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Daniel Stenberg describes the unprecedented pressure on the curl project due to a deluge of credible AI-assisted security reports, which have quadrupled the rate of incoming reports and increased the workload, while noting that most vulnerabilities found are low or medium severity.
A blog post exploring the challenges faced by open-source maintainers, including backlog of pull requests, the impact of AI tools on code review, and the dilemma of balancing quality with burnout.
The article enumerates various ways open source projects die, including maintainer abandonment, corporate neglect, funding cliffs, and bureaucratic deadlocks, highlighting systemic issues in open source sustainability.
Security researchers warn that an oncoming flood of AI-generated vulnerability reports will overwhelm open-source maintainers, forcing projects to adopt AI triage tools or risk drowning in low-quality submissions.
An open-source maintainer explains why they now prefer LLM-generated code over community PRs, arguing that AI assistance reduces risk and friction while shifting the value of contributions toward feedback, bug reports, and design discussions.
This article discusses how AI-generated code and agentic AI are overwhelming open source maintainers with low-quality pull requests and bug reports, causing projects like curl to drop bug bounties and leading to harassment of maintainers.