NIST and CISA finalise token-forgery guidance and name AI agents as users of the same signed tokens
NIST published IR 8587, “Protecting Tokens and Assertions from Forgery, Theft, and Misuse: Implementation Recommendations for Agencies and Cloud Service Providers,” as a final report on September 15, authored by Ryan Galluzzo and Andrew Regenscheid of NIST, Stephanie Nelson of Accenture Federal Services and Christine Lazcano of CISA. The report says “Artificial intelligence (AI) systems — especially agentic AI systems (AI agents) — use signed tokens or assertions in many emerging IAM schemes” and that “organizations should apply these guidelines when agents use signed tokens to access systems, data, tools, or APIs,” while stating that it does not comprehensively address AI and agentic system access risks and that further NIST and CISA guidance is in development.
A bipartisan House bill would have NIST write standards for finding, verifying and cutting off AI agents
Reps. Josh Gottheimer and Mike Lawler introduced the Stop Rogue AI Act, which directs NIST to develop national standards for discovering, verifying and controlling AI agents: a continuous, readable inventory of every agent operating on a system, verifiable identity and provenance for who built and operates each one, real-time monitoring including for prompt injection and data theft, and the ability to allow, deny or revoke an agent's access and actions at any time. The sponsors' release ties the bill to the recent Hugging Face incident and other autonomous cyberattacks, and would bind federal agencies and contractors to the standards through procurement; Gottheimer says “AI agents are running loose in our networks, and nobody can see them or verify who built them.” No bill number appears on the release.
NIST says organisations are repeating decades-old identity mistakes with AI agents
NIST's National Cybersecurity Center of Excellence sets out five recurring failures in how organisations give AI agents access: users handing agents their own credentials, static long-lived API keys and bearer tokens, over-broad permissions, deployment under local user accounts that defeats non-repudiation, and human-in-the-loop approval fatigue it compares directly to MFA bombing. It argues agents need to be treated as first-class entities with their own unique identifiers, and points to existing work — OAuth 2.0, SPIFFE and WIMSE — rather than new frameworks.
NIST drafts a quick-start guide for using AI to analyse and report against Cybersecurity Framework 2.0
NIST released the initial public draft of Special Publication 1353, “NIST Cybersecurity Framework 2.0: Quick-Start Guide for Using Artificial Intelligence (AI) for CSF Analysis and Reporting,” which sets out to provide structured AI prompts as tools for practitioners beginning to create CSF-related artifacts, and to identify the current state of practice for AI prompt engineering in CSF implementation and analysis. Comments are due October 15, 2026.
NIST opens a request for information on modernizing the National Vulnerability Database in the age of AI
NIST published a request for information in the Federal Register, at 91 FR 52042, seeking stakeholder input on opportunities, challenges and priorities for modernizing the National Vulnerability Database in a landscape shaped by artificial intelligence and machine-consumable security data, referencing AI-enabled cyber tools, AI-enabled automation and AI-assisted vulnerability discovery among the topics. Comments are due October 13, 2026 at 11:59 p.m. Eastern.
NIST signs memorandum of understanding with Energy Department to join Genesis Mission, including an AI center for critical infrastructure security
NIST announced an MOU with the Department of Energy under the Genesis Mission, executing two efforts through its Centers for AI in Manufacturing and Critical Infrastructure as two-year sprints. One is an AI Economic Security Center to Secure U.S. Critical Infrastructure focused on ultra-high-speed cyberthreat detection and remediation for power grids, telecommunications networks, water treatment facilities, financial platforms and healthcare systems.
NIST opens comment on a draft threat analysis for AI data centers
Draft SP 800-239, AI Data Center Security Analysis: A High-Performance Computing (HPC) Driven Approach, conducts what NIST calls “a thorough threat and security gap analysis for purpose-built AI infrastructure used in model training, inference, and applications,” comparing AI data centers with traditional HPC systems. The public comment period runs through 25 September 2026.
NIST director Arvind Raman named acting CAISI head after Fall's exit
NIST Director Arvind Raman was named acting director of the Center for AI Standards and Innovation after Chris Fall resigned on July 20 — about three months in, and after a predecessor who lasted under a week. Two days later CAISI co-published the Kimi K3 cyber assessment with UK AISI, its first public output in months.