CVE-2017-15010 in Tough-Cookie Module
Summary
by MITRE
A ReDoS (regular expression denial of service) flaw was found in the tough-cookie module before 2.3.3 for Node.js. An attacker that is able to make an HTTP request using a specially crafted cookie may cause the application to consume an excessive amount of CPU.
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Analysis
by VulDB Data Team • 12/30/2022
The vulnerability identified as CVE-2017-15010 represents a critical regular expression denial of service flaw within the tough-cookie module version 2.3.2 and earlier, affecting Node.js applications that process HTTP cookies. This vulnerability resides in the cookie parsing mechanism where the module employs regular expressions to validate and parse cookie attributes, creating an opportunity for malicious actors to exploit the predictable pattern matching behavior of these expressions. The flaw specifically impacts applications that rely on the tough-cookie library for handling HTTP cookie management, making it particularly dangerous in web applications where cookie parsing occurs during request processing.
The technical implementation of this vulnerability stems from the use of inefficient regular expressions within the cookie parsing logic that can be manipulated to cause catastrophic backtracking. When an attacker crafts a malicious cookie header containing specially constructed regular expression patterns, the parsing algorithm enters into an exponential time complexity execution path where the regular expression engine attempts to match the input against multiple possible combinations. This behavior creates a denial of service condition where the application consumes excessive CPU resources, potentially leading to application unresponsiveness or complete system exhaustion. The vulnerability maps to CWE-400, which specifically addresses unchecked resource consumption, and falls under the broader category of path traversal and input validation issues.
The operational impact of this vulnerability extends beyond simple service disruption to potentially enable more sophisticated attack vectors when combined with other weaknesses. Applications utilizing the affected module become vulnerable to resource exhaustion attacks that can be triggered through HTTP requests containing maliciously crafted cookies, making this particularly dangerous in high-traffic web applications or API endpoints where cookie parsing occurs frequently. Attackers can exploit this vulnerability with minimal resources, simply by sending a specially crafted HTTP request with an obfuscated cookie value that causes the application to enter an infinite loop or extremely long processing time. This vulnerability is particularly concerning in cloud environments and microservices architectures where resource exhaustion can cascade across multiple application instances.
Mitigation strategies for CVE-2017-15010 involve immediate patching of the tough-cookie module to version 2.3.3 or later, which includes fixed regular expression patterns that prevent catastrophic backtracking. Organizations should also implement input validation and sanitization measures at multiple layers of their application architecture, including web application firewalls that can detect and block suspicious cookie patterns before they reach the vulnerable parsing logic. Network-level protections such as rate limiting and connection pooling can provide additional defense-in-depth measures to prevent exploitation attempts. Security monitoring should include detection of unusual CPU consumption patterns in applications processing HTTP cookies, while application developers should consider implementing timeouts for cookie parsing operations and validating cookie content against known safe patterns. The vulnerability demonstrates the importance of regular security auditing of third-party libraries and maintaining up-to-date dependencies as outlined in ATT&CK technique T1595.001 for reconnaissance and T1496 for resource exhaustion attacks, emphasizing the need for comprehensive vulnerability management programs that address both known and emerging threats in the Node.js ecosystem.