Is CVE-2026-27893 exploited in the wild?

No. Junglewise Threat Intelligence has no report of CVE-2026-27893 being exploited in the wild.

How severe is CVE-2026-27893?

High severity, with a CVSS score of 8.8, published 27 March 2026.

Which products and versions are affected?

vllm (PyPI) ECOSYSTEM:introduced=0.10.1,fixed=0.18.0; Red Hat AI Inference Server 3.2, 3.3.

Is there a fix for CVE-2026-27893?

Yes. vllm (PyPI): upgrade to 0.18.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

How is CVE-2026-27893 attacked?

It is attacked over the network, in a software library.

Am I affected by CVE-2026-27893?

Check whether you run vllm (PyPI), Red Hat AI Inference Server or Vllm at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

CVE-2026-27893: vLLM remote code execution via hardcoded remote code trust in models

CVE-2026-27893 · Severity: high · CVSS 8.8 · Published 2026-03-27

vLLM is a high-performance engine used to run large language models (LLMs). A security flaw was found where the software ignores a user's request to block untrusted code when loading certain specific AI models (Nemotron and Kimi). If an attacker convinces a user to load a malicious model from a remote repository, they could execute arbitrary commands on the user's system, potentially leading to full system takeover or data theft.

Technologies: vllm (PyPI), Red Hat AI Inference Server, Vllm. Vendors: PyPI, Red Hat, Vllm.

Quick answers

Is CVE-2026-27893 exploited in the wild?: No. Junglewise Threat Intelligence has no report of CVE-2026-27893 being exploited in the wild.
How severe is CVE-2026-27893?: High severity, with a CVSS score of 8.8, published 27 March 2026.
Which products and versions are affected?: vllm (PyPI) ECOSYSTEM:introduced=0.10.1,fixed=0.18.0; Red Hat AI Inference Server 3.2, 3.3.
Is there a fix for CVE-2026-27893?: Yes. vllm (PyPI): upgrade to 0.18.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.
How is CVE-2026-27893 attacked?: It is attacked over the network, in a software library.
Am I affected by CVE-2026-27893?: Check whether you run vllm (PyPI), Red Hat AI Inference Server or Vllm at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

How to fix

vllm (PyPI): upgrade to 0.18.0 or later
```
pip install "vllm>=0.18.0"
```

Technical details

A protection mechanism failure (CWE-693) exists in vLLM's model executor. Specifically, the implementation files for Nemotron-VL and Kimi-K25 hardcode 'trust_remote_code=True' during calls to HuggingFace API components (AutoModel.from_config and cached_get_image_processor). This hardcoded value overrides the global user-defined security setting intended to prevent the execution of untrusted remote code. An attacker can exploit this by hosting a malicious model repository that, when loaded by a vulnerable vLLM instance, executes arbitrary Python code. The vulnerability was patched in version 0.18.0 by ensuring these components respect the global model configuration.

Affected products

vllm-project vllm >= 0.10.1, < 0.18.0

Identifiers

CVE-2026-27893
GHSA-7972-pg2x-xr59
PYSEC-2026-2297

Timeline

2026-03-26: disclosed
2026-03-27: advisory
2026-03-27: patched: Version 0.18.0 released

References

This page as Markdown. Free to reuse under CC BY 4.0 with a link back.