FLARE-AI: Flaw Reporting for AI

Flaw reporting for deployed AI systems is fundamental to identifying system failures and improving AI safety. Yet the AI reporting ecosystem is fragmented: researchers who identify flaws often do not know what or where to report, and groups who receive reports rarely share them with other relevant stakeholders. As a result, good-faith reporters duplicate effort by submitting many different forms, and recipients lack standardized, triage-ready information. We survey 12 reporting systems published by AI developers, cybersecurity groups, and AI flaw aggregators, identifying five recurring design challenges spanning discoverability, scope, information collection, coordination, and guidance for strict-liability cases. Building on this analysis and feedback from 49 experts across 32 organizations representing developers, security researchers, and ecosystem coordinators, we introduce FLARE-AI, an open-source AI flaw reporting system designed for interoperability with existing systems. FLARE-AI streamlines flaw report creation by collecting triage-relevant information through conditional logic and early classification, then enables optional dissemination of standardized, machine-readable reports to multiple developers, coordinators, and incident registries from a single submission. By lowering barriers to reporting AI flaws and improving interoperability across stakeholders, FLARE-AI helps break down silos and accelerate remediation across the AI ecosystem.

When AI systems behave badly, such as by leaking private data, producing harmful content, or being tricked by malicious users, the people who discover these problems often have no clear way to report them. Today, every AI company and watchdog group uses its own separate reporting form, each asking for different information. So someone who finds a flaw that affects several AI systems has to fill out many forms by hand, and the groups receiving those reports rarely share them with each other. The result is that many flaws go unreported or never reach the people who can fix them. To tackle this, we studied 12 existing reporting systems and gathered input from 49 experts at 32 organizations, including AI developers, security researchers, and safety groups. Using what we learned, we built FLARE-AI, a free, open-source reporting tool. It asks a few simple questions, adapts to the type of problem, and lets a person send a single report to many recipients at once in a shared, machine-readable format. By making AI flaws easier to report and share, FLARE-AI can help problems get fixed faster and prevent the same harms from happening to millions of people.