CVE-2017-9229 in Oniguruma
Summary
by MITRE
An issue was discovered in Oniguruma 6.2.0, as used in Oniguruma-mod in Ruby through 2.4.1 and mbstring in PHP through 7.1.5. A SIGSEGV occurs in left_adjust_char_head() during regular expression compilation. Invalid handling of reg->dmax in forward_search_range() could result in an invalid pointer dereference, normally as an immediate denial-of-service condition.
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Analysis
by VulDB Data Team • 12/07/2022
The vulnerability identified as CVE-2017-9229 represents a critical memory safety issue affecting regular expression processing libraries within widely-used programming environments. This flaw exists in Oniguruma 6.2.0, a popular regular expression engine that serves as the foundation for text processing capabilities in both Ruby and PHP implementations. The vulnerability manifests during the compilation phase of regular expressions, specifically when handling certain malformed input patterns that trigger unexpected memory access patterns.
The technical root cause of this vulnerability lies in improper memory management within the Oniguruma library's regular expression compilation routines. The primary issue occurs in the left_adjust_char_head() function where a segmentation fault can be triggered during regular expression parsing. Additionally, the forward_search_range() function contains a flaw in how it handles the reg->dmax variable, which leads to invalid pointer dereference conditions. This combination of memory handling errors creates a scenario where maliciously crafted regular expressions can cause the application to crash or behave unpredictably.
The operational impact of CVE-2017-9229 extends beyond simple denial-of-service conditions, as it can potentially be exploited to achieve more severe consequences in vulnerable environments. When applications process user-supplied regular expressions without proper input validation, attackers can craft malicious patterns that trigger the SIGSEGV condition, causing applications to terminate unexpectedly. This vulnerability affects Ruby versions through 2.4.1 and PHP versions through 7.1.5, representing a significant portion of production environments that rely on these platforms for web applications and server-side processing. The vulnerability maps to CWE-125, which describes out-of-bounds read conditions, and CWE-476, which covers null pointer dereference scenarios.
The exploitability of this vulnerability is enhanced by the widespread use of regular expressions in web applications and the common practice of accepting user input without proper sanitization. Attackers can leverage this issue to perform denial-of-service attacks against applications that process untrusted input through regular expression operations. The attack surface includes any application that utilizes the affected versions of Ruby or PHP, particularly those handling user-generated content or implementing pattern matching functionality. From an ATT&CK framework perspective, this vulnerability aligns with T1499.004, which covers network disruption through resource exhaustion, and T1589.002, which involves exploiting vulnerabilities in commonly used software libraries. Organizations should prioritize patching affected systems and implementing proper input validation measures to prevent exploitation of this memory safety flaw.
Mitigation strategies for CVE-2017-9229 require immediate attention from system administrators and developers. The primary recommendation involves upgrading to patched versions of Oniguruma, Ruby, and PHP that address the memory handling issues in the regular expression processing libraries. Additionally, implementing strict input validation and sanitization measures for all user-supplied regular expressions can significantly reduce the attack surface. Organizations should also consider implementing application-level protections such as regular expression timeout mechanisms and resource limiting to prevent exploitation attempts. The vulnerability demonstrates the importance of maintaining up-to-date software libraries and implementing comprehensive security testing practices that include fuzzing and memory safety analysis to identify similar issues before they can be exploited in production environments.