CVE-2017-18926 in RDF Syntax Library
Summary
by MITRE • 11/07/2020
raptor_xml_writer_start_element_common in raptor_xml_writer.c in Raptor RDF Syntax Library 2.0.15 miscalculates the maximum nspace declarations for the XML writer, leading to heap-based buffer overflows (sometimes seen in raptor_qname_format_as_xml).
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Analysis
by VulDB Data Team • 05/18/2025
The vulnerability identified as CVE-2017-18926 resides within the Raptor RDF Syntax Library version 2015, specifically affecting the raptor_xml_writer_start_element_common function in the raptor_xml_writer.c file. This flaw represents a critical heap-based buffer overflow condition that occurs during XML writing operations when processing namespace declarations. The vulnerability stems from an incorrect calculation of maximum namespace declarations, which directly impacts the memory allocation and handling of XML elements within the library's processing pipeline. The issue manifests particularly when the raptor_qname_format_as_xml function is invoked, creating a scenario where insufficient buffer sizing leads to memory corruption. Such buffer overflows are classified under CWE-121 as heap-based buffer overflow conditions, where insufficient bounds checking allows attackers to write beyond allocated memory regions. The vulnerability demonstrates characteristics consistent with CWE-787, which describes out-of-bounds write conditions, and aligns with ATT&CK technique T1059.007 for execution through command-line interface, as exploitation could potentially lead to arbitrary code execution.
The technical implementation of this vulnerability involves the improper handling of namespace declaration calculations during XML element processing. When the library encounters XML elements with multiple namespace declarations, the miscalculation in maximum namespace declarations causes the system to allocate insufficient memory buffers for storing these declarations. This miscalculation typically occurs in scenarios where namespace prefixes are dynamically generated or when complex XML structures are processed. The buffer overflow manifests when the system attempts to write namespace information beyond the pre-allocated memory boundaries, potentially overwriting adjacent memory regions including stack canaries, return addresses, or other critical program data. The vulnerability is particularly concerning because it operates within a widely used RDF processing library, meaning that any application or system utilizing Raptor for RDF data processing could be susceptible to this memory corruption issue.
The operational impact of CVE-2017-18926 extends beyond simple memory corruption, as it creates potential attack vectors for remote code execution and system compromise. An attacker could craft malicious RDF data containing specially formatted XML elements with excessive namespace declarations to trigger the buffer overflow condition. The vulnerability's exploitation potential aligns with ATT&CK tactic TA0002 (execution) and TA0004 (privilege escalation) when successful exploitation occurs, as the memory corruption could allow for arbitrary code execution within the context of the affected application. Applications using the vulnerable library include web servers processing RDF content, content management systems handling semantic web data, and any software performing RDF data processing or transformation. The vulnerability's presence in the Raptor library means that the attack surface spans across multiple domains including web applications, data processing systems, and semantic web services that rely on RDF for data representation and exchange.
Mitigation strategies for CVE-2017-18926 focus on immediate library updates and defensive programming practices. The primary solution involves upgrading to Raptor library versions 2.0.16 or later, where the namespace declaration calculation has been corrected to properly allocate memory buffers. Organizations should conduct comprehensive vulnerability assessments to identify all systems utilizing the affected library version and prioritize remediation efforts accordingly. Additional defensive measures include implementing input validation and sanitization for RDF data processing, employing memory protection mechanisms such as stack canaries and address space layout randomization, and deploying intrusion detection systems to monitor for exploitation attempts. The vulnerability highlights the importance of proper memory management in XML processing libraries and underscores the need for thorough testing of boundary conditions, particularly in functions handling dynamic content generation and namespace management. Security teams should also consider implementing application-level restrictions on namespace declaration counts and monitor for unusual XML processing patterns that could indicate exploitation attempts.