# Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations

arXiv: https://arxiv.org/abs/2306.09255 · HTML: https://mlsanity.com/paper/2306.09255/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 115 references that are in the map.
- First posted on arXiv 29 May 2023.

## Builds on (most cited first, 29 of 29)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [Defending Against Neural Fake News](https://mlsanity.com/paper/1905.12616/) (2019)
- [Mathematical Capabilities of ChatGPT](https://mlsanity.com/paper/2301.13867/) (2023)
- [Recent Trends in Deep Learning Based Natural Language Processing](https://mlsanity.com/paper/1708.02709/) (2017)
- [A Survey on Dialogue Systems: Recent Advances and New Frontiers](https://mlsanity.com/paper/1711.01731/) (2017)
- [Neural Responding Machine for Short-Text Conversation](https://mlsanity.com/paper/1503.02364/) (2015)
- [Adversarial Reprogramming of Neural Networks](https://mlsanity.com/paper/1806.11146/) (2018)
- [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://mlsanity.com/paper/1506.06714/) (2015)
- [DolphinAtack: Inaudible Voice Commands](https://mlsanity.com/paper/1708.09537/) (2017)
- [Targeted Phishing Campaigns using Large Scale Language Models](https://mlsanity.com/paper/2301.00665/) (2022)
- [An Information Retrieval Approach to Short Text Conversation](https://mlsanity.com/paper/1408.6988/) (2014)
- [Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements](https://mlsanity.com/paper/2001.00623/) (2020)
- [Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference](https://mlsanity.com/paper/2108.11673/) (2021)
- [Artificial Intelligence MArkup Language: A Brief Tutorial](https://mlsanity.com/paper/1307.3091/) (2013)
- [The Insecurity of Home Digital Voice Assistants -- Amazon Alexa as a Case Study](https://mlsanity.com/paper/1712.03327/) (2017)
- [An Empirical Assessment of Security and Privacy Risks of Web based-Chatbots](https://mlsanity.com/paper/2205.08252/) (2022)
- [Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants](https://mlsanity.com/paper/2301.06544/) (2023)
- [Digital Forensic Approaches for Amazon Alexa Ecosystem](https://mlsanity.com/paper/1707.08696/) (2017)
- [Seq2Seq AI Chatbot with Attention Mechanism](https://mlsanity.com/paper/2006.02767/) (2020)
- [Hello Me, Meet the Real Me: Audio Deepfake Attacks on Voice Assistants](https://mlsanity.com/paper/2302.10328/) (2023)
- [Community Targeted Phishing: A Middle Ground Between Massive and Spear Phishing through Natural Language Generation](https://mlsanity.com/paper/1708.07342/) (2017)
- [Towards Vulnerability Analysis of Voice-Driven Interfaces and Countermeasures for Replay](https://mlsanity.com/paper/1904.06591/) (2019)
- [Living-off-the-Land Abuse Detection Using Natural Language Processing and Supervised Learning](https://mlsanity.com/paper/2208.12836/) (2022)
- [Zero Botnets: An Observe-Pursue-Counter Approach](https://mlsanity.com/paper/2201.06068/) (2022)

## Built on by (most cited first, 8 of 8)

- [A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly](https://mlsanity.com/paper/2312.02003/) (2023)
- [RatGPT: Turning online LLMs into Proxies for Malware Attacks](https://mlsanity.com/paper/2308.09183/) (2023)
- [Deep Learning for Steganalysis of Diverse Data Types: A review of methods, taxonomy, challenges and future directions](https://mlsanity.com/paper/2308.04522/) (2023)
- [Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awareness](https://mlsanity.com/paper/2401.15127/) (2024)
- [Evaluating LLM-based Personal Information Extraction and Countermeasures](https://mlsanity.com/paper/2408.07291/) (2024)
- [The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie](https://mlsanity.com/paper/2309.02029/) (2023)
- [Multi-Agent Framework for Threat Mitigation and Resilience in AI-Based Systems](https://mlsanity.com/paper/2512.23132/) (2025)
- [GPT-Enabled Cybersecurity Training: A Tailored Approach for Effective Awareness](https://mlsanity.com/paper/2405.04138/) (2024)

## Abstract (arXiv)

Chatbots shifted from rule-based to artificial intelligence techniques and gained traction in medicine, shopping, customer services, food delivery, education, and research. OpenAI developed ChatGPT blizzard on the Internet as it crossed one million users within five days of its launch. However, with the enhanced popularity, chatbots experienced cybersecurity threats and vulnerabilities. This paper discussed the relevant literature, reports, and explanatory incident attacks generated against chatbots. Our initial point is to explore the timeline of chatbots from ELIZA (an early natural language processing computer program) to GPT-4 and provide the working mechanism of ChatGPT. Subsequently, we explored the cybersecurity attacks and vulnerabilities in chatbots. Besides, we investigated the ChatGPT, specifically in the context of creating the malware code, phishing emails, undetectable zero-day attacks, and generation of macros and LOLBINs. Furthermore, the history of cyberattacks and vulnerabilities exploited by cybercriminals are discussed, particularly considering the risk and vulnerabilities in ChatGPT. Addressing these threats and vulnerabilities requires specific strategies and measures to reduce the harmful consequences. Therefore, the future directions to address the challenges were presented.