The Rules of Engagement for Bug Bounty Programs

February 2018·
Aron Laszka
Aron Laszka
,
Mingyi Zhao
,
Akash Malbari
,
Jens Grossklags
Abstract

White hat hackers, also called ethical hackers, who find and report vulnerabilities to bug bounty programs have become a significant part of today’s security ecosystem. While the efforts of white hats contribute to heightened levels of security at the participating organizations, the white hats’ participation needs to be carefully managed to balance risks with anticipated benefits. One way, taken by organizations, to manage bug bounty programs is to create rules that aim to regulate the behavior of white hats, but also bind these organizations to certain actions (e.g., level of bounty payments). To the best of our knowledge, no research exists that studies the content of these program rules and their impact on the effectiveness of bug bounty programs.

We collected and analyzed the rules of 111 bounty programs on a major bug bounty platform, HackerOne. We qualitatively study the contents of these rules to determine a taxonomy of statements governing the expected behavior of white hats and organizations. We also report specific examples of rules to illustrate their reach and diversity across programs. We further engage in a quantitative analysis by pairing the findings of the analysis of the program rules with a second dataset about the performance of the same bug bounty programs, and conducting statistical analyses to evaluate the impact of program rules on program outcomes.

Type
Venue
22nd International Conference on Financial Cryptography and Data Security (FC 2018), 138–159
publications

Acceptance Rate: 26%

Authors

Aron Laszka
Associate Professor

Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.

His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.

His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.