CVE-2024-52585 in Autolab
Summary
by MITRE • 11/18/2024
Autolab is a course management service that enables auto-graded programming assignments. There is an HTML injection vulnerability in version 3.0.1 that can affect instructors and CAs on the grade submissions page. The issue is patched in version 3.0.2. One may apply the patch manually by editing line 589 on `gradesheet.js.erb` to take in feedback as text rather than html.
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Analysis
by VulDB Data Team • 01/22/2025
The CVE-2024-52585 vulnerability represents a critical HTML injection flaw within the Autolab course management platform, specifically affecting version 3.0.1. This system serves as an automated grading service for programming assignments, making it a vital component in academic computing education environments. The vulnerability manifests on the grade submissions page where instructors and course assistants interact with student submissions, creating a potential attack vector that could compromise the integrity of the grading process and student data. The flaw stems from improper handling of user-provided feedback content, allowing malicious actors to inject HTML code that executes within the browser context of authorized users.
The technical implementation of this vulnerability resides in the gradesheet.js.erb file at line 589, where the application fails to properly sanitize or escape user input before rendering it as HTML content. This represents a classic Cross-Site Scripting (XSS) vulnerability classified under CWE-79, which occurs when web applications include untrusted data in web pages without proper validation or escaping. The vulnerability specifically affects the feedback submission functionality where instructors and course assistants enter comments or notes about student submissions. When malicious HTML code is injected into these fields, it gets rendered as part of the page content, potentially executing scripts in the context of the victim's browser session.
The operational impact of this vulnerability extends beyond simple data corruption, as it enables attackers to perform several malicious activities within the Autolab environment. Authorized users could be subjected to session hijacking attacks, where attackers steal authentication tokens and impersonate legitimate users to access confidential student information or modify grades. The vulnerability also enables phishing attacks where attackers craft convincing fake interfaces that appear to be legitimate Autolab components, tricking users into revealing sensitive information. Additionally, the injection could be used to redirect users to malicious websites or download malware, creating a broader security threat to the entire academic institution's computing infrastructure. This type of attack aligns with ATT&CK technique T1531 which focuses on 'Modify System Image' and T1059 which covers 'Command and Scripting Interpreter' through malicious script execution.
The patch implementation for CVE-2024-52585 requires manual intervention by modifying the gradesheet.js.erb file to treat feedback content as plain text rather than HTML. This approach follows the principle of input sanitization and output escaping, which are fundamental defensive measures against XSS vulnerabilities. The recommended fix involves ensuring that user-provided feedback is properly escaped before being rendered in the browser context, preventing the execution of embedded HTML or JavaScript code. This remediation strategy aligns with industry best practices for secure web application development and addresses the root cause of the vulnerability. Organizations should implement automated patch management processes to ensure timely deployment of security updates, while also conducting thorough testing to verify that the patch does not introduce regressions in the grading functionality. The vulnerability highlights the importance of proper input validation in web applications and demonstrates how seemingly innocuous feedback fields can become attack vectors when not properly secured against malicious input.