CVE-2025-66455: Lmdeploy Remote Code Execution Vulnerability

CRITICAL
Advisory Identifier: GHSA-2vh9-42vm-xmv2
CVSS 9.8
CWE-502
Published
Advisory Summary

CVE-2025-66455 is a CRITICAL (CVSS 9.8) remote code execution vulnerability (CWE-502: Deserialization of Untrusted Data) affecting Lmdeploy libraries in the PyPI ecosystem. The issue involves lmdeploy has remote code execution by pickle deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py. Remediation is available by upgrading affected packages to version 0.16.0.

CVE-2025-66455 at a Glance

CVE Identifier CVE-2025-66455
GHSA Identifier GHSA-2vh9-42vm-xmv2
Severity CRITICAL
CVSS v3.1 Base Score 9.8
CWE Classification CWE-502: Deserialization of Untrusted Data
Affected Product Lmdeploy
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 9.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2025-66455

To remediate this vulnerability, upgrade all affected Lmdeploy dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

lmdeploy fixed: 0.16.0
pip install lmdeploy>=0.16.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show lmdeploy

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2025-66455, inspect your installed packages using pip:

pip show lmdeploy

Analyze the terminal output to locate any version of Lmdeploy in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 0.16.0), your application is affected.

Note: The pip show lmdeploy command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-502: Deserialization of Untrusted Data, where the product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. In Lmdeploy, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

## Summary LMDeploy's PyTorch DistServe/PD-disaggregation control plane used `recv_pyobj()` to deserialize messages received through a ZeroMQ PULL socket. PyZMQ implements `recv_pyobj()` using Python pickle deserialization, which can execute arbitrary code while reconstructing an object. The peer address used by the receiver was supplied through the `POST /distserve/p2p_connect` HTTP endpoint. An attacker who could reach an affected DistServe API server could cause the server to connect to an attacker-controlled ZeroMQ endpoint and deserialize a crafted pickle payload. API-key authentication is not enabled unless the operator explicitly configures it. As a result, affected DistServe deployments without API keys allowed unauthenticated remote code execution with the privileges of the LMDeploy serving process. This issue affects the PyTorch backend when PD-disaggregation/DistServe is enabled. Ordinary deployments that do not use the affected disaggregated-serving path do not expose this data flow. ## Affected components - HTTP entry point: `lmdeploy/serve/openai/endpoints/distserve.py`, `POST /distserve/p2p_connect` - Attacker-controlled peer address: `DistServeConnectionRequest.remote_engine_endpoint_info.zmq_address` - Vulnerable receiver: `lmdeploy/pytorch/disagg/conn/engine_conn.py`, `EngineP2PConnection.handle_zmq_recv()` - Unsafe operation: `recv_pyobj()`, which performs pickle deserialization ## Vulnerable data flow 1. A caller submits a DistServe P2P connection request containing a ZeroMQ address. 2. The LMDeploy engine connects its ZeroMQ PULL socket to that address. 3. `handle_zmq_recv()` receives messages using `recv_pyobj()`. 4. A malicious peer sends a crafted pickle object. 5. Python code executes during deserialization, before LMDeploy can perform any type or field validation. A type check performed after `recv_pyobj()` cannot mitigate this issue because pickle payload execution occurs during deserialization. ## Impact Successful exploitation allows arbitrary code execution as the LMDeploy serving process. This can expose model weights, prompts, credentials, attached storage, cluster-network services, and host or GPU resources. An attacker may also modify or terminate the serving process. ## Affected versions Affected versions: - `lmdeploy >= 0.9.2, < 0.16.0` The vulnerable P2P receiver was introduced in commit `b0b705f7`. ## Remediation The issue was fixed by replacing the pickle-based ZeroMQ protocol with JSON serialization: - `send_pyobj()` was replaced with `send_json()`. - `recv_pyobj()` was replaced with `recv_json()`. - Received objects are validated using the `DistServeCacheFreeRequest` Pydantic schema before use. - Invalid or off-schema messages are rejected without terminating the receive loop. Fix commit: https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2 The fix was released in LMDeploy 0.16.0. ## Workarounds Users who cannot upgrade immediately should: - Prevent untrusted clients from reaching `/distserve/*` endpoints. - Restrict the DistServe HTTP and ZeroMQ control planes to trusted cluster networks. - Configure API-key authentication. - Block arbitrary outbound ZeroMQ connections from serving nodes. These measures reduce exposure but do not make pickle deserialization safe. Upgrading to LMDeploy 0.16.0 or later is recommended.

CVE-2025-66455 Affected Lmdeploy Versions

1 component(s)
Fixed Versions:
0.16.0
Product / Package Ecosystem Affected Versions Fixed Version
lmdeploy
PyPI
≥ 0.9.2
< 0.16.0
0.16.0

References

Frequently Asked Questions

What is CVE-2025-66455?
CVE-2025-66455 is a security vulnerability in Lmdeploy involving LMDeploy has Remote Code Execution by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py under CWE-502: Deserialization of Untrusted Data.
Which Lmdeploy versions are affected?
Affected versions include releases prior to 0.16.0 across affected packages: lmdeploy.
What version fixes CVE-2025-66455?
Upgrading to 0.16.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is lmdeploy affected?
Yes, lmdeploy is affected in releases prior to 0.16.0. Upgrade your dependency to 0.16.0 or later.
What is the CVSS score of CVE-2025-66455?
CVE-2025-66455 has a CVSS v3.1 base score of 9.8 (CRITICAL) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2025-66455?
CVE-2025-66455 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).
How can I check PyPI dependencies for CVE-2025-66455?
Run the dependency tree command: 'pip show lmdeploy'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-2vh9-42vm-xmv2",
  "modified" : "2026-09-18T17:03:56Z",
  "published" : "2026-09-18T17:03:56Z",
  "aliases" : [ "CVE-2025-66455" ],
  "summary" : "LMDeploy has Remote Code Execution by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py",
  "details" : "## Summary\n\nLMDeploy's PyTorch DistServe/PD-disaggregation control plane used\n`recv_pyobj()` to deserialize messages received through a ZeroMQ PULL\nsocket. PyZMQ implements `recv_pyobj()` using Python pickle\ndeserialization, which can execute arbitrary code while reconstructing\nan object.\n\nThe peer address used by the receiver was supplied through the\n`POST /distserve/p2p_connect` HTTP endpoint. An attacker who could reach\nan affected DistServe API server could cause the server to connect to an\nattacker-controlled ZeroMQ endpoint and deserialize a crafted pickle\npayload.\n\nAPI-key authentication is not enabled unless the operator explicitly\nconfigures it. As a result, affected DistServe deployments without API\nkeys allowed unauthenticated remote code execution with the privileges\nof the LMDeploy serving process.\n\nThis issue affects the PyTorch backend when PD-disaggregation/DistServe\nis enabled. Ordinary deployments that do not use the affected\ndisaggregated-serving path do not expose this data flow.\n\n## Affected components\n\n- HTTP entry point:\n  `lmdeploy/serve/openai/endpoints/distserve.py`,\n  `POST /distserve/p2p_connect`\n- Attacker-controlled peer address:\n  `DistServeConnectionRequest.remote_engine_endpoint_info.zmq_address`\n- Vulnerable receiver:\n  `lmdeploy/pytorch/disagg/conn/engine_conn.py`,\n  `EngineP2PConnection.handle_zmq_recv()`\n- Unsafe operation: `recv_pyobj()`, which performs pickle deserialization\n\n## Vulnerable data flow\n\n1. A caller submits a DistServe P2P connection request containing a\n   ZeroMQ address.\n2. The LMDeploy engine connects its ZeroMQ PULL socket to that address.\n3. `handle_zmq_recv()` receives messages using `recv_pyobj()`.\n4. A malicious peer sends a crafted pickle object.\n5. Python code executes during deserialization, before LMDeploy can\n   perform any type or field validation.\n\n  A type check performed after `recv_pyobj()` cannot mitigate this issue\n  because pickle payload execution occurs during deserialization.\n\n## Impact\n\nSuccessful exploitation allows arbitrary code execution as the\nLMDeploy serving process. This can expose model weights, prompts,\ncredentials, attached storage, cluster-network services, and host or\nGPU resources. An attacker may also modify or terminate the serving\nprocess.\n\n## Affected versions\n\nAffected versions:\n\n- `lmdeploy >= 0.9.2, < 0.16.0`\n\nThe vulnerable P2P receiver was introduced in commit `b0b705f7`.\n\n## Remediation\n\nThe issue was fixed by replacing the pickle-based ZeroMQ protocol with\nJSON serialization:\n\n- `send_pyobj()` was replaced with `send_json()`.\n- `recv_pyobj()` was replaced with `recv_json()`.\n- Received objects are validated using the\n  `DistServeCacheFreeRequest` Pydantic schema before use.\n- Invalid or off-schema messages are rejected without terminating the\n  receive loop.\n\nFix commit:\n\nhttps://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2\n\nThe fix was released in LMDeploy 0.16.0.\n\n## Workarounds\n\nUsers who cannot upgrade immediately should:\n\n- Prevent untrusted clients from reaching `/distserve/*` endpoints.\n- Restrict the DistServe HTTP and ZeroMQ control planes to trusted\n  cluster networks.\n- Configure API-key authentication.\n- Block arbitrary outbound ZeroMQ connections from serving nodes.\n\nThese measures reduce exposure but do not make pickle deserialization\nsafe. Upgrading to LMDeploy 0.16.0 or later is recommended.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "lmdeploy"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0.9.2"
      }, {
        "fixed" : "0.16.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-2vh9-42vm-xmv2"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/InternLM/lmdeploy"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-502" ],
    "severity" : "CRITICAL",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-09-18T17:03:56Z",
    "nvd_published_at" : null
  }
}