The Surprising Complexity of Finding Known Vulnerabilities (god2025)

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With the increasing reliance on third-party software components, ensuring their security against known vulnerabilities has become a daily challenge for individuals and organizations. Despite the availability of a variety of tools and databases, we found all of them fall short when applied to real-world scenarios - raising questions about their effectiveness, generalizability, and practical utility. Starting from our perspective as penetration testers, we identified three main problems with existing solutions in vulnerability identification: Accuracy and completeness of results - Many tools exhibit limited precision and recall, often depending on a single data source (e.g. NVD) and overlooking critical indicators such as known exploits or patch history. Rigid input requirements - Most solutions enforce strict formatting constraints (e.g., requiring exact CPEs), creating usability and reliability issues when dealing with diverse or incomplete data. Lack of usable outputs - The inability to meaningfully export or integrate results into broader workflows hampers both manual and automated security processes. In order to solve these challenges, we developed the open-source tool search_vulns. It leverages information from multiple data sources and uses text comparison techniques and CPEs in combination to increase accuracy in software identification. Due to this approach, it can even automatically generate CPEs that have yet to be published. Together with its custom logic for version comparison, this further enhances the quality of results. Finally, search_vulns provides a fine-granular export of results in different formats. In conclusion, this talk aims to simplify the surprising complexity of finding known vulnerabilities in software. To do so, we discuss common challenges in mapping software names to CPEs, e.g. for product rebrandings, single-version vulnerabilities and yet to be published software versions. In addition, we present an approach using multiple data sources in combination to enrich CVE data with information on known exploits, likelihood of exploitability (EPSS) and other data sources. Finally, we present search_vulns as open-source tool. Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://c3voc.de