CVE-2015-0221 in Django
Summary
by MITRE
The django.views.static.serve view in Django before 1.4.18, 1.6.x before 1.6.10, and 1.7.x before 1.7.3 reads files an entire line at a time, which allows remote attackers to cause a denial of service (memory consumption) via a long line in a file.
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Analysis
by VulDB Data Team • 03/08/2022
The vulnerability identified as CVE-2015-0221 affects the django.views.static.serve view in Django web applications, representing a classic denial of service flaw that impacts multiple versions of the popular Python web framework. This issue specifically targets the file serving mechanism used by Django applications, where the static file handler processes files line-by-line without proper memory management controls. The vulnerability exists in versions prior to 1.4.18, 1.6.10, and 1.7.3, indicating a long-standing flaw that affected a significant portion of Django deployments. The flaw stems from the implementation's inability to handle files containing extremely long lines, which causes the application to consume excessive memory during file processing, ultimately leading to system resource exhaustion.
The technical root cause of this vulnerability lies in the inefficient file reading implementation within Django's static file serving functionality. When the static.serve view encounters a file with a very long line, it reads the entire line into memory at once rather than processing it in chunks or implementing proper buffer management. This approach creates a memory consumption pattern where the application allocates memory proportional to the length of the longest line in the file being served. The vulnerability is classified under CWE-400 as an Uncontrolled Resource Consumption, specifically manifesting as a memory exhaustion attack that can be triggered remotely by sending requests to static file endpoints. The flaw operates at the application layer and can be exploited without authentication, making it particularly dangerous in production environments where static files are publicly accessible.
The operational impact of this vulnerability extends beyond simple denial of service, potentially affecting entire web applications and the underlying infrastructure hosting them. Attackers can exploit this weakness by uploading or referencing files containing extremely long lines, causing the Django application to consume all available memory and eventually crash or become unresponsive. This type of attack can be particularly devastating in cloud environments where memory resources are limited and shared among multiple applications. The vulnerability creates a scenario where a single malicious request can cause cascading failures, affecting not just the targeted application but potentially other services running on the same infrastructure. From an attacker's perspective, this represents a low-effort, high-impact method for disrupting services, as demonstrated by the ATT&CK technique T1499.200 which covers resource exhaustion attacks targeting application availability.
Organizations affected by this vulnerability should immediately implement mitigations including updating to patched versions of Django, which properly handle long lines in file processing by implementing memory limits and chunked reading approaches. Additional protective measures include implementing rate limiting on static file requests, configuring memory limits for application processes, and deploying monitoring systems to detect unusual memory consumption patterns. Network-level protections such as web application firewalls can also help identify and block malicious requests attempting to exploit this vulnerability. The fix implemented in patched versions typically involves modifying the file reading logic to process data in fixed-size buffers rather than reading entire lines, thereby preventing unbounded memory allocation. Security teams should also conduct thorough audits of their static file serving configurations and ensure that all Django applications are running patched versions to prevent exploitation of this and similar resource exhaustion vulnerabilities.