# ThreatGPT: An Agentic AI Framework for Enhancing Public Safety through Threat Modeling

arXiv: https://arxiv.org/abs/2509.05379 · HTML: https://mlsanity.com/paper/2509.05379/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 4 of its 30 references that are in the map.
- First posted on arXiv 4 Sep 2025.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 4 of 4)

- [Reinforcement learning](https://mlsanity.com/paper/2405.10369/) (2024)
- [Generative AI](https://mlsanity.com/paper/2309.07930/) (2023)
- [Learning from Few Examples: A Summary of Approaches to Few-Shot Learning](https://mlsanity.com/paper/2203.04291/) (2022)
- [Securing the Digital World: Protecting smart infrastructures and digital industries with Artificial Intelligence (AI)-enabled malware and intrusion detection](https://mlsanity.com/paper/2401.01342/) (2023)

## Built on by (most cited first, 3 of 3)

- [LLMAC: A Global and Explainable Access Control Framework with Large Language Model](https://mlsanity.com/paper/2602.09392/) (2026)
- [Multi-Agent Collaborative Intrusion Detection for Low-Altitude Economy IoT: An LLM-Enhanced Agentic AI Framework](https://mlsanity.com/paper/2601.17817/) (2026)
- [Trust propagation and structural containment in Multi-agent LLM pipelines](https://mlsanity.com/paper/2609.17648/) (2026)

## Abstract (arXiv)

As our cities and communities become smarter, the systems that keep us safe, such as traffic control centers, emergency response networks, and public transportation, also become more complex. With this complexity comes a greater risk of security threats that can affect not just machines but real people's lives. To address this challenge, we present ThreatGPT, an agentic Artificial Intelligence (AI) assistant built to help people whether they are engineers, safety officers, or policy makers to understand and analyze threats in public safety systems. Instead of requiring deep cybersecurity expertise, it allows users to simply describe the components of a system they are concerned about, such as login systems, data storage, or communication networks. Then, with the click of a button, users can choose how they want the system to be analyzed by using popular frameworks such as STRIDE, MITRE ATT&CK, CVE reports, NIST, or CISA. ThreatGPT is unique because it does not just provide threat information, but rather it acts like a knowledgeable partner. Using few-shot learning, the AI learns from examples and generates relevant smart threat models. It can highlight what might go wrong, how attackers could take advantage, and what can be done to prevent harm. Whether securing a city's infrastructure or a local health service, this tool adapts to users' needs. In simple terms, ThreatGPT brings together AI and human judgment to make our public systems safer. It is designed not just to analyze threats, but to empower people to understand and act on them, faster, smarter, and with more confidence.