H.R.7696

AI Cyber Grid Protection Resilient Development Act of 2026

Introduced·2/25/26

Overview

This bill establishes a federal grant program designed to enhance the nation's cybersecurity infrastructure by creating advanced testing environments for grid-scale cyberattack simulations. The legislation authorizes awards to National Laboratories and institutions of higher education for the specific purpose of developing secure artificial intelligence cyber-physical testbeds. These testbeds will serve as sophisticated simulation platforms capable of modeling and analyzing large-scale cyberattacks against critical energy infrastructure. The bill addresses the growing intersection of artificial intelligence, cybersecurity, and critical infrastructure protection, recognizing that modern grid systems face increasingly sophisticated cyber threats that require advanced testing and defense mechanisms. By leveraging the technical expertise of National Laboratories and academic institutions, the program aims to create realistic testing environments where cybersecurity professionals can develop, test, and refine defensive strategies without risking actual grid infrastructure.

Core Provisions

The bill creates a new grant program administered through federal channels to support the development of AI-enabled cyber-physical testbeds specifically designed for grid-scale cyberattack simulation. The program designates National Laboratories and institutions of higher education as eligible recipients for grant awards. The testbeds must incorporate artificial intelligence capabilities and maintain secure operational environments to prevent actual security breaches during testing. The cyber-physical nature of these testbeds indicates they will combine both digital cybersecurity elements and physical infrastructure components to accurately simulate real-world grid operations and attack scenarios. While the bill establishes the program framework and identifies eligible entities, it does not specify the authorization amounts, appropriation levels, or the duration of the grant program.

Key Points

  • Creation of a competitive grant program for AI cyber-physical testbed development
  • Eligibility limited to National Laboratories and institutions of higher education
  • Testbeds must simulate grid-scale cyberattacks with secure AI integration
  • Focus on cyber-physical systems that replicate actual grid infrastructure

Implementation

The implementation structure designates National Laboratories and institutions of higher education as both the implementing entities and grant recipients, creating a decentralized execution model. While the bill does not explicitly identify the administering federal agency, the involvement of National Laboratories suggests oversight by the Department of Energy or a related agency with jurisdiction over both energy infrastructure and national laboratory operations. The absence of specified funding mechanisms, appropriation amounts, or reporting requirements in the available text indicates these details may be contained in subsequent sections or left to regulatory implementation. Grant recipients will bear the primary responsibility for designing, constructing, and operating the secure testbeds, with compliance requirements focused on maintaining security protocols and achieving the simulation capabilities outlined in the grant awards.

Impact

The primary beneficiaries of this legislation include National Laboratories and institutions of higher education that will receive grant funding to develop cutting-edge cybersecurity research capabilities. Secondary beneficiaries encompass the broader energy sector, including utilities, grid operators, and infrastructure providers who will benefit from improved cybersecurity defenses developed through testbed research. The program will enhance national security by creating dedicated environments for testing defensive measures against sophisticated cyberattacks without risking operational grid systems. The testbeds will provide training opportunities for cybersecurity professionals and researchers, advancing workforce development in critical infrastructure protection. While cost estimates are not provided in the available text, the development of secure AI cyber-physical testbeds capable of grid-scale simulation represents a significant investment in both physical infrastructure and advanced computing capabilities. The administrative burden will fall primarily on grant recipients who must design and maintain complex testing environments while ensuring security protocols prevent unauthorized access or unintended consequences from simulation activities.

Legal Framework

The constitutional basis for this legislation derives from Congress's authority to provide for the common defense and general welfare under Article I, Section 8 of the Constitution, as well as its power to regulate interstate commerce, which encompasses the electrical grid infrastructure that crosses state boundaries. The program operates within the existing framework of federal grant-making authority and builds upon statutory foundations governing National Laboratories and federal support for higher education research. The involvement of National Laboratories suggests connection to the Department of Energy Organization Act and related statutes establishing the national laboratory system. The bill will require implementing regulations to establish grant application procedures, selection criteria, security standards for testbed operations, and performance metrics for funded projects. The legislation does not appear to preempt state or local authority over energy infrastructure but rather creates a parallel federal research capability to support cybersecurity improvements across jurisdictions.

Critical Issues

Implementation challenges center on the technical complexity of creating realistic grid-scale simulation environments that accurately replicate both the physical infrastructure and cyber components of modern electrical grids. The secure integration of artificial intelligence into these testbeds presents additional challenges, as AI systems themselves can introduce vulnerabilities while simultaneously serving as defensive tools. The absence of specified funding levels creates uncertainty about the program's scale and sustainability, potentially limiting the number and sophistication of testbeds that can be developed. Coordination between multiple National Laboratories and academic institutions may prove difficult without clear governance structures and data-sharing protocols. Security concerns arise from the dual-use nature of cyberattack simulation capabilities, which could potentially be exploited if testbed security is compromised. The bill may face scrutiny regarding the appropriate balance between federal investment in research infrastructure versus direct grid hardening measures. Questions may arise about whether limiting eligibility to National Laboratories and institutions of higher education excludes private sector entities with relevant expertise in grid operations and cybersecurity. The lack of specified performance metrics or accountability measures could complicate oversight and assessment of program effectiveness.

Key Points

  • Technical complexity of creating accurate grid-scale cyber-physical simulations
  • Security risks inherent in developing sophisticated cyberattack simulation capabilities
  • Coordination challenges among multiple laboratories and academic institutions
  • Absence of funding specifications creates program scope uncertainty
  • Potential exclusion of private sector grid operators and cybersecurity firms
  • Need for robust security protocols to prevent testbed exploitation

Where it stands

Current
Subcommittee on Cybersecurity and Infrastructure Protection Committee
Next
Committee decision

Sponsors

3
0
Democratic CaucusRepublican Caucus

History

Feb 26

House

Referred to the Subcommittee on Cybersecurity and Infrastructure Protection.

Feb 25

House

Introduced in House

Feb 25

House

Referred to the House Committee on Homeland Security.