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AI floods crypto bug bounty programs with false reports

AI floods crypto bug bounty programs with low-quality submissions, straining teams.

  • Cryptocurrency bug bounty programs are experiencing a surge in submissions, with Cosmos Labs reporting a 900% year-over-year increase.
  • Protocol leaders attribute this flood to AI tools, which lower the cost of generating reports but often produce low-quality or false positives.
  • Teams are responding by tightening submission scoring, prioritizing trusted researchers, and considering defensive AI systems to filter the noise.

The rise of Artificial Intelligence has triggered a flood of bogus bug bounty submissions across cryptocurrency protocols, straining development teams trying to identify legitimate security threats. Bug bounty systems reward ethical Hackers for reporting vulnerabilities, but AI has made sweeping through code for potential bugs easier and cheaper. However, AI tools are also prone to hallucination, leading to an influx of invalid reports.

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Consequently, Barry Plunkett, co-CEO of Cosmos Labs, said their program has seen a 900% increase in submission volume from last year. This results in 20-50 reports daily, creating a significant burden for their team. Kadan Stadelmann, CTO at Komodo Platform, also confirmed a notable increase in submissions and payouts across organizations.

He noted, “There has definitely been an increase in low-quality bug bounty submissions, some of which have been false positives, potentially suggesting AI sourcing.” The open-source tool curl, used in blockchain infrastructure, faced such a severe influx that its creator ended the bounty program due to exhaustion. Daniel Stenberg announced the termination, citing “AI slop” in vulnerability reports.

Meanwhile, protocols are adapting by tightening how they score submissions and prioritizing trusted researchers. Cosmos Labs is working with bounty providers offering advanced triage. Stadelmann suggested AI could also be the solution, stating defensive AI systems will be crucial to automatically sift through incoming reports. Consequently, smaller teams will need stricter standards for their programs to manage the volume.

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