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A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries

1 . Data Description

  • CVE entries in our dataset cover the period from 2002 to 2019, each consisting of 21 features. Each feature's name and corresponding column name in the CSV file are explained in the following table. The dataset is released as comma-separated values(CSV) format (all_c_cpp_release2.0.csv).
Features Column Name in the CSV Description
Access Complexity access_complexity Reflects the complexity of the attack required to exploit the software feature misuse vulnerability
Authentication Required authentication_required If authentication is required to exploit the vulnerability
Availability Impact availability_impact Measures the potential impact to availability of a successfully exploited misuse vulnerability
Commit ID commit_id Commit ID in code repository, indicating a mini-version
Commit Message commit_message Commit message from developer
Confidentiality Impact confidentiality_impact Measures the potential impact on confidentiality of a successfully exploited misuse vulnerability
CWE ID cwe_id Common Weakness Enumeration ID
CVE ID cve_id Common Vulnerabilities and Exposures ID
CVE Page cve_page CVE Details web page link for that CVE
CVE Summary summary CVE summary information
CVSS Score score The relative severity of software flaw vulnerabilities
Files Changed files_changed All the changed files and corresponding patches
Integrity Impact integrity_impact Measures the potential impact to integrity of a successfully exploited misuse vulnerability\
Mini-version After Fix version_after_fix Mini-version ID after the fix
Mini-version Before Fix version_before_fix Mini-version ID before the fix
Programming Language lang Project programming language
Project project Project name
Publish Date publish_date Publish date of the CVE
Reference Link ref_ink Reference link in the CVE page
Update Date update_date Update date of the CVE
Vulnerability Classification vulnerability_classification Vulnerability type
  • We used the code changes information(minned from commited version patches) to localize which lines of code in the files were modified. Taking modified lines between the two mini-versions as flaw lines, we split the functions in the modified files into vulnerable functions (if there were flaw lines modified in the function) and non-vulnerable functions.

  • The cleaned version of split functions is coming soon.

  • The cleaned version of split functions(CSV format) can be found at: https://drive.google.com/file/d/1-0VhnHBp9IGh90s2wCNjeCMuy70HPl8X/view?usp=sharing

    Some of the intermediary files in the data collecting and cleaning process can be found at:https://drive.google.com/file/d/1E95oVDSO0CfAAs-Q0yav2HBGLZQce_v2/view?usp=sharing

    Pandas is recommended (Python Package, like pandas.read_csv("filepath/file.csv") ) to work on the dataset.

    Also JSON format dataset can be found at: https://drive.google.com/file/d/1deNsPfeh77h1SHjJURYOeyCR96JgxB_A/view?usp=sharing

    • Split functions are released as comma-separated values(CSV) format:
    Column Name in the CSV Description
    func_before The function before the vulnerability being fixed(if "vul" labeled as "1", then this is the vulnerable function)
    func_after The function after the vulnerability being fixed
    lines_before The modified lines in the founction before the vulnerability being fixed
    lines_after The modified lines in the founction after the vulnerability being fixed
    vul "1" means vulnerable function and "0" means non-vulnerable function
    vul_func_with_fix The code comments showing how the vulnerability was fixed

2. HOW To Use The Scripts

  • Pre-Requirements

    Citation

    ACM Reference Format:

    Jiahao Fan, Yi Li, Shaohua Wang and Tien N. Nguyen. 2020. A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries. In MSR ’20: The 17th International Conference on Mining Software Repositories,May 25–26, 2020, MSR, Seoul, South Korea. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3379597.3387501

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