CVE-2018-7537 in Django
Summary
by MITRE
An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. If django.utils.text.Truncator's chars() and words() methods were passed the html=True argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The chars() and words() methods are used to implement the truncatechars_html and truncatewords_html template filters, which were thus vulnerable.
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Analysis
by VulDB Data Team • 02/21/2023
The vulnerability described in CVE-2018-7537 represents a critical performance degradation issue affecting the Django web framework across multiple versions. This flaw specifically targets the django.utils.text.Truncator class which provides text truncation functionality for Django applications. The vulnerability manifests when the chars() and words() methods are invoked with the html=True parameter, triggering a catastrophic backtracking scenario within a regular expression pattern used internally by these methods. This issue affects Django versions 2.0 prior to 2.0.3, 1.11 prior to 1.11.11, and 1.8 prior to 1.8.19, indicating it has been present for several major releases and represents a long-standing security concern. The vulnerability directly impacts the truncatechars_html and truncatewords_html template filters, which are commonly used in web applications to limit the display length of text content while preserving HTML formatting. When maliciously crafted HTML input is processed through these vulnerable methods, the regular expression engine becomes overwhelmed with exponential backtracking operations, causing the application to become unresponsive or extremely slow to respond. This behavior aligns with CWE-1333, which describes improper regular expression handling that can lead to denial of service conditions through resource exhaustion. The vulnerability operates at the application layer and can be exploited through user-supplied input that flows into Django template filters, making it particularly dangerous in web applications where user input is processed. From an operational standpoint, this vulnerability creates significant risk for applications that rely on text truncation functionality, especially those handling untrusted input from users. The performance degradation can effectively render applications unusable or vulnerable to denial of service attacks, as the processing time increases exponentially with input complexity. Attackers can craft specific HTML inputs that trigger the backtracking behavior, causing servers to consume excessive CPU resources and potentially leading to system instability or complete service disruption. The impact extends beyond simple performance degradation as it can be leveraged to create resource exhaustion attacks against web applications, making it particularly concerning for high-traffic sites or applications with limited computational resources. This vulnerability directly maps to ATT&CK technique T1499.004, which involves network disruption through resource exhaustion attacks. The security implications are compounded by the fact that the affected methods are commonly used throughout Django applications, making the vulnerability widespread and difficult to fully mitigate without comprehensive code review. Organizations using affected Django versions face significant risk of application slowdowns or complete unavailability when processing certain types of user input through the vulnerable template filters. The vulnerability demonstrates the importance of proper input validation and regular expression design in web application security, as improper regex patterns can create exploitable conditions that affect system availability. The fix for this vulnerability required modifications to the regular expression patterns used within the Truncator class to eliminate the backtracking behavior, emphasizing the need for careful regex implementation in security-critical applications. This issue underscores the importance of maintaining up-to-date software versions and the potential consequences of using vulnerable libraries in production environments, particularly when those libraries handle user input processing. The vulnerability serves as a reminder that even seemingly benign text processing functions can become security risks when implemented with inadequate input handling or regular expression patterns that are susceptible to exploitation through carefully crafted inputs.