CVE-2017-14158 in Scrapy
Summary
by MITRE
Scrapy 1.4 allows remote attackers to cause a denial of service (memory consumption) via large files because arbitrarily many files are read into memory, which is especially problematic if the files are then individually written in a separate thread to a slow storage resource, as demonstrated by interaction between dataReceived (in core/downloader/handlers/http11.py) and S3FilesStore.
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Analysis
by VulDB Data Team • 12/27/2022
The vulnerability identified as CVE-2017-14158 affects Scrapy version 1.4 and represents a significant denial of service weakness that can be exploited remotely through memory exhaustion attacks. This flaw stems from the web scraping framework's handling of large file downloads where the system reads arbitrarily many files into memory without proper size limitations or memory management controls. The issue becomes particularly severe when combined with asynchronous processing patterns that involve writing data to slow storage resources through separate threads, creating a cascading memory consumption problem that can overwhelm system resources and render the application unusable.
The technical implementation of this vulnerability occurs within the core downloader handlers of Scrapy, specifically in the dataReceived method located in core/downloader/handlers/http11.py. This method processes incoming HTTP data streams and passes them to the S3FilesStore component for storage operations. The flaw manifests when the system encounters large files that are downloaded and immediately loaded into memory buffers without any size validation or memory allocation limits. The combination of reading large files into memory and then asynchronously writing them to slow storage targets like Amazon S3 creates a memory pressure scenario where multiple large files can accumulate in memory simultaneously, leading to excessive memory consumption and eventual system crash or unresponsiveness.
The operational impact of this vulnerability extends beyond simple service disruption to encompass potential system instability and resource exhaustion across multiple attack vectors. Attackers can exploit this weakness by crafting malicious web responses or by targeting websites that serve large files, causing the Scrapy spider to consume increasing amounts of memory until the system either crashes or becomes unresponsive. The asynchronous nature of the storage operations exacerbates the problem as the memory consumption continues even while the writing operations to slow storage resources are in progress, creating a memory leak scenario that can be difficult to detect and mitigate in production environments. This vulnerability directly aligns with CWE-400, which addresses the weakness of unrestricted resource consumption, and can be mapped to ATT&CK technique T1499.001 for resource exhaustion attacks.
Mitigation strategies for this vulnerability require implementing multiple layers of protection within the Scrapy framework and its underlying components. The most effective approach involves adding size limitations and memory constraints to the dataReceived method, implementing proper buffer management, and introducing rate limiting for file downloads. Organizations should configure maximum file size limits within their Scrapy spiders and implement memory monitoring mechanisms to detect and prevent excessive memory consumption. Additionally, the framework should be updated to include proper asynchronous resource management that prevents memory accumulation during slow storage write operations. Security teams should also consider implementing network-level controls and monitoring for unusual memory consumption patterns that could indicate exploitation attempts. The vulnerability highlights the importance of proper resource management in asynchronous programming patterns and demonstrates how seemingly benign file handling operations can become critical security concerns when combined with improper memory allocation practices.