Researchers at the Software Engineering Institute at Carnegie Mellon University, in collaboration with academic, industry, and nonprofit partners, have developed FLARE-AI, an open-source platform designed to standardize the reporting and coordination of artificial intelligence vulnerabilities. The platform addresses a longstanding gap in the AI security landscape by providing a formal mechanism for researchers and developers to identify flaws, notify affected vendors, and orchestrate cross-organizational remediation efforts. Prior to FLARE-AI, AI vulnerabilities were frequently reported to single vendors, leaving structural weaknesses replicated across multiple third-party models and integrations unaddressed. The new platform allows users to submit a standardized, machine-readable report detailing the flaw or incident. Submitters can then route the disclosure to independent security organizations, government agencies, model-hosting platforms, or the original AI developers. Upon receipt, these organizations can address the issue directly or coordinate a unified disclosure and patching strategy. FLARE-AI integrates directly with established cybersecurity infrastructure, most notably the Vulnerability Information and Coordination Environment managed by the SEI CERT Coordination Center. SEI software engineer Greg Strom facilitated the backend integration, enabling the platform to feed AI-specific reports into traditional vulnerability workflows. When a report enters this system, experts from the CERT Coordination Center and the SEI AI Security Incident Response Team evaluate the findings. If validated, they coordinate with affected parties and assign Common Vulnerabilities and Exposures identifiers, ensuring transparent communication across the broader technology ecosystem. The development of FLARE-AI follows a 2024 industry workshop that highlighted the urgent need for standardized AI vulnerability reporting and improved information-sharing infrastructure. The platform aligns with recent federal directives advocating for a centralized AI cybersecurity clearinghouse to strengthen vulnerability discovery, validation, and remediation. By adapting proven software security practices to the AI domain, FLARE-AI bridges the traditionally siloed AI research and cybersecurity communities. Lauren McIlvenny, technical director of threat analysis at the SEI and project adviser, emphasized that the initiative marks a maturation phase for AI development, similar to the security evolution seen in cloud computing and industrial control systems. She noted that the platform provides a structured environment for AI researchers to adopt coordinated vulnerability disclosure processes. Ultimately, FLARE-AI establishes a collective security framework, enabling the technology sector to systematically identify, report, and neutralize AI flaws before they cascade across interconnected products and services.