CVE-2021-42006 in GCLib
Summary
by MITRE • 10/05/2021
An out-of-bounds access in GffLine::GffLine in gff.cpp in GCLib 0.12.7 allows an attacker to cause a segmentation fault or possibly have unspecified other impact via a crafted GFF file.
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Analysis
by VulDB Data Team • 10/09/2021
The vulnerability identified as CVE-2021-42006 represents a critical out-of-bounds memory access flaw within the GCLib 0.12.7 library, specifically within the GffLine::GffLine constructor function located in gff.cpp. This issue arises when processing malformed GFF (General Feature Format) files, which are commonly used in bioinformatics applications for representing genomic features and annotations. The vulnerability stems from inadequate input validation and bounds checking within the library's parsing logic, creating a potential attack surface where maliciously crafted GFF files can trigger memory corruption behaviors.
The technical implementation of this vulnerability involves the GffLine constructor failing to properly validate array indices or buffer boundaries when parsing GFF file content. When an attacker provides a specially crafted GFF file containing malformed data structures or unexpected field values, the parsing routine attempts to access memory locations beyond the allocated buffer boundaries. This out-of-bounds access can result in segmentation faults that crash the application, or in more severe cases, may allow for arbitrary code execution depending on the memory layout and the specific nature of the overflow. The vulnerability aligns with CWE-129, which specifically addresses insufficient bounds checking in input validation scenarios.
The operational impact of this vulnerability extends beyond simple application crashes, as it can be exploited in various attack scenarios within bioinformatics environments. Systems utilizing GCLib for processing genomic data, such as sequence analysis tools, genome browsers, or bioinformatics pipelines, become vulnerable to denial-of-service attacks or potential remote code execution. The attack vector requires an attacker to convince a victim to process a malicious GFF file, which could occur through email attachments, file sharing platforms, or automated data ingestion processes. This makes the vulnerability particularly dangerous in collaborative research environments or automated bioinformatics workflows where file processing occurs without explicit user validation.
Mitigation strategies for CVE-2021-42006 should focus on immediate library updates to versions that address the bounds checking deficiencies in GffLine::GffLine functionality. Organizations should implement strict input validation policies for all GFF file processing, including pre-validation of file integrity and content structure before parsing. The implementation of defensive programming practices such as bounds checking, input sanitization, and memory protection mechanisms should be enforced throughout the application stack. Additionally, deployment of intrusion detection systems capable of identifying malformed GFF file patterns and network-based protections can help prevent exploitation attempts. This vulnerability demonstrates the importance of robust input validation in scientific computing libraries, where the processing of structured data formats like GFF files requires careful attention to memory safety and error handling to prevent exploitation through crafted inputs. The ATT&CK framework categorizes this as a code injection technique through malformed input processing, emphasizing the need for comprehensive input validation controls in data processing applications.