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vllm@0.19.0

A high-throughput and memory-efficient inference and serving engine for LLMs

  • latest version

    0.19.0

  • first published

    2 years ago

  • latest version published

    2 days ago

  • licenses detected

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    Direct Vulnerabilities

    Known vulnerabilities in the vllm package. This does not include vulnerabilities belonging to this package’s dependencies.

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    VulnerabilityVulnerable Version
    • M
    Server-side Request Forgery (SSRF)

    vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs

    Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) via the download_bytes_from_url function. An attacker can cause the server to make arbitrary HTTP or HTTPS requests to internal or external resources by supplying a crafted file_url value in batch input JSON, potentially accessing sensitive internal services or causing denial of service.

    How to fix Server-side Request Forgery (SSRF)?

    A fix was pushed into the master branch but not yet published.

    [0.16.0,)
    • H
    Deserialization of Untrusted Data

    vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the SUB ZeroMQ socket, where the deserialization is performed using the unsafe pickle library. An attacker on the same cluster can execute arbitrary code on the remote machine by sending maliciously crafted deserialized payloads.

    Note The V0 engine is off by default since v0.8.0, and the V1 engine is not affected. Due to the V0 engine's deprecated status and the invasive nature of a fix, the developers recommend ensuring a secure network environment if the V0 engine with multi-host tensor parallelism is still in use.

    How to fix Deserialization of Untrusted Data?

    There is no fixed version for vllm.

    [0.5.2,)
    • H
    Deserialization of Untrusted Data

    vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs

    Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the MessageQueue.dequeue() API function. An attacker can execute arbitrary code by sending a malicious payload to the message queue.

    How to fix Deserialization of Untrusted Data?

    There is no fixed version for vllm.

    [0,)
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