An Empirical Assessment of Security and Privacy Risks of Web based-Chatbots
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Abstract (arXiv)
Web-based chatbots provide website owners with the benefits of increased sales, immediate response to their customers, and insight into customer behaviour. While Web-based chatbots are getting popular, they have not received much scrutiny from security researchers. The benefits to owners come at the cost of users' privacy and security. Vulnerabilities, such as tracking cookies and third-party domains, can be hidden in the chatbot's iFrame script. This paper presents a large-scale analysis of five Web-based chatbots among the top 1-million Alexa websites. Through our crawler tool, we identify the presence of chatbots in these 1-million websites. We discover that 13,515 out of the top 1-million Alexa websites (1.59%) use one of the five analysed chatbots. Our analysis reveals that the top 300k Alexa ranking websites are dominated by Intercom chatbots that embed the least number of third-party domains. LiveChat chatbots dominate the remaining websites and embed the highest samples of third-party domains. We also find that 850 (6.29%) of the chatbots use insecure protocols to transfer users' chats in plain text. Furthermore, some chatbots heavily rely on cookies for tracking and advertisement purposes. More than two-thirds (68.92%) of the identified cookies in chatbot iFrames are used for ads and tracking users. Our results show that, despite the promises for privacy, security, and anonymity given by the majority of the websites, millions of users may unknowingly be subject to poor security guarantees by chatbot service providers
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 May 2022.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 2.
4 papers.
- 2025A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasurescited by 54
- 2023Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendationscited by 7
- 2024Measuring, Modeling, and Helping People Account for Privacy Risks in Online Self-Disclosures with AIcited by 4
- 2025Can I Trust This Chatbot? Assessing User Privacy in AI-Healthcare Chatbot Applicationscited by 2
- 2025Can I Trust This Chatbot? Assessing User Privacy in AI-Healthcare Chatbot Applications18 Sep 2025
- 2025A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures24 Jun 2025
- 2024Measuring, Modeling, and Helping People Account for Privacy Risks in Online Self-Disclosures with AI19 Dec 2024
- 2023Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations29 May 2023