vLLM: Unauthenticated Internal Path and Username Disclosure via Validation Error Messages
Summary
When the vLLM API receives a malformed request (e.g., invalid JSON or missing required fields), FastAPI raises a Pydantic RequestValidationError. The validation_exception_handler in vllm/entrypoints/openai/server_utils.py converts this exception to a string via str(exc), which includes the internal file path and line number of the handler function. The existing sanitize_message() function in vllm/entrypoints/utils.py strips memory addresses (e.g., 0x7f...) but does not strip File "...", line X patterns. The result is a user-facing HTTP response that leaks internal system information.
Impact
An unauthenticated attacker can extract the following with a single malformed request:
- OS username running the vLLM process (e.g.,
ubuntu) - Home directory path (e.g.,
/home/ubuntu/) - Virtual environment path (e.g.,
vllm-env/) - Python version (e.g.,
3.12) - Internal package structure and line numbers (e.g.,
vllm/entrypoints/openai/chat_completion/api_router.py) - Handler function names per endpoint, enabling precise version fingerprinting
This information aids attackers in constructing targeted exploits: environment paths narrow the attack surface, and handler function names + line numbers enable exact version identification even when the /version endpoint is disabled.
All POST endpoints that accept JSON bodies are affected, including /v1/chat/completions, /v1/completions, /tokenize, and /detokenize.
Workarounds
Deploying vLLM behind a reverse proxy that rewrites error response bodies to strip file paths would mitigate this, though it is fragile.
Remediation Recommendation
Two possible fixes (either suffices):
Option A — Fix validation_exception_handler: Construct the error message from exc.errors() (the structured Pydantic error list) rather than str(exc). This avoids the traceback-style string entirely.
Option B — Fix sanitize_message: Add a regex to strip File "...", line \d+ patterns, similar to how memory addresses are already stripped:
import re
msg = re.sub(r'File ".*?", line \d+, in \w+', '[internal]', msg)
Option A is preferred as it addresses the root cause rather than filtering symptoms.
Environment Tested
- vLLM 0.20.1 (pip install, latest stable as of May 2026)
- Python 3.12
- Ubuntu 22.04
- Model: Qwen/Qwen2-0.5B (text-only; bug is model-independent)
This was fixed here: https://github.com/vllm-project/vllm/commit/e87521626f
Betroffene Software
Klicken Sie auf eine Technologie, um alle zugehörigen Schwachstellen anzuzeigen.
| Plattform | Paket | Anfällige Versionen | Behoben in |
|---|---|---|---|
| Python (PyPI) | vllm | < 0.26.0 | 0.26.0 |
Verweise
- https://github.com/vllm-project/vllm/security/advisories/GHSA-hwrm-c4cx-rf4j
- https://nvd.nist.gov/vuln/detail/CVE-2026-73555
- https://github.com/vllm-project/vllm/pull/46415
- https://github.com/vllm-project/vllm/commit/e87521626febe2763f997691d1599de4175f4324
- https://github.com/vllm-project/vllm
- https://github.com/vllm-project/vllm/releases/tag/v0.26.0
- https://pypi.org/project/vllm
- https://github.com/advisories/GHSA-hwrm-c4cx-rf4j
- CVSS-Vektor
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N- Schwäche (CWE)
CWE-209- Plattform
- Python (PyPI)
- Paket
vllm- Veröffentlicht
- 04.09.2026
- Aktualisiert
- 11.10.2026 15:18
Quellen und Lizenzen
OSV / GitHub Advisory Database - PYSEC-2026-3937 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-hwrm-c4cx-rf4j - CC BY 4.0
Schwachstellenhistorie: vllm
Alle veröffentlichten Schwachstellen dieses Pakets (Python (PyPI)), neueste zuerst. Zeigt, ob es ein einmaliger Ausrutscher ist oder ein Paket, das man im Auge behalten muss.
- Einträge insgesamt
- 94
- Erste → letzte
- 09.2024 10.2026
- Ohne Fix
- 5
- In Angriffen ausgenutzt
- 0
Verteilung nach Schweregrad
- Kritisch 9
- Hoch 23
- Mittel 47
- Niedrig 4
- Nicht bewertet 11
Veröffentlichungen pro Jahr
- 2024: 2
- 2025: 30
- 2026: 62
-
vLLM: Unauthenticated Internal Path and Username Disclosure via Validation Error Messages dieser Eintrag
Erkennen Sie Schwachstellen in Ihrer Anwendung
Mit der DockRay-Integration und aktivierter Softwareinventarisierung prüft DockRay gemeldete Komponentenversionen auf bekannte Schwachstellen und benachrichtigt Sie über bestätigte Treffer. Die Abdeckung hängt von der unterstützten Technologie und den verfügbaren Meldungen ab.