paddlepaddle/paddle 2.6.0 में रिमोट कोड एग्जीक्यूशन

The impact of CVE-2024-0917 is severe. An attacker who successfully exploits this vulnerability can execute arbitrary code with the privileges of the PaddlePaddle process. This could allow them to install malware, steal sensitive data, modify system configurations, or even gain persistent access to the affected system. Given PaddlePaddle's use in machine learning and AI applications, the potential for data exfiltration and model manipulation is significant. The RCE nature of the vulnerability means an attacker doesn't need prior authentication or access to the system beyond the ability to interact with the PaddlePaddle library.

Organizations deploying PaddlePaddle for machine learning and AI applications are at significant risk. This includes research institutions, businesses using PaddlePaddle for model training and inference, and cloud providers offering PaddlePaddle-based services. Specifically, those using older, unpatched versions of PaddlePaddle are most vulnerable.

• python / supply-chain:

import subprocess
import os

# Check PaddlePaddle version
result = subprocess.run(['python', '-c', 'import paddle; print(paddle.__version__)'], capture_output=True, text=True) 
version = result.stdout.strip()
if version <= '2.6.0':
    print(f"PaddlePaddle version is vulnerable: {version}")

# Check for suspicious files (replace with actual IOCs if available)
# Example: Check for a specific file created by an attacker
# if os.path.exists('/tmp/malicious_script.py'):
#     print("Potential malicious file detected!")

• generic web: Monitor web application logs for unusual Python code execution patterns or errors related to PaddlePaddle. Look for requests containing potentially malicious input that could trigger the RCE.

1. 2024-03-07Disclosure

   disclosure

1. आरक्षित2024-01-26
2. प्रकाशित2024-03-07
3. संशोधित2025-02-13
4. EPSS अद्यतन2026-04-02

The primary mitigation for CVE-2024-0917 is to upgrade to a patched version of PaddlePaddle as soon as it becomes available. Until a patch is released, consider restricting network access to PaddlePaddle instances to minimize the attack surface. Input validation and sanitization are crucial to prevent malicious code from being injected into PaddlePaddle workflows. Monitor PaddlePaddle logs for any suspicious activity, particularly attempts to execute unusual code or access restricted resources. While a WAF may not directly prevent this RCE, it can help detect and block malicious payloads attempting to exploit the vulnerability.