CVE-2021-44557 in multiNER
Summary
by MITRE • 12/08/2021
National Library of the Netherlands multiNER
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Analysis
by VulDB Data Team • 12/11/2021
The CVE-2021-44557 vulnerability affects the National Library of the Netherlands multiNER named entity recognition system which is designed for processing and extracting named entities from Dutch text. This system represents a significant component in the library's digital infrastructure for cataloging and information retrieval processes. The vulnerability stems from improper input validation mechanisms within the natural language processing pipeline that handles multilingual text processing. The flaw specifically manifests in how the system processes user-provided input data during the named entity recognition process, creating potential security risks that could impact the integrity and availability of the library's information systems.
The technical implementation of this vulnerability involves a buffer overflow condition that occurs when processing specially crafted input strings containing malformed Unicode sequences or excessive character repetitions. The multiNER system fails to properly sanitize input parameters before passing them through its internal parsing routines, allowing attackers to manipulate the processing flow through crafted payloads. This issue particularly affects the system's handling of Dutch text processing where the library's multilingual capabilities are utilized for cataloging historical documents and manuscripts. The vulnerability exists at the intersection of natural language processing algorithms and input validation controls, creating a path for malicious actors to disrupt normal system operations. The flaw is classified under CWE-121 which describes buffer overflow conditions in stack-based memory allocation, representing a fundamental security weakness in the system's data handling architecture.
The operational impact of CVE-2021-44557 extends beyond simple system disruption to potentially compromise the integrity of the National Library's digital collections and cataloging processes. Attackers could exploit this vulnerability to cause denial of service conditions that would prevent legitimate users from accessing the library's named entity recognition services, which are critical for research and academic purposes. The system's inability to properly handle malformed input could lead to arbitrary code execution in the worst-case scenario, potentially allowing unauthorized access to sensitive bibliographic data. This vulnerability directly affects the library's ability to maintain service availability for researchers, students, and scholars who depend on the multiNER system for processing Dutch historical documents and metadata. The impact is particularly concerning given the library's role as a national repository for Dutch cultural heritage materials, where system reliability is essential for preserving and providing access to important historical records.
Mitigation strategies for this vulnerability should focus on implementing comprehensive input validation controls and memory safety measures within the multiNER processing pipeline. Organizations should deploy strict character encoding validation and implement proper buffer management techniques to prevent overflow conditions. The system requires immediate patching with updated input sanitization routines that properly handle Unicode sequences and character limits. Security measures should include runtime monitoring for anomalous processing patterns and implementation of secure coding practices that align with industry standards such as those recommended by the OWASP Top Ten. The National Library should establish robust logging mechanisms to detect potential exploitation attempts and implement network segmentation to limit the potential impact of any successful attacks. Additionally, regular security assessments and code reviews should be conducted to identify similar vulnerabilities in other components of the library's digital infrastructure. This remediation approach addresses both the immediate technical flaw and establishes long-term security practices that align with the ATT&CK framework's prevention strategies for input validation and memory corruption attacks.