CVE-2025-31953: CWE-798 Use of Hard-coded Credentials in HCL Software iAutomate
HCL iAutomate includes hardcoded credentials which may result in potential exposure of confidential data if intercepted or accessed by unauthorized parties.
AI Analysis
Technical Summary
CVE-2025-31953 is a high-severity vulnerability identified in HCL Software's iAutomate product, specifically version 6.5.1. The vulnerability is classified under CWE-798, which pertains to the use of hard-coded credentials within software. Hard-coded credentials are embedded directly into the application's code or configuration files, making them accessible to anyone who can inspect the software or its binaries. In this case, iAutomate includes such hard-coded credentials that could be intercepted or accessed by unauthorized parties. The CVSS 3.1 base score of 7.1 reflects a high severity, with the vector indicating that the vulnerability can be exploited remotely over the network (AV:N), requires low attack complexity (AC:L), requires privileges (PR:L), no user interaction (UI:N), and impacts confidentiality highly (C:H), integrity to a lesser extent (I:L), and does not affect availability (A:N). The presence of hard-coded credentials means that an attacker who gains network access and has some level of privileges could potentially extract these credentials and use them to escalate privileges, access confidential data, or move laterally within the environment. Since the vulnerability does not require user interaction, exploitation can be automated or performed stealthily. Although no known exploits are currently reported in the wild, the risk remains significant due to the nature of the flaw and the criticality of the data potentially exposed. The lack of available patches at the time of publication increases the urgency for organizations to implement compensating controls. Given that iAutomate is an automation platform used for orchestrating IT processes, the compromise of credentials could lead to unauthorized execution of automated tasks, exposing sensitive operational data and potentially disrupting business workflows.
Potential Impact
For European organizations, the impact of this vulnerability could be substantial. iAutomate is likely used in enterprise environments to automate critical IT and business processes, meaning that unauthorized access via hard-coded credentials could lead to exposure of confidential corporate data, intellectual property, and personal data protected under GDPR. The confidentiality impact is high, as attackers could extract sensitive information or credentials to further compromise internal systems. Integrity impact is moderate, as attackers might manipulate automated workflows or configurations, potentially causing incorrect or malicious operations. Availability is not directly affected by this vulnerability, but indirect effects could arise if automated processes are disrupted. Given the stringent data protection regulations in Europe, any data breach resulting from exploitation could lead to significant legal and financial consequences, including fines and reputational damage. Additionally, organizations in sectors such as finance, manufacturing, and critical infrastructure that rely heavily on automation tools like iAutomate may face operational risks. The vulnerability also poses a risk for supply chain attacks if attackers leverage compromised credentials to infiltrate partner or customer networks.
Mitigation Recommendations
Organizations using HCL iAutomate version 6.5.1 should immediately assess their exposure to this vulnerability. Since no official patches are currently available, the following specific mitigations are recommended: 1) Conduct a thorough code and configuration audit to identify and remove or replace hard-coded credentials with secure credential management solutions such as vaults or environment variables. 2) Restrict network access to iAutomate management interfaces using network segmentation, firewalls, and VPNs to limit exposure to trusted administrators only. 3) Implement strict access controls and monitor privileged accounts for unusual activity, as exploitation requires some level of privilege. 4) Enable detailed logging and continuous monitoring to detect any unauthorized access attempts or suspicious behavior related to iAutomate. 5) Rotate any credentials found embedded in the software immediately and ensure that any secrets are stored securely outside the application code. 6) Engage with HCL Software support to obtain timelines for official patches or updates and apply them promptly once available. 7) Consider deploying application-layer firewalls or intrusion detection/prevention systems to detect exploitation attempts targeting this vulnerability. 8) Educate IT and security teams about the risks of hard-coded credentials and enforce secure development practices to prevent recurrence.
Affected Countries
Germany, France, United Kingdom, Netherlands, Italy, Spain, Sweden, Belgium
CVE-2025-31953: CWE-798 Use of Hard-coded Credentials in HCL Software iAutomate
Description
HCL iAutomate includes hardcoded credentials which may result in potential exposure of confidential data if intercepted or accessed by unauthorized parties.
AI-Powered Analysis
Technical Analysis
CVE-2025-31953 is a high-severity vulnerability identified in HCL Software's iAutomate product, specifically version 6.5.1. The vulnerability is classified under CWE-798, which pertains to the use of hard-coded credentials within software. Hard-coded credentials are embedded directly into the application's code or configuration files, making them accessible to anyone who can inspect the software or its binaries. In this case, iAutomate includes such hard-coded credentials that could be intercepted or accessed by unauthorized parties. The CVSS 3.1 base score of 7.1 reflects a high severity, with the vector indicating that the vulnerability can be exploited remotely over the network (AV:N), requires low attack complexity (AC:L), requires privileges (PR:L), no user interaction (UI:N), and impacts confidentiality highly (C:H), integrity to a lesser extent (I:L), and does not affect availability (A:N). The presence of hard-coded credentials means that an attacker who gains network access and has some level of privileges could potentially extract these credentials and use them to escalate privileges, access confidential data, or move laterally within the environment. Since the vulnerability does not require user interaction, exploitation can be automated or performed stealthily. Although no known exploits are currently reported in the wild, the risk remains significant due to the nature of the flaw and the criticality of the data potentially exposed. The lack of available patches at the time of publication increases the urgency for organizations to implement compensating controls. Given that iAutomate is an automation platform used for orchestrating IT processes, the compromise of credentials could lead to unauthorized execution of automated tasks, exposing sensitive operational data and potentially disrupting business workflows.
Potential Impact
For European organizations, the impact of this vulnerability could be substantial. iAutomate is likely used in enterprise environments to automate critical IT and business processes, meaning that unauthorized access via hard-coded credentials could lead to exposure of confidential corporate data, intellectual property, and personal data protected under GDPR. The confidentiality impact is high, as attackers could extract sensitive information or credentials to further compromise internal systems. Integrity impact is moderate, as attackers might manipulate automated workflows or configurations, potentially causing incorrect or malicious operations. Availability is not directly affected by this vulnerability, but indirect effects could arise if automated processes are disrupted. Given the stringent data protection regulations in Europe, any data breach resulting from exploitation could lead to significant legal and financial consequences, including fines and reputational damage. Additionally, organizations in sectors such as finance, manufacturing, and critical infrastructure that rely heavily on automation tools like iAutomate may face operational risks. The vulnerability also poses a risk for supply chain attacks if attackers leverage compromised credentials to infiltrate partner or customer networks.
Mitigation Recommendations
Organizations using HCL iAutomate version 6.5.1 should immediately assess their exposure to this vulnerability. Since no official patches are currently available, the following specific mitigations are recommended: 1) Conduct a thorough code and configuration audit to identify and remove or replace hard-coded credentials with secure credential management solutions such as vaults or environment variables. 2) Restrict network access to iAutomate management interfaces using network segmentation, firewalls, and VPNs to limit exposure to trusted administrators only. 3) Implement strict access controls and monitor privileged accounts for unusual activity, as exploitation requires some level of privilege. 4) Enable detailed logging and continuous monitoring to detect any unauthorized access attempts or suspicious behavior related to iAutomate. 5) Rotate any credentials found embedded in the software immediately and ensure that any secrets are stored securely outside the application code. 6) Engage with HCL Software support to obtain timelines for official patches or updates and apply them promptly once available. 7) Consider deploying application-layer firewalls or intrusion detection/prevention systems to detect exploitation attempts targeting this vulnerability. 8) Educate IT and security teams about the risks of hard-coded credentials and enforce secure development practices to prevent recurrence.
Affected Countries
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Technical Details
- Data Version
- 5.1
- Assigner Short Name
- HCL
- Date Reserved
- 2025-04-01T18:46:19.517Z
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 68829beead5a09ad004432d9
Added to database: 7/24/2025, 8:47:42 PM
Last enriched: 8/1/2025, 1:06:48 AM
Last updated: 8/31/2025, 5:36:39 AM
Views: 27
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