Generating Phishing Attacks using ChatGPT
- URL: http://arxiv.org/abs/2305.05133v1
- Date: Tue, 9 May 2023 02:38:05 GMT
- Title: Generating Phishing Attacks using ChatGPT
- Authors: Sayak Saha Roy, Krishna Vamsi Naragam, Shirin Nilizadeh
- Abstract summary: We identify several malicious prompts that can be provided to ChatGPT to generate functional phishing websites.
These attacks can be generated using vanilla ChatGPT without the need of any prior adversarial exploits.
- Score: 1.392250707100996
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The ability of ChatGPT to generate human-like responses and understand
context has made it a popular tool for conversational agents, content creation,
data analysis, and research and innovation. However, its effectiveness and ease
of accessibility makes it a prime target for generating malicious content, such
as phishing attacks, that can put users at risk. In this work, we identify
several malicious prompts that can be provided to ChatGPT to generate
functional phishing websites. Through an iterative approach, we find that these
phishing websites can be made to imitate popular brands and emulate several
evasive tactics that have been known to avoid detection by anti-phishing
entities. These attacks can be generated using vanilla ChatGPT without the need
of any prior adversarial exploits (jailbreaking).
Related papers
- From ML to LLM: Evaluating the Robustness of Phishing Webpage Detection Models against Adversarial Attacks [0.8050163120218178]
Phishing attacks attempt to deceive users into stealing sensitive information.
Current phishing webpage detection solutions are vulnerable to adversarial attacks.
We develop a tool that generates adversarial phishing webpages by embedding diverse phishing features into legitimate webpages.
arXiv Detail & Related papers (2024-07-29T18:21:34Z) - Evaluating the Efficacy of Large Language Models in Identifying Phishing Attempts [2.6012482282204004]
Phishing, a prevalent cybercrime tactic for decades, remains a significant threat in today's digital world.
This paper aims to analyze the effectiveness of 15 Large Language Models (LLMs) in detecting phishing attempts.
arXiv Detail & Related papers (2024-04-23T19:55:18Z) - AbuseGPT: Abuse of Generative AI ChatBots to Create Smishing Campaigns [0.0]
We propose AbuseGPT method to show how the existing generative AI-based chatbots can be exploited by attackers in real world to create smishing texts.
We have found strong empirical evidences to show that attackers can exploit ethical standards in the existing generative AI-based chatbots services.
We also discuss some future research directions and guidelines to protect the abuse of generative AI-based services.
arXiv Detail & Related papers (2024-02-15T05:49:22Z) - Exploring ChatGPT's Capabilities on Vulnerability Management [56.4403395100589]
We explore ChatGPT's capabilities on 6 tasks involving the complete vulnerability management process with a large-scale dataset containing 70,346 samples.
One notable example is ChatGPT's proficiency in tasks like generating titles for software bug reports.
Our findings reveal the difficulties encountered by ChatGPT and shed light on promising future directions.
arXiv Detail & Related papers (2023-11-11T11:01:13Z) - From Chatbots to PhishBots? -- Preventing Phishing scams created using
ChatGPT, Google Bard and Claude [3.7741995290294943]
This study explores the potential of using four popular commercially available Large Language Models to generate phishing attacks.
We build a BERT-based automated detection tool that can be used for the early detection of malicious prompts.
Our model is transferable across all four commercial LLMs, attaining an average accuracy of 96% for phishing website prompts and 94% for phishing email prompts.
arXiv Detail & Related papers (2023-10-29T22:52:40Z) - Exploring the Dark Side of AI: Advanced Phishing Attack Design and
Deployment Using ChatGPT [2.4178831487657937]
We make ChatGPT generate the following parts of a phishing attack.
We show that recent advances in AI underscore the potential risks of its misuse in phishing attacks.
arXiv Detail & Related papers (2023-09-19T09:31:39Z) - Is ChatGPT Involved in Texts? Measure the Polish Ratio to Detect
ChatGPT-Generated Text [48.36706154871577]
We introduce a novel dataset termed HPPT (ChatGPT-polished academic abstracts)
It diverges from extant corpora by comprising pairs of human-written and ChatGPT-polished abstracts instead of purely ChatGPT-generated texts.
We also propose the "Polish Ratio" method, an innovative measure of the degree of modification made by ChatGPT compared to the original human-written text.
arXiv Detail & Related papers (2023-07-21T06:38:37Z) - ChatGPT for Us: Preserving Data Privacy in ChatGPT via Dialogue Text
Ambiguation to Expand Mental Health Care Delivery [52.73936514734762]
ChatGPT has gained popularity for its ability to generate human-like dialogue.
Data-sensitive domains face challenges in using ChatGPT due to privacy and data-ownership concerns.
We propose a text ambiguation framework that preserves user privacy.
arXiv Detail & Related papers (2023-05-19T02:09:52Z) - To ChatGPT, or not to ChatGPT: That is the question! [78.407861566006]
This study provides a comprehensive and contemporary assessment of the most recent techniques in ChatGPT detection.
We have curated a benchmark dataset consisting of prompts from ChatGPT and humans, including diverse questions from medical, open Q&A, and finance domains.
Our evaluation results demonstrate that none of the existing methods can effectively detect ChatGPT-generated content.
arXiv Detail & Related papers (2023-04-04T03:04:28Z) - Backdoor Attack against Speaker Verification [86.43395230456339]
We show that it is possible to inject the hidden backdoor for infecting speaker verification models by poisoning the training data.
We also demonstrate that existing backdoor attacks cannot be directly adopted in attacking speaker verification.
arXiv Detail & Related papers (2020-10-22T11:10:08Z) - Phishing and Spear Phishing: examples in Cyber Espionage and techniques
to protect against them [91.3755431537592]
Phishing attacks have become the most used technique in the online scams, initiating more than 91% of cyberattacks, from 2012 onwards.
This study reviews how Phishing and Spear Phishing attacks are carried out by the phishers, through 5 steps which magnify the outcome.
arXiv Detail & Related papers (2020-05-31T18:10:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.