{"id":41493,"date":"2023-05-28T15:18:54","date_gmt":"2023-05-28T12:18:54","guid":{"rendered":"https:\/\/saudishopper.com.sa\/en\/?p=41493"},"modified":"2026-03-28T03:21:42","modified_gmt":"2026-03-28T00:21:42","slug":"chatgpt-phishing-fantasies-will-ai-chatbots-help-fight-cyberscam","status":"publish","type":"post","link":"https:\/\/saudishopper.com.sa\/en\/chatgpt-phishing-fantasies-will-ai-chatbots-help-fight-cyberscam\/","title":{"rendered":"ChatGPT phishing fantasies: will AI chatbots help fight cyberscam?\u00a0"},"content":{"rendered":"\n

Kaspersky experts have conducted research studying ChatGPT phishing links detection capability. While ChatGPT had previously demonstrated the ability to\u00a0<\/strong>create<\/strong><\/a>\u00a0phishing emails and write\u00a0<\/strong>malware<\/strong><\/a>, its effectiveness in detecting malicious links was limited.\u00a0The study revealed that although ChatGPT knows a great deal about phishing and can guess the target of a phishing attack, it had high false positive rates of up to 64 percent. Often, it produced imaginary explanations and false evidence to justify its verdicts.<\/strong><\/p>\n\n\n\n

ChatGPT, an AI-powered language model, has been a topic of discussion in the cybersecurity world due to its potential to create phishing emails and the concerns about its impact on cybersecurity experts\u2019 job security even despite its creators\u2019 warnings that it is too early to apply the novel technology to such high-risk domains. Kaspersky experts decided to conduct an experiment to reveal ChatGPT\u2019s ability to detect phishing links, as well as the cybersecurity knowledge it learned during training. Company\u2019s experts tested gpt-3.5-turbo, the model that powers ChatGPT, on more than 2,000 links that Kaspersky anti-phishing technologies deemed phishing, and mixed it with thousands of safe URLs.<\/p>\n\n\n\n

In the experiment, detection rates varies depending on the prompt used. The experiment was based on asking ChatGPT two questions: \u201cDoes this link lead to a phishing website?\u201d and \u201cIs this link safe to visit?\u201d. The results showed that ChatGPT had a detection rate of 87.2% and a false positive rate of 23.2% for the first question. The second question, \u201cIs this link safe to visit?\u201d had a higher detection rate of 93.8%, but a higher false positive rate of 64.3%. While the detection rate is very high, the false positive rate is too high for any kind of production application. <\/p>\n\n\n\n

Question asked<\/strong><\/td>Detection rate<\/strong><\/td>False positive rate<\/strong><\/td><\/tr>
Does this link lead to a phishing website?<\/td>87.2%<\/strong><\/td>23.2%<\/strong><\/td><\/tr>
Is this link safe to visit?<\/td>93.8%<\/strong><\/td>64.3%<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n


The unsatisfactory results at the detection task were expected, but could ChatGPT help with classifying and investigating attacks? Since attackers typically mention popular brands in their links to deceive users into believing that the URL is legitimate and belongs to a reputable company, the AI language model shows impressive results in the identification of potential phishing targets. For instance, ChatGPT has successfully extracted a target from more than half of the URLs, including major tech portals like Facebook, TikTok, and Google, marketplaces such as Amazon and Steam, and numerous banks from around the globe, among others \u2013 without any additional training.<\/p>\n\n\n\n

The experiment also showed ChatGPT might have serious problems when it comes to proving its point on the decision whether the link is malicious. Some explanations were correct and based on facts, others revealed known limitations of language models, including hallucinations and misstatements: many explanations were misleading, despite the confident tone.<\/p>\n\n\n\n

Below are the examples of misleading explanations provided by ChatGPT:<\/em><\/p>\n\n\n\n