Curl Terminates Bug Bounty Program to Curb AI-Generated Submissions

The cURL project, a widely used open-source tool for data transfer operations, has formally discontinued its bug bounty program in response to an overwhelming volume of AI-generated low-quality submissions. Maintainer Daniel Stenberg confirmed the termination via a GitHub commit titled "BUG-BOUNTY.md: we stop the bug-bounty end of Jan 2026," establishing January 31, 2026, as the definitive endpoint for all bounty-related activities.

Regulatory Action: Program Termination Framework

Effective immediately, the cURL security team will no longer accept new submissions for financial rewards. This structural change removes monetary incentives that previously encouraged contributors to submit unverified or automatically generated reports. The decision follows two years of escalating challenges, with Stenberg first noting problematic AI submissions in early 2024 and formally considering termination by mid-2025.

Compliance Requirements and Implementation

1. Submission Protocol Revision: All bug reports submitted after January 31, 2026, will be treated as community contributions without compensation. The project maintains its vulnerability disclosure process through standard GitHub issues and email channels.
2. Validation Criteria Enforcement: Reports must include verifiable reproduction steps, impact analysis, and technical understanding of the flaw. Submissions failing these criteria may be publicly documented as invalid.
3. Resource Reallocation: Security team efforts will prioritize human-validated vulnerabilities, reducing time spent triaging automated or superficial reports.

Compliance Timeline

• January 21, 2026: Program termination announced via GitHub and mailing lists.
• January 31, 2026: Final date for bounty-eligible submissions.
• February 1, 2026 onward: All new reports processed under non-monetary contribution guidelines.

Policy Justification and Enforcement Mechanisms

Stenberg emphasized that ending the bounty program directly addresses operational inefficiencies caused by what he termed "AI slop"—automated submissions lacking technical rigor. In a mailing list statement, he noted: "The current torrent of submissions put a high load on the curl security team. This action reduces noise while preserving our commitment to security."

The project retains its right to publicly identify and critique invalid submissions, a practice Stenberg defends as a deterrent against wasted resources. However, he acknowledged balancing this with ethical considerations: "Exposing and ridiculing time-wasters sends a clear message: Never report bugs without understanding them. That said, we recognize submitters may be inexperienced individuals learning from mistakes."

Strategic Implications

This policy shift reflects broader industry challenges with generative AI in security workflows. While tools like LLMs can assist skilled researchers (as Stenberg confirmed with validated AI-aided discoveries), they risk flooding projects with unreliable output. The cURL approach establishes a precedent for open-source communities balancing automation with quality control, emphasizing that:

• Financial incentives may inadvertently promote low-value automation
• Public accountability mechanisms remain viable for maintaining submission standards
• Volunteer-driven projects require explicit guardrails against resource exhaustion

Developers may continue submitting vulnerabilities without compensation, but Stenberg noted outcomes will depend on community adherence to revised protocols: "The future will tell whether contributors share findings without payment—and whether they risk public critique for substandard reports."