HackerPapers

arXiv:2301.04781cs.CR

Bug Hunters' Perspectives on the Challenges and Benefits of the Bug Bounty Ecosystem

Omer Akgul, Taha Eghtesad, Amit Elazari, Omprakash Gnawali, Jens Grossklags, Michelle L. Mazurek, Daniel Votipka, Aron Laszka

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

Although researchers have characterized the bug-bounty ecosystem from the point of view of platforms and programs, minimal effort has been made to understand the perspectives of the main workers: bug hunters. To improve bug bounties, it is important to understand hunters' motivating factors, challenges, and overall benefits. We address this research gap with three studies: identifying key factors through a free listing survey (n=56), rating each factor's importance with a larger-scale factor-rating survey (n=159), and conducting semi-structured interviews to uncover details (n=24). Of 54 factors that bug hunters listed, we find that rewards and learning opportunities are the most important benefits. Further, we find scope to be the top differentiator between programs. Surprisingly, we find earning reputation to be one of the least important motivators for hunters. Of the challenges we identify, communication problems, such as unresponsiveness and disputes, are the most substantial. We present recommendations to make the bug-bounty ecosystem accommodating to more bug hunters and ultimately increase participation in an underutilized market.

arXiv comments
Journal reference
DOI
Subjects
cs.CRCryptography and Security cs.SESoftware Engineering

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Jan 2023 to Jan 2023. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.