# Cyber Sentinel: Exploring Conversational Agents in Streamlining Security Tasks with GPT-4 arXiv: https://arxiv.org/abs/2309.16422 ยท HTML: https://mlsanity.com/paper/2309.16422/ ## Key facts - Cited by 9 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 22 of its 64 references that are in the map. - First posted on arXiv 28 Sep 2023. ## 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, 22 of 22) - [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017) - [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018) - [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023) - [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022) - [Self-Consistency Improves Chain of Thought Reasoning in Language Models](https://mlsanity.com/paper/2203.11171/) (2022) - [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://mlsanity.com/paper/2305.10601/) (2023) - [A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT](https://mlsanity.com/paper/2302.11382/) (2023) - [A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT](https://mlsanity.com/paper/2303.04226/) (2023) - [From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy](https://mlsanity.com/paper/2307.00691/) (2023) - [ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models](https://mlsanity.com/paper/2302.07257/) (2023) - [PentestGPT: An LLM-empowered Automatic Penetration Testing Tool](https://mlsanity.com/paper/2308.06782/) (2023) - [A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?](https://mlsanity.com/paper/2303.11717/) (2023) - [Getting pwn'd by AI: Penetration Testing with Large Language Models](https://mlsanity.com/paper/2308.00121/) (2023) - [Generating Fake Cyber Threat Intelligence Using Transformer-Based Models](https://mlsanity.com/paper/2102.04351/) (2021) - [Slot Self-Attentive Dialogue State Tracking](https://mlsanity.com/paper/2101.09374/) (2021) - [Targeted Phishing Campaigns using Large Scale Language Models](https://mlsanity.com/paper/2301.00665/) (2022) - [A Survey on Adversarial Attacks for Malware Analysis](https://mlsanity.com/paper/2111.08223/) (2021) - [Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence](https://mlsanity.com/paper/2010.13637/) (2020) - [ChatIDS: Advancing Explainable Cybersecurity Using Generative AI](https://mlsanity.com/paper/2306.14504/) (2023) - [Chatbots in a Botnet World](https://mlsanity.com/paper/2212.11126/) (2022) - [Cyber-All-Intel: An AI for Security related Threat Intelligence](https://mlsanity.com/paper/1905.02895/) (2019) - [A Brief Introduction to Generative Models](https://mlsanity.com/paper/2103.00265/) (2021) ## Built on by (most cited first, 9 of 9) - [AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks](https://mlsanity.com/paper/2403.01038/) (2024) - [When LLMs Meet Cybersecurity: A Systematic Literature Review](https://mlsanity.com/paper/2405.03644/) (2024) - [ThreatModeling-LLM: Automating Threat Modeling using Large Language Models for Banking System](https://mlsanity.com/paper/2411.17058/) (2024) - [Large Language Models for Security Operations Centers: A Comprehensive Survey](https://mlsanity.com/paper/2509.10858/) (2025) - [Auspex: Building Threat Modeling Tradecraft into an Artificial Intelligence-based Copilot](https://mlsanity.com/paper/2503.09586/) (2025) - [FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations](https://mlsanity.com/paper/2506.11635/) (2025) - [Generative AI for Internet of Things Security: Challenges and Opportunities](https://mlsanity.com/paper/2502.08886/) (2025) - [SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization](https://mlsanity.com/paper/2604.26394/) (2026) - [COHORT: Collaborative Orchestration for Hardening via Offensive Replay on Emulated Topologies](https://mlsanity.com/paper/2606.30479/) (2026) ## Abstract (arXiv) In an era where cyberspace is both a battleground and a backbone of modern society, the urgency of safeguarding digital assets against ever-evolving threats is paramount. This paper introduces Cyber Sentinel, an innovative task-oriented cybersecurity dialogue system that is effectively capable of managing two core functions: explaining potential cyber threats within an organization to the user, and taking proactive/reactive security actions when instructed by the user. Cyber Sentinel embodies the fusion of artificial intelligence, cybersecurity domain expertise, and real-time data analysis to combat the multifaceted challenges posed by cyber adversaries. This article delves into the process of creating such a system and how it can interact with other components typically found in cybersecurity organizations. Our work is a novel approach to task-oriented dialogue systems, leveraging the power of chaining GPT-4 models combined with prompt engineering across all sub-tasks. We also highlight its pivotal role in enhancing cybersecurity communication and interaction, concluding that not only does this framework enhance the system's transparency (Explainable AI) but also streamlines the decision-making process and responding to threats (Actionable AI), therefore marking a significant advancement in the realm of cybersecurity communication.