Using AI/ML to Find and Remediate Enterprise Secrets in Code & Document Sharing Platforms
This addresses a mostly unaddressed challenge for software developers by reducing noise and toil compared to existing heuristic methods.
The paper tackles the problem of detecting and automatically remediating secrets in code and document sharing platforms, introducing baseline AI models with good detection performance and an automatic remediation mechanism.
We introduce a new challenge to the software development community: 1) leveraging AI to accurately detect and flag up secrets in code and on popular document sharing platforms that frequently used by developers, such as Confluence and 2) automatically remediating the detections (e.g. by suggesting password vault functionality). This is a challenging, and mostly unaddressed task. Existing methods leverage heuristics and regular expressions, that can be very noisy, and therefore increase toil on developers. The next step - modifying code itself - to automatically remediate a detection, is a complex task. We introduce two baseline AI models that have good detection performance and propose an automatic mechanism for remediating secrets found in code, opening up the study of this task to the wider community.