CVE-2025-62319: Boolean-Based SQL Injection Vulnerability

CVE-2025-62319 Overview

CVE-2025-62319 is a Boolean-Based SQL Injection vulnerability that allows attackers to manipulate SQL queries by injecting Boolean conditions (TRUE or FALSE) into application input fields. Instead of returning database errors or visible data, the application responds differently depending on whether the injected condition evaluates to true or false. This allows an attacker to inject arbitrary SQL into backend configuration queries executed within the application, potentially leading to complete database compromise.

Critical Impact

This vulnerability enables unauthenticated remote attackers to extract sensitive data, modify database contents, and potentially achieve full system compromise through SQL injection attacks that bypass traditional error-based detection methods.

Affected Products

• HCL Software (specific product details available in vendor advisory)

Discovery Timeline

• 2026-03-16 - CVE CVE-2025-62319 published to NVD
• 2026-03-17 - Last updated in NVD database

Technical Details for CVE-2025-62319

Vulnerability Analysis

This vulnerability is classified under CWE-89 (Improper Neutralization of Special Elements used in an SQL Command), commonly known as SQL Injection. The application fails to properly sanitize user-supplied input before incorporating it into SQL queries executed against the backend database.

Boolean-based blind SQL injection is particularly insidious because it does not rely on visible error messages or direct data extraction. Instead, attackers craft payloads that cause the application to exhibit different behaviors (such as different response times, content lengths, or HTTP status codes) based on whether injected SQL conditions evaluate to TRUE or FALSE.

The network-accessible attack vector, combined with no authentication requirements, means that any remote attacker can exploit this vulnerability without needing valid credentials or user interaction. Successful exploitation can result in unauthorized access to sensitive information stored in the database, modification or deletion of data, and in some cases, command execution on the underlying server.

Root Cause

The root cause of this vulnerability lies in insufficient input validation and the direct incorporation of user-controlled data into SQL queries without proper parameterization or prepared statements. The application constructs SQL queries dynamically using string concatenation with unsanitized user input, allowing attackers to break out of the intended query structure and inject malicious SQL code.

When Boolean conditions are injected, the database evaluates these conditions and returns results that affect application behavior. By systematically testing different conditions, attackers can infer database structure, extract data character by character, and ultimately compromise the entire database.

Attack Vector

The attack is conducted remotely over the network without requiring authentication or user interaction. An attacker identifies vulnerable input fields that are incorporated into SQL queries and crafts payloads containing Boolean logic. By observing how the application responds to conditions like ' AND 1=1-- versus ' AND 1=2--, the attacker can determine when injected SQL is being executed.

The exploitation technique involves methodically testing conditions to extract information bit by bit. For example, an attacker might use payload variations to determine if specific characters exist in database fields, gradually reconstructing sensitive data such as usernames, passwords, or configuration details.

For detailed technical information and remediation guidance, refer to the HCL Software Knowledge Base Article.

Detection Methods for CVE-2025-62319

Indicators of Compromise

• Unusual database query patterns containing Boolean logic operators such as AND 1=1, AND 1=2, OR 1=1
• Application logs showing suspicious input containing SQL syntax characters like single quotes, double dashes, or semicolons
• Database logs indicating repeated queries with incrementing or systematic variations in conditions
• Anomalous response time patterns suggesting time-based SQL injection attempts
• Unexpected database access patterns or data extraction from sensitive tables

Detection Strategies

• Implement Web Application Firewalls (WAF) with SQL injection detection rules to identify and block malicious payloads
• Deploy database activity monitoring solutions to detect anomalous query patterns and unauthorized data access
• Enable detailed application logging for input validation failures and suspicious request parameters
• Use intrusion detection systems (IDS) configured with SQL injection signatures targeting Boolean-based techniques

Monitoring Recommendations

• Monitor HTTP request parameters for SQL metacharacters and Boolean operators
• Implement real-time alerting on database query anomalies, including unusual WHERE clause conditions
• Track response time variances that may indicate time-based SQL injection probing
• Establish baseline application behavior metrics to detect deviations indicative of exploitation attempts

How to Mitigate CVE-2025-62319

Immediate Actions Required

• Review and apply vendor patches as referenced in the HCL Software Knowledge Base Article
• Audit application code for SQL injection vulnerabilities, particularly in areas handling user input
• Implement parameterized queries (prepared statements) across all database interactions
• Deploy Web Application Firewall (WAF) rules specifically targeting SQL injection attack patterns
• Restrict database account privileges to the minimum necessary for application functionality

Patch Information

Vendor patch information and remediation guidance are available through the HCL Software Knowledge Base Article. Organizations should consult this resource for specific patch versions and deployment instructions applicable to their environments.

Workarounds

• Implement strict input validation using allowlists for expected data formats and character sets
• Use stored procedures with parameterized inputs to abstract direct SQL query construction
• Deploy network-level controls such as WAF rules to filter requests containing SQL injection patterns
• Enable database query logging and implement monitoring to detect and respond to exploitation attempts
• Consider implementing application-level rate limiting to slow down automated exploitation tools

# Example WAF rule configuration for SQL injection mitigation
# ModSecurity example rule
SecRule REQUEST_URI|ARGS|ARGS_NAMES "@detectSQLi" \
    "id:1001,\
    phase:2,\
    deny,\
    status:403,\
    msg:'SQL Injection Attempt Detected',\
    log,\
    auditlog"