CVE-2017-12962 in LibSass
Summary
by MITRE
There are memory leaks in LibSass 3.4.5 triggered by deeply nested code, such as code with a long sequence of open parenthesis characters, leading to a remote denial of service attack.
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Analysis
by VulDB Data Team • 11/09/2019
The vulnerability identified as CVE-2017-12962 represents a critical memory leak issue within LibSass version 3.4.5 that manifests through deeply nested code structures. This flaw specifically targets the Sass preprocessor library commonly used in web development environments, creating a remote denial of service condition when maliciously crafted code is processed. The vulnerability stems from the library's inability to properly handle excessive nesting levels during the parsing phase, particularly when encountering prolonged sequences of opening parenthesis characters that create deeply nested syntax structures.
The technical implementation of this vulnerability exploits the recursive parsing mechanisms inherent in LibSass's compiler architecture. When the parser encounters deeply nested code with excessive opening parentheses, it creates a cascade of recursive function calls that consume increasing amounts of memory without proper cleanup. This memory allocation pattern continues until system resources are exhausted, resulting in the application crashing or becoming unresponsive. The flaw operates at the parsing layer of the Sass compilation process, making it particularly dangerous as it can be triggered by processing any maliciously constructed stylesheet regardless of the user's privileges or authentication status.
From an operational perspective, this vulnerability creates significant risk for web applications that utilize LibSass for dynamic stylesheet compilation. Attackers can remotely exploit this weakness by submitting specially crafted Sass code that triggers the memory leak condition, potentially causing denial of service across entire web applications or services that depend on the affected library. The impact extends beyond individual applications to encompass entire infrastructure components that rely on Sass processing, as the memory consumption grows exponentially with nesting depth. This vulnerability particularly affects server-side rendering environments where Sass files are compiled dynamically in response to user requests, creating a persistent threat vector for remote attackers.
The vulnerability aligns with CWE-401, which addresses improper handling of memory allocation failures, and demonstrates characteristics consistent with attack patterns found in the MITRE ATT&CK framework under the execution and privilege escalation categories. Organizations implementing LibSass in production environments face substantial risk as this vulnerability can be exploited without requiring authentication or elevated privileges, making it particularly attractive to threat actors seeking to disrupt services. The memory leak occurs during the compilation phase rather than runtime execution, which means that even legitimate code with excessive nesting could potentially trigger the issue if processed under specific conditions.
Mitigation strategies for CVE-2017-12962 primarily involve immediate version upgrades to LibSass 3.4.6 or later, which contain patches addressing the recursive parsing behavior that causes the memory leaks. Organizations should implement input validation and sanitization measures to prevent processing of excessively nested code structures, particularly in environments where user-generated content is processed. Additionally, deploying resource limits and monitoring systems can help detect and prevent exploitation attempts by identifying unusual memory consumption patterns. Security teams should also consider implementing automated scanning tools to identify vulnerable versions of LibSass within their codebases and establish regular patching schedules to maintain protection against similar vulnerabilities. The fix implemented in subsequent versions typically involves adding recursion depth limits and improved memory management to prevent the exponential growth of memory allocation during parsing operations.