huntr
Secure AI/ML systems through crowdsourced vulnerability reporting
Target Audience
- Security researchers specializing in AI/ML
- AI/ML open-source maintainers
- Machine learning engineers
Hashtags
Overview
huntr connects security researchers with AI/ML project maintainers to identify and fix vulnerabilities in open-source tools and model formats. It streamlines vulnerability disclosure with automated maintainer outreach and bounty rewards, helping protect critical AI infrastructure. The platform ensures responsible disclosure by giving maintainers 31 days to respond before resolving high-risk issues.
Key Features
Secure submission
Dedicated form for vulnerability reports in AI/ML systems
Maintainer outreach
Automated follow-ups every 7 days for 31-day response window
Bounty rewards
Compensation for valid vulnerabilities in open-source projects
CVE issuance
Public vulnerability tracking for open-source reports
Delayed disclosure
90-day publication buffer for sensitive AI model reports
Use Cases
Research AI/ML vulnerabilities
Earn bug bounties for valid reports
Maintain secure open-source AI projects
Track CVE assignments for vulnerabilities
Pros & Cons
Pros
- First dedicated platform for AI/ML security vulnerabilities
- Structured disclosure process with maintainer accountability
- Financial incentives for researchers and maintainers
- CVE assignment brings professional recognition
Cons
- Currently limited to open-source projects and model formats
- No patch submission support yet (planned feature)
- 90-day disclosure delay might be lengthy for some users
Frequently Asked Questions
What types of vulnerabilities does huntr accept?
Accepts vulnerabilities in AI/ML open-source applications, libraries, and model file formats
How are researchers rewarded?
Bounties awarded for valid reports after maintainer confirmation or huntr validation
When are vulnerability reports made public?
Open-source reports publish after 90 days unless maintainers request extensions
Reviews for huntr
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