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    CVE-2026-73555

    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.

    Published:Aug 13, 2026
    Last Modified:Aug 14, 2026
    EPS:Aug 13, 2026
    EPSS Score:0.00255
    CVSS Score:5.3

    Affected Products

    Vendor
    Vllm-project
    Product
    Vllm

    Exploits

    No exploit reference

    Related CVEs

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    CVE-2026-71486 (CVSS 4.3) — vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the /v1/completions/derend…
    CVE-2026-73559 (CVSS 6.5) — vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.26.0, the /v1/completio…
    CVE-2026-73558 (CVSS 5.3) — vLLM is an inference and serving engine for large language models. Prior to 0.27.0, an integer overflow in blo…
    CVE-2026-73557 (CVSS 6.3) — vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safe_load_prom…
    CVE-2026-73556 (CVSS 5.3) — vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structured_outputs.reg…
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    CVE-2026-55574 (CVSS 8.7) — vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Prior to 0.24.0, the str…
    CVE-2026-54234 (CVSS 7.5) — vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Prior to 0.24.0, a front…

    Common Vulnerability Scoring System

    Attack Vector
    Network
    Adjacent
    Local
    Physical
    Privileges Required
    None
    Low
    High
    User Interaction
    None
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    Scope
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    Changed
    Confidentiality
    None
    Low
    High
    Integrity
    None
    Low
    High
    Availability
    None
    Low
    High