint handler names. This information disclosure can be triggered by unauthenticated malformed JSON requests to the /v1/chat/completions, /v1/completions, /tokenize, and /detokenize endpoints. The vulnerability is classified as CWE-209 (Generation of Error Message Containing Sensitive Information).
Potential Impact
An attacker can obtain sensitive internal information about the server environment and application structure by sending malformed JSON requests to the affected API endpoints. This information disclosure does not allow direct code execution or data modification but may aid in further attacks by revealing environment details. The CVSS score is 5.3 (medium severity), reflecting limited confidentiality impact without integrity or availability effects.
Mitigation Recommendations
This vulnerability is fixed in vLLM version 0.26.0. Users should upgrade to version 0.26.0 or later to remediate this issue. No other mitigation or temporary workaround is indicated in the available data.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-08-12T20:53:46.380Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a7ddecdbf8831d5395d0179
Added to database: 08/13/2026, 15:12:13 UTC
Last enriched: 08/13/2026, 15:28:37 UTC
Last updated: 08/13/2026, 17:43:31 UTC
Views: 4
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