CVE-2026-56570 in iControl
Summary
by MITRE • 07/31/2026
HCL iControl was affected by Auto complete Enabled vulnerabilities. It involves expose sensitive information such as: Valid usernames, Email addresses used for login, Account identifiers If the system is accessed from shared environments, attackers may enumerate valid usernames through browser suggestions.
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Analysis
by VulDB Data Team • 07/31/2026
The HCL iControl platform suffered from a critical auto-complete enabled vulnerability that exposed sensitive authentication information through browser auto-suggestion features. This vulnerability falls under the category of information disclosure and directly impacts user authentication security by allowing unauthorized enumeration of valid account credentials. The flaw specifically affects the login interface where browsers automatically suggest previously entered usernames, email addresses, and account identifiers, creating a significant attack surface for threat actors.
This vulnerability represents a classic implementation issue that aligns with CWE-201, which focuses on information exposure through improper auto-complete functionality. When users access the system from shared or public environments, attackers can exploit the browser's auto-complete feature to systematically enumerate valid usernames and email addresses used for authentication purposes. The exposed information includes legitimate account identifiers, email addresses associated with user accounts, and potentially other sensitive credential data that could be leveraged in subsequent attack phases.
The operational impact of this vulnerability extends beyond simple information disclosure as it enables automated enumeration attacks that can be executed rapidly through browser-based auto-complete features. Attackers can leverage this weakness to build comprehensive lists of valid accounts without triggering account lockout mechanisms or other security controls designed to prevent brute force attempts. This particular vulnerability is especially dangerous in shared computing environments where multiple users access the same system, as it allows attackers to collect authentication data passively through browser behavior rather than through active exploitation techniques.
The attack surface for this vulnerability can be expanded through various threat actor methodologies that align with ATT&CK technique T1589.002, which focuses on credential access through reconnaissance and enumeration. The auto-complete feature essentially provides a passive reconnaissance mechanism that bypasses traditional authentication barriers, allowing attackers to gather intelligence about valid user accounts before attempting more sophisticated attacks such as password spraying or credential stuffing attacks.
Organizations should implement immediate mitigations including disabling auto-complete functionality for authentication forms, implementing proper input validation controls, and ensuring that browser auto-complete features are disabled for sensitive fields. The solution involves configuring web applications to explicitly set autocomplete="off" attributes on login forms while also implementing additional security controls such as account lockout mechanisms, multi-factor authentication, and monitoring for unusual enumeration patterns. These measures align with industry best practices outlined in NIST SP 800-63B and ISO/IEC 27001 standards for authentication and access control management.
Security teams should also consider implementing network-level controls to monitor for unusual login pattern behaviors that could indicate automated enumeration attempts, while ensuring that system administrators regularly audit authentication logs for signs of account discovery activities. The vulnerability demonstrates the importance of considering browser-based security features as part of the overall application security posture, particularly in environments where shared computing resources are common and where traditional network security controls may not prevent passive reconnaissance attacks.