CVE-2025-13687 Overview
IBM DataStage on Cloud Pak for Data versions 5.1.2 through 5.3.0 contains a command injection vulnerability that allows authenticated users to execute arbitrary commands on the underlying system. The vulnerability exists due to improper validation of user-supplied input through the user-defined function component, enabling attackers with low-privileged access to execute system commands with normal user privileges.
Critical Impact
Authenticated attackers can leverage improper input validation in the user-defined function component to inject and execute arbitrary system commands, potentially leading to complete system compromise, data exfiltration, or lateral movement within the Cloud Pak for Data environment.
Affected Products
- IBM DataStage on Cloud Pak for Data 5.1.2
- IBM DataStage on Cloud Pak for Data 5.2.x
- IBM DataStage on Cloud Pak for Data 5.3.0
Discovery Timeline
- 2026-03-03 - CVE-2025-13687 published to NVD
- 2026-03-04 - Last updated in NVD database
Technical Details for CVE-2025-13687
Vulnerability Analysis
This vulnerability is classified as CWE-78 (Improper Neutralization of Special Elements used in an OS Command), commonly known as OS Command Injection. The flaw resides in the user-defined function component of IBM DataStage on Cloud Pak for Data, where user-supplied input is not properly sanitized before being passed to system command execution functions.
The attack can be conducted remotely over the network and requires only low-privilege authenticated access to the platform. No user interaction is required to exploit this vulnerability. Successful exploitation grants attackers the ability to execute arbitrary commands with the privileges of the application process, potentially enabling confidentiality breaches through data access, integrity violations through system modification, and availability impacts through service disruption.
Root Cause
The root cause of CVE-2025-13687 is insufficient input validation in the user-defined function component. When processing user-supplied parameters, the application fails to properly sanitize or escape special characters that have significance in shell command contexts. This allows attackers to inject additional commands by including shell metacharacters such as semicolons, pipes, or command substitution sequences in their input.
Attack Vector
The vulnerability is exploitable over the network by authenticated users with standard privileges. An attacker would craft malicious input containing command injection payloads and submit it through the user-defined function interface. The application processes this input without adequate validation, passing it to an underlying system shell where the injected commands are executed.
The attack does not require any special privileges beyond basic authentication to the DataStage platform. The low attack complexity combined with the potential for high impact on confidentiality, integrity, and availability makes this a significant security concern for organizations running affected versions.
Since no verified code examples are available for this vulnerability, organizations should refer to the IBM Support Document for detailed technical information about the vulnerability mechanism and exploitation patterns.
Detection Methods for CVE-2025-13687
Indicators of Compromise
- Unusual process execution originating from IBM DataStage or Cloud Pak for Data containers
- Unexpected shell commands or subprocesses spawned by the DataStage application process
- Anomalous network connections initiated from the DataStage environment to external addresses
- Log entries showing malformed or suspicious input patterns in user-defined function requests
Detection Strategies
- Monitor application logs for user-defined function invocations containing shell metacharacters such as ;, |, &, $(), or backticks
- Implement network monitoring to detect unusual outbound connections from DataStage pods or containers
- Deploy endpoint detection solutions to identify anomalous command execution patterns within the Cloud Pak for Data environment
- Review authentication logs for accounts accessing user-defined function capabilities
Monitoring Recommendations
- Enable detailed audit logging for all user-defined function operations in IBM DataStage
- Configure SIEM rules to alert on command injection patterns in application request logs
- Monitor container and pod behavior for unexpected process creation or file system modifications
- Implement network segmentation monitoring to detect lateral movement attempts from compromised DataStage instances
How to Mitigate CVE-2025-13687
Immediate Actions Required
- Identify all IBM DataStage on Cloud Pak for Data deployments running versions 5.1.2 through 5.3.0
- Apply the security patch provided by IBM as documented in the vendor advisory
- Review access controls to limit which users can create or modify user-defined functions
- Implement network segmentation to restrict DataStage environment access to authorized users only
Patch Information
IBM has released a security update to address this command injection vulnerability. Organizations should consult the IBM Support Document for detailed patching instructions and download links. Apply the patch to all affected IBM DataStage on Cloud Pak for Data installations running versions 5.1.2 through 5.3.0 as soon as possible.
Workarounds
- Restrict access to the user-defined function feature to only trusted administrative users until patching is complete
- Implement web application firewall rules to filter common command injection payloads targeting DataStage endpoints
- Review and audit existing user-defined functions for any signs of malicious modification
- Consider temporarily disabling the user-defined function capability if it is not business-critical
# Example: Review DataStage user permissions
# Audit users with access to user-defined functions
oc get rolebindings -n <datastage-namespace> -o wide | grep datastage
# Monitor for suspicious process execution
kubectl logs -f <datastage-pod> | grep -E "(exec|system|shell|cmd)"
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

