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An Investigation into Protestware

Tanner Finken, Jesse Chen, Sazzadur Rahaman

TL;DR

This paper provides the first systematic, data driven study of protestware by collecting 32 samples and applying inductive coding to characterize how protests are induced, who is targeted, and how transparent the protest actions are. It introduces a four category coding framework and a 13 code taxonomy that captures diverse mechanisms such as conditional DoS, ideology promotion, and dedicated protest software, revealing that many protests discriminate by user group and often hide their protest behavior. The aftermath analysis combines a retrospective supply chain study, sentiment analysis, and usage trend tracking to show that disruptive protestware can cause downstream disruption and that trust dynamics in OSS can persist with increasing dependencies even after protests. The findings highlight substantial implications for OSS governance, security monitoring, and contingency planning, and point to future work on automatic detection and real time notification of protestware activities.

Abstract

Protests are public expressions of personal or collective discontent with the current state of affairs. Although traditional protests involve in-person events, the ubiquity of computers and software opened up a new avenue for activism: protestware. The roots of protestware date back to the early days of computing. However, recent events in the Russo-Ukrainian war has sparked a new wave of protestware. While news and media are heavily reporting on individual protestware as they are discovered, the understanding of such software as a whole is severely limited. In particular, we do not have a detailed understanding of their characteristics and their impact on the community. To address this gap, we first collect 32 samples of protestware. Then, with these samples, we formulate characteristics of protestware using inductive analysis. In addition, we analyze the aftermath of the protestware which has potential to affect the software supply chain in terms of community sentiment and usage. We report that: (1) protestware has three notable characteristics, namely, i) the "nature of inducing protest" is diverse, ii) the "nature of targeting users" is discriminatory, and iii) the "nature of transparency" is not always respected; (2) disruptive protestware may cause substantial adverse impact on downstream users; (3) developers of protestware may not shift their beliefs even with pushback; (4) the usage of protestware from JavaScript libraries has been seen to generally increase over time.

An Investigation into Protestware

TL;DR

This paper provides the first systematic, data driven study of protestware by collecting 32 samples and applying inductive coding to characterize how protests are induced, who is targeted, and how transparent the protest actions are. It introduces a four category coding framework and a 13 code taxonomy that captures diverse mechanisms such as conditional DoS, ideology promotion, and dedicated protest software, revealing that many protests discriminate by user group and often hide their protest behavior. The aftermath analysis combines a retrospective supply chain study, sentiment analysis, and usage trend tracking to show that disruptive protestware can cause downstream disruption and that trust dynamics in OSS can persist with increasing dependencies even after protests. The findings highlight substantial implications for OSS governance, security monitoring, and contingency planning, and point to future work on automatic detection and real time notification of protestware activities.

Abstract

Protests are public expressions of personal or collective discontent with the current state of affairs. Although traditional protests involve in-person events, the ubiquity of computers and software opened up a new avenue for activism: protestware. The roots of protestware date back to the early days of computing. However, recent events in the Russo-Ukrainian war has sparked a new wave of protestware. While news and media are heavily reporting on individual protestware as they are discovered, the understanding of such software as a whole is severely limited. In particular, we do not have a detailed understanding of their characteristics and their impact on the community. To address this gap, we first collect 32 samples of protestware. Then, with these samples, we formulate characteristics of protestware using inductive analysis. In addition, we analyze the aftermath of the protestware which has potential to affect the software supply chain in terms of community sentiment and usage. We report that: (1) protestware has three notable characteristics, namely, i) the "nature of inducing protest" is diverse, ii) the "nature of targeting users" is discriminatory, and iii) the "nature of transparency" is not always respected; (2) disruptive protestware may cause substantial adverse impact on downstream users; (3) developers of protestware may not shift their beliefs even with pushback; (4) the usage of protestware from JavaScript libraries has been seen to generally increase over time.
Paper Structure (40 sections, 3 figures, 3 tables)

This paper contains 40 sections, 3 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Background and Definitions
  3. Protestware
  4. Protestware vs Supply Chain Attacks
  5. Protestware Collection and Preparation
  6. Data Collection
  7. Data Preparation
  8. Initial Observations
  9. Dataset Statistics.
  10. Triggers
  11. RQ1: Characteristics
  12. Coding Methodology
  13. RQ1.1: Nature of Inducing Protests
  14. Altering Software (15).
  15. Altering Documentation (4).
  16. ...and 25 more sections

Figures (3)

  • Figure 1: Taxonomy of protestware based on their nature of being induced.
  • Figure 2: Example of ideology promotion evoCMScommit.
  • Figure 3: Grouped bar chart of protestware breakdowns by our characteristics.