How severe is GHSA-4mqg-h5jf-j9m7?

GHSA-4mqg-h5jf-j9m7 has a CVSS score of 9.9/10, rated CRITICAL. Immediate patching is strongly recommended.

Which packages are affected by GHSA-4mqg-h5jf-j9m7?

GHSA-4mqg-h5jf-j9m7 affects the following packages: torchserve (PyPI). Ecosystems affected: PyPI.

How do I fix GHSA-4mqg-h5jf-j9m7?

Update torchserve to 0.8.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-4mqg-h5jf-j9m7 is resolved across your whole dependency graph.

How do I detect GHSA-4mqg-h5jf-j9m7 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for torchserve. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

How do I mitigate GHSA-4mqg-h5jf-j9m7 if there is no patch (or I can't update yet)?

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.

How does O3 Security protect against GHSA-4mqg-h5jf-j9m7?

O3 pinpoints whether GHSA-4mqg-h5jf-j9m7 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Is GHSA-4mqg-h5jf-j9m7 actively exploited in the wild?

No public exploit code has been indexed for GHSA-4mqg-h5jf-j9m7 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

When was GHSA-4mqg-h5jf-j9m7 published, and has it been updated?

GHSA-4mqg-h5jf-j9m7 was published on October 2, 2023 and was last updated on December 7, 2024. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

GHSA-4mqg-h5jf-j9m7

CRITICAL

TorchServe Pre-Auth Remote Code Execution

Published

Oct 2, 2023

Updated

Dec 7, 2024

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Blast Radius

1 pkg affected

🐍torchserve

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

Impact

Use of Open Source Library potentially exposed to RCE Issue: Use of a version of the SnakeYAML v1.31 open source library with multiple issues that potentially exposes the user to unsafe deserialization of Java objects. This could allow third parties to execute arbitrary code on the target system. This issue is present in versions 0.3.0 to 0.8.1. Mitigation: A pull request to address this issue has been merged - https://github.com/pytorch/serve/pull/2523. TorchServe release 0.8.2 includes this fix.

Patches

TorchServe release 0.8.2 includes fixes to address the previously listed issue:

https://github.com/pytorch/serve/releases/tag/v0.8.2

Tags for upgraded DLC release User can use the following new image tags to pull DLCs that ship with patched TorchServe version 0.8.2: x86 GPU

v1.9-pt-ec2-2.0.1-inf-gpu-py310
v1.8-pt-sagemaker-2.0.1-inf-gpu-py310

x86 CPU

v1.8-pt-ec2-2.0.1-inf-cpu-py310
v1.7-pt-sagemaker-2.0.1-inf-cpu-py310

Graviton

v1.7-pt-graviton-ec2-2.0.1-inf-cpu-py310
v1.5-pt-graviton-sagemaker-2.0.1-inf-cpu-py310

Neuron

1.13.1-neuron-py310-sdk2.13.2-ubuntu20.04
1.13.1-neuronx-py310-sdk2.13.2-ubuntu20.04
1.13.1-neuronx-py310-sdk2.13.2-ubuntu20.04

The full DLC image URI details can be found at: https://github.com/aws/deep-learning-containers/blob/master/available_images.md#available-deep-learning-containers-images

References

https://github.com/pytorch/serve/pull/2523 https://github.com/pytorch/serve/releases/tag/v0.8.2 https://github.com/aws/deep-learning-containers/blob/master/available_images.md#available-deep-learning-containers-images

Credit

We would like to thank Oligo Security for responsibly disclosing this issue and working with us on its resolution. If you have any questions or comments about this advisory, we ask that you contact AWS/Amazon Security via our vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting)) or directly via email to [email protected]. Please do not create a public GitHub issue.

Affected Packages

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`torchserve`	≥ 0.3.0&&< 0.8.2	0.8.2

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for torchserve. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update torchserve to 0.8.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-4mqg-h5jf-j9m7 is resolved across your whole dependency graph.
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.
How O3 protects you
O3 pinpoints whether GHSA-4mqg-h5jf-j9m7 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-4mqg-h5jf-j9m7. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

## Impact **Use of Open Source Library potentially exposed to RCE** **Issue**: Use of a version of the SnakeYAML `v1.31 `open source library with multiple issues that potentially exposes the user to unsafe deserialization of Java objects. This could allow third parties to execute arbitrary code on the target system. This issue is present in versions `0.3.0` to `0.8.1`. **Mitigation**: A pull request to address this issue has been merged - https://github.com/pytorch/serve/pull/2523. TorchServe release `0.8.2` includes this fix. ## Patches ## TorchServe release 0.8.2 includes fixes to

O3 Security · Impact-Aware SCA

Is GHSA-4mqg-h5jf-j9m7 in your dependencies?

O3 detects GHSA-4mqg-h5jf-j9m7 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

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