Chatbots in a Honeypot World
Not on the map. Why?
Abstract (arXiv)
Question-and-answer agents like ChatGPT offer a novel tool for use as a potential honeypot interface in cyber security. By imitating Linux, Mac, and Windows terminal commands and providing an interface for TeamViewer, nmap, and ping, it is possible to create a dynamic environment that can adapt to the actions of attackers and provide insight into their tactics, techniques, and procedures (TTPs). The paper illustrates ten diverse tasks that a conversational agent or large language model might answer appropriately to the effects of command-line attacker. The original result features feasibility studies for ten model tasks meant for defensive teams to mimic expected honeypot interfaces with minimal risks. Ultimately, the usefulness outside of forensic activities stems from whether the dynamic honeypot can extend the time-to-conquer or otherwise delay attacker timelines short of reaching key network assets like databases or confidential information. While ongoing maintenance and monitoring may be required, ChatGPT's ability to detect and deflect malicious activity makes it a valuable option for organizations seeking to enhance their cyber security posture. Future work will focus on cybersecurity layers, including perimeter security, host virus detection, and data security.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 4 of its 28 references that are in the map. First posted on arXiv 10 Jan 2023.
Builds on
4 of 28 references.
References · 4
- 2022Reasoning with Language Model Prompting: A Surveycited by 251
- 2022Targeted Phishing Campaigns using Large Scale Language Modelscited by 22
- 2022Chatbots in a Botnet Worldcited by 8
- 2016A Survey on Honeypot Software and Data Analysiscited by 7
Built on by
Citing papers per year: 2023: 5; 2024: 3; 2025: 0; 2026: 1.
9 papers.
- 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 152
- 2024Large Language Models in Cybersecurity: State-of-the-Artcited by 34
- 2023LLM in the Shell: Generative Honeypotscited by 19
- 2024Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awarenesscited by 14
- 2024LLM Honeypot: Leveraging Large Language Models as Advanced Interactive Honeypot Systemscited by 10
- 2023Numeracy from Literacy: Data Science as an Emergent Skill from Large Language Modelscited by 8
- 2023Scamming the Scammers: Using ChatGPT to Reply Mails for Wasting Time and Resourcescited by 8
- 2023Grading Conversational Responses Of Chatbotscited by 1
- 2026AdvancedShelLM: A Stateful Multi-Agent LLM Honeypot for SSH Deceptioncited by 1
- 2026AdvancedShelLM: A Stateful Multi-Agent LLM Honeypot for SSH Deception26 Jun 2026
- 2024LLM Honeypot: Leveraging Large Language Models as Advanced Interactive Honeypot Systems12 Sep 2024
- 2024Large Language Models in Cybersecurity: State-of-the-Art30 Jan 2024
- 2024Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awareness26 Jan 2024
- 2023LLM in the Shell: Generative Honeypots31 Aug 2023
- 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models4 Apr 2023
- 2023Scamming the Scammers: Using ChatGPT to Reply Mails for Wasting Time and Resources10 Feb 2023
- 2023Grading Conversational Responses Of Chatbots1 Feb 2023
- 2023Numeracy from Literacy: Data Science as an Emergent Skill from Large Language Models31 Jan 2023