Modernizing National Emergency Response and Artificial Intelligence Security Infrastructure

The National Nuclear Security Administration (NNSA) secures and protects the nation’s nuclear security enterprise, including monitoring threats and coordinating responses for facilities and the American public. NNSA’s missions are facing increasing challenges: heightened vulnerability to severe wildfires, the need for rapid radiological incident assessment, and emerging risks from artificial intelligence (AI) technologies that could compromise nuclear security.

To address these challenges, NNSA seeks TMF investment to modernize the foundational technology infrastructure supporting its nuclear security missions through an integrated cloud and AI transformation. Current systems have critical vulnerabilities: the FireGuard wildfire monitoring activity requires intensive manual analysis across classification barriers; the Turbo Federal Radiological Monitoring and Assessment Center (FRMAC) radiological assessment tool cannot communicate with other emergency response applications; and limited AI development infrastructure prevents rapid evaluation of models for nuclear security threats. These vulnerabilities hamper data aggregation, slow emergency response, and leave gaps in the agency’s ability to assess evolving technological risks.

With $28,372,000 in TMF support, NNSA plans to modernize systems for emergency response and to advance the assessment of emergent technologies. This investment will support three high-priority workstreams:

• FireGuard is an interagency activity in which the National Guard provides wildfire intelligence to NNSA, the U.S. Forest Service, and State agencies. Agencies, including NNSA, use these alerts to reduce response times to wildfires. Through the TMF, FireGuard aims to use machine learning to automatically track fire boundaries and move data between computing systems. This automation would allow analysts to spend their time verifying maps instead of drawing them from scratch, which is particularly critical as wildfires pose growing risks to nuclear sites.
• The Turbo FRMAC radiological assessment tool cannot communicate with other response applications that emergency teams rely on. This isolation forces analysts to perform time‑consuming manual data transfers, slowing the overall response to radiological incidents. Through the TMF, NNSA plans to shift the Turbo FRMAC radiological assessment tool from its legacy desktop software to a cloud‑based platform, providing emergency teams with the speed, accuracy, and collaborative capability they need to protect the public and critical infrastructure during radiological crises.
• Improved AI infrastructure is expected to provide NNSA with the ability to rapidly build, deploy, and rigorously test AI models for nuclear security. Through the TMF, NNSA intends to develop capabilities that could detect or mitigate nuclear-security threats while ensuring these new capabilities enhance security rather than introduce new risks.

By integrating effort across these workstreams, NNSA will move toward a resilient, future-ready technology ecosystem where automated threat detection systems, cloud-based emergency tools, and robust AI security frameworks work together to protect critical nuclear assets. As wildfire frequency intensifies and AI capabilities evolve, this investment positions NNSA’s emergency response teams with scalable, interoperable technology that can adapt to emerging threats while maintaining the highest standards of nuclear security.