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2025
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| Online Access: | https://doi.org/10.5281/zenodo.15593802 |
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| _version_ | 1866902100479311872 |
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| author | Thimmaiah, Neil Gjomemo, Rigel Venkatakrishnan, V.N. |
| author_facet | Thimmaiah, Neil Gjomemo, Rigel Venkatakrishnan, V.N. |
| contents | <p>Modern web applications are becoming increasingly complex. They<br>include multiple dynamic runtime constructs that are difficult to<br>analyze by static application security testing (SAST) tools. These<br>tools often use a graph representation of the code for their analysis.<br>However, built statically, such graphs may miss important data<br>and control flows dependent on runtime information. In addition,<br>the presence of difficult-to-analyze code patterns in modern web<br>applications, referred to as testability tarpits, further reduces the<br>accuracy of statically built graphs. As a result, current SAST tools<br>have several false negatives because of ’hidden’ paths, which are<br>not present in the graphs. In this paper, we present SemFinder,<br>an approach designed to automatically detect such hidden paths.<br>SemFinder uses natural language semantics to hypothesize connec-<br>tions between different locations in the code based on the meaning<br>and similarity of the variables in those locations and test those<br>hypotheses dynamically. We evaluate SemFinder on 30 PHP appli-<br>cations and discover 215 new exploitable hidden paths with respect<br>to existing SAST tools, leading to the submission of 31 new CVEs</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15593802 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | SemFinder: A Semantics Based Approach to Enhance Vulnerability Analysis in Web Applications Thimmaiah, Neil Gjomemo, Rigel Venkatakrishnan, V.N. <p>Modern web applications are becoming increasingly complex. They<br>include multiple dynamic runtime constructs that are difficult to<br>analyze by static application security testing (SAST) tools. These<br>tools often use a graph representation of the code for their analysis.<br>However, built statically, such graphs may miss important data<br>and control flows dependent on runtime information. In addition,<br>the presence of difficult-to-analyze code patterns in modern web<br>applications, referred to as testability tarpits, further reduces the<br>accuracy of statically built graphs. As a result, current SAST tools<br>have several false negatives because of ’hidden’ paths, which are<br>not present in the graphs. In this paper, we present SemFinder,<br>an approach designed to automatically detect such hidden paths.<br>SemFinder uses natural language semantics to hypothesize connec-<br>tions between different locations in the code based on the meaning<br>and similarity of the variables in those locations and test those<br>hypotheses dynamically. We evaluate SemFinder on 30 PHP appli-<br>cations and discover 215 new exploitable hidden paths with respect<br>to existing SAST tools, leading to the submission of 31 new CVEs</p> |
| title | SemFinder: A Semantics Based Approach to Enhance Vulnerability Analysis in Web Applications |
| url | https://doi.org/10.5281/zenodo.15593802 |