Vulnerability-Lookup

CVE-2025-66455 (GCVE-0-2025-66455)

Vulnerability from cvelistv5 – Published: 2026-09-18 17:03 – Updated: 2026-09-18 19:54

Title

LMDeploy has Remote Code Execution by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py

Summary

LMDeploy is a toolkit for compressing, deploying, and serving large language models. Starting in version 0.9.2 and prior to version 0.16.0, 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. The fix was released in LMDeploy 0.16.0. 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, and block arbitrary outbound ZeroMQ connections from serving nodes. These measures reduce exposure but do not make pickle deserialization safe.

Severity

9.8 (Critical)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

SSVC

Exploitation: none Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-09-18 19:54 UTC

CWE

CWE-502 - Deserialization of Untrusted Data

Assigner

GitHub_M mitre root

References

3 references

URL	Tags
https://github.com/InternLM/lmdeploy/security/adv…	x_refsource_CONFIRM
https://github.com/InternLM/lmdeploy/commit/f05b4…	x_refsource_MISC
https://github.com/InternLM/lmdeploy/releases/tag…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version	CPE status
InternLM	lmdeploy	Affected: >= 0.9.2, < 0.16.0	guessed

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-66455",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-09-18T19:54:08.825899Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-09-18T19:54:19.941Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "lmdeploy",
          "vendor": "InternLM",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 0.9.2, \u003c 0.16.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "LMDeploy is a toolkit for compressing, deploying, and serving large language models. Starting in version 0.9.2 and prior to version 0.16.0, LMDeploy\u0027s 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. The fix was released in LMDeploy 0.16.0. 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, and block arbitrary outbound ZeroMQ connections from serving nodes. These measures reduce exposure but do not make pickle deserialization safe."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 9.8,
            "baseSeverity": "CRITICAL",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-502",
              "description": "CWE-502: Deserialization of Untrusted Data",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-09-18T17:03:37.084Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-2vh9-42vm-xmv2",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-2vh9-42vm-xmv2"
        },
        {
          "name": "https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2"
        },
        {
          "name": "https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0"
        }
      ],
      "source": {
        "advisory": "GHSA-2vh9-42vm-xmv2",
        "discovery": "UNKNOWN"
      },
      "title": "LMDeploy has Remote Code Execution\u00a0by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2025-66455",
    "datePublished": "2026-09-18T17:03:37.084Z",
    "dateReserved": "2025-12-01T18:44:35.640Z",
    "dateUpdated": "2026-09-18T19:54:19.941Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2",
  "vulnerability-lookup:meta": {
    "nvd": {
      "cve": {
        "affected": [
          {
            "affectedData": [
              {
                "product": "lmdeploy",
                "vendor": "InternLM",
                "versions": [
                  {
                    "status": "affected",
                    "version": "\u003e= 0.9.2, \u003c 0.16.0"
                  }
                ]
              }
            ],
            "source": "security-advisories@github.com"
          }
        ],
        "cveTags": [],
        "descriptions": [
          {
            "lang": "en",
            "value": "LMDeploy is a toolkit for compressing, deploying, and serving large language models. Starting in version 0.9.2 and prior to version 0.16.0, LMDeploy\u0027s 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. The fix was released in LMDeploy 0.16.0. 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, and block arbitrary outbound ZeroMQ connections from serving nodes. These measures reduce exposure but do not make pickle deserialization safe."
          }
        ],
        "id": "CVE-2025-66455",
        "lastModified": "2026-09-18T20:17:00.043",
        "metrics": {
          "cvssMetricV31": [
            {
              "cvssData": {
                "attackComplexity": "LOW",
                "attackVector": "NETWORK",
                "availabilityImpact": "HIGH",
                "baseScore": 9.8,
                "baseSeverity": "CRITICAL",
                "confidentialityImpact": "HIGH",
                "integrityImpact": "HIGH",
                "privilegesRequired": "NONE",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
                "version": "3.1"
              },
              "exploitabilityScore": 3.9,
              "impactScore": 5.9,
              "source": "security-advisories@github.com",
              "type": "Secondary"
            }
          ],
          "ssvcV203": [
            {
              "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
              "ssvcData": {
                "id": "CVE-2025-66455",
                "options": [
                  {
                    "exploitation": "none"
                  },
                  {
                    "automatable": "yes"
                  },
                  {
                    "technicalImpact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-09-18T19:54:08.825899Z",
                "version": "2.0.3"
              }
            }
          ]
        },
        "published": "2026-09-18T18:17:04.420",
        "references": [
          {
            "source": "security-advisories@github.com",
            "url": "https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2"
          },
          {
            "source": "security-advisories@github.com",
            "url": "https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0"
          },
          {
            "source": "security-advisories@github.com",
            "url": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-2vh9-42vm-xmv2"
          }
        ],
        "sourceIdentifier": "security-advisories@github.com",
        "vulnStatus": "Received",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-502"
              }
            ],
            "source": "security-advisories@github.com",
            "type": "Secondary"
          }
        ]
      }
    },
    "vulnrichment": {
      "containers": {
        "adp": [
          {
            "metrics": [
              {
                "other": {
                  "content": {
                    "id": "CVE-2025-66455",
                    "options": [
                      {
                        "Exploitation": "none"
                      },
                      {
                        "Automatable": "yes"
                      },
                      {
                        "Technical Impact": "total"
                      }
                    ],
                    "role": "CISA Coordinator",
                    "timestamp": "2026-09-18T19:54:08.825899Z",
                    "version": "2.0.3"
                  },
                  "type": "ssvc"
                }
              }
            ],
            "providerMetadata": {
              "dateUpdated": "2026-09-18T19:54:14.828Z",
              "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
              "shortName": "CISA-ADP"
            },
            "title": "CISA ADP Vulnrichment"
          }
        ],
        "cna": {
          "affected": [
            {
              "product": "lmdeploy",
              "vendor": "InternLM",
              "versions": [
                {
                  "status": "affected",
                  "version": "\u003e= 0.9.2, \u003c 0.16.0"
                }
              ]
            }
          ],
          "descriptions": [
            {
              "lang": "en",
              "value": "LMDeploy is a toolkit for compressing, deploying, and serving large language models. Starting in version 0.9.2 and prior to version 0.16.0, LMDeploy\u0027s 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. The fix was released in LMDeploy 0.16.0. 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, and block arbitrary outbound ZeroMQ connections from serving nodes. These measures reduce exposure but do not make pickle deserialization safe."
            }
          ],
          "metrics": [
            {
              "cvssV3_1": {
                "attackComplexity": "LOW",
                "attackVector": "NETWORK",
                "availabilityImpact": "HIGH",
                "baseScore": 9.8,
                "baseSeverity": "CRITICAL",
                "confidentialityImpact": "HIGH",
                "integrityImpact": "HIGH",
                "privilegesRequired": "NONE",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
                "version": "3.1"
              }
            }
          ],
          "problemTypes": [
            {
              "descriptions": [
                {
                  "cweId": "CWE-502",
                  "description": "CWE-502: Deserialization of Untrusted Data",
                  "lang": "en",
                  "type": "CWE"
                }
              ]
            }
          ],
          "providerMetadata": {
            "dateUpdated": "2026-09-18T17:03:37.084Z",
            "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
            "shortName": "GitHub_M"
          },
          "references": [
            {
              "name": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-2vh9-42vm-xmv2",
              "tags": [
                "x_refsource_CONFIRM"
              ],
              "url": "https://github.com/InternLM/lmdeploy/security/advisories/GHSA-2vh9-42vm-xmv2"
            },
            {
              "name": "https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/InternLM/lmdeploy/commit/f05b4ad8bf2e2d84101a1d63b3c44fadd99223b2"
            },
            {
              "name": "https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0"
            }
          ],
          "source": {
            "advisory": "GHSA-2vh9-42vm-xmv2",
            "discovery": "UNKNOWN"
          },
          "title": "LMDeploy has Remote Code Execution\u00a0by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py"
        }
      },
      "cveMetadata": {
        "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "assignerShortName": "GitHub_M",
        "cveId": "CVE-2025-66455",
        "datePublished": "2026-09-18T17:03:37.084Z",
        "dateReserved": "2025-12-01T18:44:35.640Z",
        "dateUpdated": "2026-09-18T19:54:19.941Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}

GHSA-2VH9-42VM-XMV2

Vulnerability from github – Published: 2026-09-18 17:03 – Updated: 2026-09-18 17:03

Summary

LMDeploy has Remote Code Execution by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py

Details

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

A caller submits a DistServe P2P connection request containing a ZeroMQ address.
The LMDeploy engine connects its ZeroMQ PULL socket to that address.
handle_zmq_recv() receives messages using recv_pyobj().
A malicious peer sends a crafted pickle object.
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.

Severity

9.8 (Critical)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "lmdeploy"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.9.2"
            },
            {
              "fixed": "0.16.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-66455"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-502"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-09-18T17:03:56Z",
    "nvd_published_at": null,
    "severity": "CRITICAL"
  },
  "details": "## Summary\n\nLMDeploy\u0027s 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 \u003e= 0.9.2, \u003c 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.",
  "id": "GHSA-2vh9-42vm-xmv2",
  "modified": "2026-09-18T17:03:56Z",
  "published": "2026-09-18T17:03:56Z",
  "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"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "LMDeploy has Remote Code Execution\u00a0by Pickle Deserialization via handle_zmq_recv in lmdeploy/lmdeploy/pytorch/disagg/conn/engine_conn.py"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

Action not permitted

CVE-2025-66455 (GCVE-0-2025-66455)

GHSA-2VH9-42VM-XMV2

Summary

Affected components

Vulnerable data flow

Impact

Affected versions

Remediation

Workarounds

Tags

Sightings

Nomenclature

Related by attack behaviour