CVE-2022-25317 in Cerebrate
Summary
by MITRE • 02/18/2022
An issue was discovered in Cerebrate through 1.4. genericForm allows reflected XSS in form descriptions via a user-controlled description.
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Analysis
by VulDB Data Team • 05/31/2026
The vulnerability identified in Cerebrate versions through 1.4 represents a critical reflected cross-site scripting flaw that resides within the genericForm functionality. This issue manifests when user-controlled description parameters are not properly sanitized or encoded before being rendered in form descriptions, creating an avenue for malicious actors to inject arbitrary javascript code. The vulnerability operates through the reflection mechanism where attacker-supplied input is immediately reflected back to the user without adequate output encoding, allowing for the execution of malicious scripts in the context of the victim's browser session.
The technical implementation of this vulnerability stems from insufficient input validation and output encoding practices within the form description rendering pipeline. When users submit form descriptions containing malicious payloads, these inputs are processed and displayed without proper sanitization, enabling attackers to craft payloads that execute in the victim's browser context. The vulnerability specifically affects the genericForm component which serves as a flexible form creation tool, making it particularly dangerous as it can be leveraged across multiple form types and configurations. This flaw aligns with CWE-79 which categorizes cross-site scripting vulnerabilities as a result of insufficient output encoding or filtering of user-controllable data.
The operational impact of this vulnerability extends beyond simple script execution, as it can enable sophisticated attack vectors including session hijacking, credential theft, and redirection to malicious sites. An attacker could craft a malicious form description containing a payload that steals authentication cookies or redirects users to phishing sites when the form is viewed by other users. The reflected nature of this vulnerability means that the attack payload must be delivered through social engineering or direct user interaction, as the malicious code is reflected back from the server in response to user input. This characteristic makes the vulnerability particularly challenging to detect and prevent without proper input validation mechanisms.
Security practitioners should implement comprehensive input validation and output encoding measures to address this vulnerability. The recommended mitigation includes implementing strict input sanitization routines that remove or encode potentially dangerous characters before processing user input, alongside robust output encoding mechanisms that ensure all user-controllable data is properly escaped when rendered in HTML contexts. Additionally, implementing content security policies can provide an additional layer of defense by restricting the sources from which scripts can be executed within the application context. The vulnerability demonstrates the importance of following secure coding practices and adhering to established security frameworks that emphasize the principle of least privilege and defense in depth. Organizations should also consider implementing automated security scanning tools that can detect similar patterns in their codebase and establish proper security awareness training for developers to prevent similar issues in future implementations. This vulnerability serves as a reminder of the critical importance of input validation and output encoding in preventing cross-site scripting attacks, particularly in applications that handle user-generated content.