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Why secret detection tools are not enough: It’s not just about false positives - An industrial case study

Checked-in secrets in version-controlled software projects pose security risks to software and services. Secret detection tools can identify the presence of secrets in the code, commit changesets, and project version control history. As these tools can generate false positives, developers are provid...

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Detalles Bibliográficos
Autores principales: Rahman, Md Rayhanur, Imtiaz, Nasif, Storey, Margaret-Anne, Williams, Laurie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928718/
https://www.ncbi.nlm.nih.gov/pubmed/35313538
http://dx.doi.org/10.1007/s10664-021-10109-y
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author Rahman, Md Rayhanur
Imtiaz, Nasif
Storey, Margaret-Anne
Williams, Laurie
author_facet Rahman, Md Rayhanur
Imtiaz, Nasif
Storey, Margaret-Anne
Williams, Laurie
author_sort Rahman, Md Rayhanur
collection PubMed
description Checked-in secrets in version-controlled software projects pose security risks to software and services. Secret detection tools can identify the presence of secrets in the code, commit changesets, and project version control history. As these tools can generate false positives, developers are provided with mechanisms to bypass the warnings generated from these tools. Providing this override mechanism can result in developers sometimes exposing secrets in software repositories. The goal of this article is to aid software security practitioners in understanding why‘ secrets are checked into repositories, despite being warned by tools, through an industrial case study of analysis of usage data of a secret detection tool and a survey of developers who bypassed the tool alert. In this case study, we analyzed the usage data of a checked-in secret detection tool used widely by a software company and we surveyed developers who bypassed the warnings generated by the tool. From the case study, we found that, despite developers classified 50% of the warning as false positive, developers also bypassed the warning due to time constraints, working with non-shipping projects, technical challenges of eliminating secrets completely from the version control history, technical debts, and perceptions that check-ins are low risk. We advocate practitioners and researchers to investigate the findings of our study further to improve secret detection tools and related development practices. We also advocate that organizations should insert secondary checks, as is done by the company we studied, to capture occasions where developers incorrectly bypass secret detection tools.
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spelling pubmed-89287182022-03-17 Why secret detection tools are not enough: It’s not just about false positives - An industrial case study Rahman, Md Rayhanur Imtiaz, Nasif Storey, Margaret-Anne Williams, Laurie Empir Softw Eng Article Checked-in secrets in version-controlled software projects pose security risks to software and services. Secret detection tools can identify the presence of secrets in the code, commit changesets, and project version control history. As these tools can generate false positives, developers are provided with mechanisms to bypass the warnings generated from these tools. Providing this override mechanism can result in developers sometimes exposing secrets in software repositories. The goal of this article is to aid software security practitioners in understanding why‘ secrets are checked into repositories, despite being warned by tools, through an industrial case study of analysis of usage data of a secret detection tool and a survey of developers who bypassed the tool alert. In this case study, we analyzed the usage data of a checked-in secret detection tool used widely by a software company and we surveyed developers who bypassed the warnings generated by the tool. From the case study, we found that, despite developers classified 50% of the warning as false positive, developers also bypassed the warning due to time constraints, working with non-shipping projects, technical challenges of eliminating secrets completely from the version control history, technical debts, and perceptions that check-ins are low risk. We advocate practitioners and researchers to investigate the findings of our study further to improve secret detection tools and related development practices. We also advocate that organizations should insert secondary checks, as is done by the company we studied, to capture occasions where developers incorrectly bypass secret detection tools. Springer US 2022-03-17 2022 /pmc/articles/PMC8928718/ /pubmed/35313538 http://dx.doi.org/10.1007/s10664-021-10109-y Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Rahman, Md Rayhanur
Imtiaz, Nasif
Storey, Margaret-Anne
Williams, Laurie
Why secret detection tools are not enough: It’s not just about false positives - An industrial case study
title Why secret detection tools are not enough: It’s not just about false positives - An industrial case study
title_full Why secret detection tools are not enough: It’s not just about false positives - An industrial case study
title_fullStr Why secret detection tools are not enough: It’s not just about false positives - An industrial case study
title_full_unstemmed Why secret detection tools are not enough: It’s not just about false positives - An industrial case study
title_short Why secret detection tools are not enough: It’s not just about false positives - An industrial case study
title_sort why secret detection tools are not enough: it’s not just about false positives - an industrial case study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928718/
https://www.ncbi.nlm.nih.gov/pubmed/35313538
http://dx.doi.org/10.1007/s10664-021-10109-y
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