AI Slop is DDoSing Open Source Understanding the Impact of AI-Generated Contributions on Open Source Sustainability

Jul 16, 2026

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Open source software communities face escalating pressure from Generative AI (GenAI) tools, producing “AI-DDoS”: plausible but low-quality AI-generated contributions that overwhelm maintainer review capacity. The study applies a phenomenon-based mixed-methods design: practitioner accounts from Reddit, OSS mentor mailing lists, and blogs generate six themes and hypotheses; Bayesian Structural Time Series analysis then evaluates effects across 294 repositories with over 2 million pull requests and issues. Results show PR growth in 2025 alongside declining merge rates and an 18.18% PR-merge drop for one-time contributors versus the counterfactual, followed by 11 validated remediation strategies.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Introduction

Research Questions and Approach

Threat to Contribution Workflows and Ecosystem Supply Chains

“AI Slop is DDoSing Open Source”: Understanding the Impact of AI-Generated Contributions on Open Source Sustainability Sadia Afroz 1 Courtney Miller2 Tyler Menezes3 Edward Gilmour1 Anita Sarma 1 Zixuan Feng4 1 Oregon State University, Corvallis, OR, USA ({afrozs, gilmoued, [anita.sarma](anita.sarma}@oregonstate.edu)[}](anita.sarma}@oregonstate.edu)[@oregonstate.edu](anita.sarma}@oregonstate.edu)) 2 The George Washington University, Washington, DC, USA ([courtney.miller@gwu.edu](courtney.miller@gwu.edu)) 3 CodeDay, Seattle, WA, USA ([tylermenezes@codeday.org](tylermenezes@codeday.org)) 4 Virginia Commonwealth University, Richmond, VA, USA ([fengz3@vcu.edu](fengz3@vcu.edu)) arXiv :2607 .04003v 1 [ cs . SE] 4 Jul 2026 Abstract—Open source software (OSS) communities are facing increasing pressure from Generative AI (GenAI) tools. We call it AI-DDoS: a denial-of-service effect in which plausible but lowquality AI-generated contributions overwhelm OSS community capacity. Using a phenomenon-based mixed-methods approach, we first analyze practitioner accounts from Reddit, OSS mentor mailing lists, and blogs to identify six recurring themes and derive hypotheses. We then evaluate these hypotheses using Bayesian Structural Time Series analysis across 294 repositories with over 2 million pull requests and issues. Our results show that while PR volume increased in 2025, merge rates declined, with one-time contributors experiencing an 18.18% drop in PR merge rates relative to the counterfactual. Finally, we identify 11 remediation strategies through practitioners’ interviews and validate them with a survey of 229 OSS practitioners, grouping them into preservative, adaptive, and transformative orientations. Our findings show that AI-DDoS is not only a contributionvolume problem but a sustainability trap: communities often default to low-effort defensive strategies that protect short-term review capacity while making openness difficult to sustain. Index Terms—AI-generated Contribution, OSS, AI-DDoS. I. INTRODUCTION Generative Artificial Intelligence (GenAI) tools for software development have dramatically lowered the cost of producing code while raising the cost of evaluating it [1], [2] . In opensource software (OSS) communities, this asymmetry produces a phenomenon we call AI-DDoS: a flood of plausible-looking, low-quality GenAI contributions that disrupts the contribution process and overwhelms the limited time and resources maintainers have to review contributions. Figure 1 presents an overview of the steep rise in contributions and the decline in accepted contributions. OSS practitioners have begun responding defensively to this barrage [3], [4] . In January 2026, the cURL project ended its six-year bug bounty program after AI-generated contributions reduced the proportion of valid submissions to about 5% by July 2025, making triage unsustainable [4], [5] . Others have moved to invitation-only contribution workflows, adopted blanket policies rejecting unsolicited pull requests, and stopped accepting outside vulnerability reports [2], [3] . These responses help projects survive the immediate flood, but they narrow or completely block the pathways through Fig. 1. Overview of contribution flow. which OSS sustains itself. Over a decade of OSS sustainability research establishes that a project’s health and survival depend on its maintainers, who provide the labor that keeps the project alive, and on its ability to recruit and retain new contributors who renew that labor over time [6], [7] . The problem is that the programs OSS projects are shuttering to cope with AIDDoS are the same ones they use to recruit and retain those contributors (e.g., good first issues [8]) . AI-DDoS and the strategies used to remediate it therefore reach well beyond their immediate toll on the maintainers (e.g., Linux [9] and Ghostty [10]) . The first impact is on the projects themselves: as communities close their doors to survive the

FAQs

What problem does the paper describe as AI-DDoS?

AI-DDoS refers to a denial-of-service effect where plausible but low-quality AI-generated contributions overwhelm OSS community capacity, disrupting the contribution and review process.

How is AI-DDoS investigated in the study?

The paper uses a phenomenon-based mixed-methods approach: it analyzes practitioner accounts to derive themes and hypotheses, then tests them with Bayesian Structural Time Series causal impact analysis across 294 repositories and 2+ million pull requests and issues.

What do the results show about contribution metrics and contributor behavior?

PR volume increased in 2025, but merge rates declined. One-time contributors experienced an 18.18% drop in PR merge rates relative to the counterfactual, indicating reduced effective contribution quality or reviewability under AI-DDoS pressure.

Jul 16, 2026

Upload by Noah