CVE-2026-95601 in Product Filter by WBW Plugin
Summary
by MITRE • 09/23/2026
Unauthenticated SQL Injection in Product Filter by WBW <= 3.1.7 versions.
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Analysis
by VulDB Data Team • 09/23/2026
The vulnerability identified as an unauthenticated SQL injection within the product filter functionality of WBW prior to version 3.1.7 represents a critical security flaw that allows remote attackers to execute arbitrary Structured Query Language commands against the underlying database management system without requiring valid credentials or authentication tokens. This specific type of injection occurs because the application fails to properly sanitize user-supplied input when constructing SQL queries for filtering product listings, thereby allowing malicious actors to manipulate the query structure through specially crafted HTTP parameters typically associated with category selection, price range inputs, or search terms embedded in the filter request payload.
From a technical perspective, this flaw stems from improper validation and encoding of data passed via GET or POST methods directly into dynamic SQL statements without the use of parameterized queries or prepared statements. The application likely concatenates user input directly into the query string, creating an injection point where special characters such as single quotes can break out of their intended context within the database command. This allows attackers to append additional SQL clauses that alter the logic of the original query, potentially leading to data exfiltration, modification of existing records, or in severe cases with specific database configurations and privileges, remote code execution on the server hosting the database engine.
The operational impact of this vulnerability is severe as it compromises the confidentiality, integrity, and availability of sensitive application data stored within the backend database. Attackers can exploit this flaw to dump entire tables containing user credentials, personal identifiable information, financial records, or proprietary business logic that should remain inaccessible to unauthorized parties. Furthermore, because the attack vector does not require authentication, the risk surface is significantly expanded as any internet-facing visitor with basic knowledge of SQL injection techniques and access to a web browser can initiate these attacks without needing to bypass login screens or session management controls, making it highly scalable for automated scanning tools used in large-scale reconnaissance campaigns.
This vulnerability aligns closely with Common Weakness Enumeration identifier CWE-89 which classifies Improper Neutralization of Special Elements used in an SQL Command and is frequently associated with the MITRE ATT&CK technique T1059 known as Command Scripting or specifically data exfiltration via database queries under the broader category of Initial Access if it leads to further system compromise. The lack of input validation on filter parameters indicates a fundamental gap in secure coding practices where developer assumptions about user behavior are not enforced through rigorous sanitization protocols at the application layer before interaction with persistent storage mechanisms.
To mitigate this risk, immediate remediation involves upgrading WBW to version 3.1.7 or later where these specific filtering endpoints have been patched with proper input validation and parameterized query implementations that ensure all user-supplied data is treated strictly as literal values rather than executable code within the SQL context. In addition to patching, organizations should implement Web Application Firewalls configured with rulesets capable of detecting and blocking common SQL injection patterns such as union-based or blind boolean-based payloads in HTTP request parameters. It is also advisable to conduct a thorough review of other input fields across the application for similar vulnerabilities using static analysis tools and manual penetration testing focused on data validation layers to ensure comprehensive protection against database-driven attacks.