CVE-2022-30464 in ChatBot App with Suggestion
Summary
by MITRE • 05/24/2022
ChatBot App with Suggestion in PHP/OOP v1.0 is vulnerable to Cross Site Scripting (XSS) via /simple_chat_bot/classes/Master.php?f=save_response.
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Analysis
by VulDB Data Team • 05/29/2022
The vulnerability identified as CVE-2022-30464 affects the ChatBot App with Suggestion in PHP/OOP version 1.0, specifically targeting the /simple_chat_bot/classes/Master.php file with the f=save_response parameter. This represents a critical cross site scripting flaw that allows malicious actors to inject arbitrary javascript code into the application's response handling mechanism. The vulnerability stems from insufficient input validation and output sanitization within the application's backend processing logic, creating an attack surface where user-supplied data can be executed in the context of other users' browsers.
The technical exploitation of this vulnerability occurs through the save_response function parameter, which processes user inputs without proper sanitization before storing or returning them to clients. When an attacker crafts malicious input containing javascript payloads and submits it through the chatbot interface, the application fails to properly escape or filter the content, allowing the malicious script to execute in the victim's browser. This vulnerability falls under CWE-79 which specifically addresses cross site scripting flaws in web applications, where the application fails to properly validate or sanitize user-provided data before incorporating it into dynamically generated web pages.
The operational impact of this vulnerability is significant as it enables attackers to perform various malicious activities including session hijacking, credential theft, data exfiltration, and defacement of the chatbot interface. An attacker could potentially steal user session cookies, redirect victims to malicious sites, or inject persistent malware that executes in the context of authenticated users. The attack surface is particularly concerning in chatbot applications where users may trust the interface and interact with it regularly, making successful exploitation more likely to result in sustained compromise. This vulnerability directly maps to attack techniques described in the MITRE ATT&CK framework under T1531 and T1059, which cover credential access and execution through malicious scripts.
Mitigation strategies should focus on implementing comprehensive input validation and output encoding mechanisms throughout the application's data flow. The most effective approach involves sanitizing all user inputs using proper escaping techniques before processing or storing them, particularly for HTML content that will be rendered in web browsers. Implementing Content Security Policy headers can provide additional protection against script execution, while regular security code reviews and automated scanning should be conducted to identify similar vulnerabilities in other application components. The application should also implement proper parameter validation and utilize prepared statements or similar mechanisms to prevent injection attacks. Organizations should ensure that all user inputs are properly escaped using context-appropriate encoding methods such as HTML entity encoding for web content and proper database escaping for storage operations.