Phishing email attacks are among the most common and most harmful cybersecurity attacks. With the emergence of generative AI, phishing attacks can be based on emails generated automatically, making it more difficult to detect them. That is, instead of a single email format sent to a large number of recipients, generative AI can be used to send each potential victim a different email, making it more difficult for cybersecurity systems to identify the scam email before it reaches the recipient. Here we describe a corpus of AI-generated phishing emails. We also use different machine learning tools to test the ability of automatic text analysis to identify AI-generated phishing emails. The results are encouraging, and show that machine learning tools can identify an AI-generated phishing email with high accuracy compared to regular emails or human-generated scam email. By applying descriptive analytic, the specific differences between AI-generated emails and manually crafted scam emails are profiled, and show that AI-generated emails are different in their style from human-generated phishing email scams. Therefore, automatic identification tools can be used as a warning for the user. The paper also describes the corpus of AI-generated phishing emails that is made open to the public, and can be used for consequent studies. While the ability of machine learning to detect AI-generated phishing email is encouraging, AI-generated phishing emails are different from regular phishing emails, and therefore it is important to train machine learning systems also with AI-generated emails in order to repel future phishing attacks that are powered by generative AI.

Here's an experiment being run by undergraduate computer science students everywhere: Ask ChatGPT to generate phishing emails, and test whether these are better at persuading victims to respond or click on the link than the usual spam. It's an interesting experiment, and the results are likely to vary wildly based on the details of the experiment. Bruce Schneier is a lecturer and fellow at the Harvard Kennedy School and chief of security architecture at Inrupt. His latest book is A Hacker's Mind. Barath Raghavan is a professor of computer science at USC and cofounder of INVISV.

Google is blocking more than 18million hoax emails a day as criminals try to snare victims with coronavirus scam messages. The tech giant has more than 1.5 billion users of its Gmail platform and has revealed it is currently blocking more than 100 million phishing emails a day. Almost a fifth of these are using the coronavirus pandemic to try and trick innocent people. Google also says it is seeing an additional 240 million COVID-related daily spam messages. Google has announced it is blocking more than 18million hoax emails a day as criminals try to snare victims with coronavirus scam messages.

The next big trend was a key topic in the fourth World Internet Conference held in Wuzhen recently. During the event, Alibaba founder Jack Ma said humans "have explored less than 10 percent of our brains, and the machine created by that 10 percent knowledge won't beat humans". Tencent founder Ma Huateng noted that internet plus advanced manufacturing will create smart manufacturing that combines software, hardware and services. Meanwhile, Baidu founder Li Yanhong said that the population dividend for the internet industry is ending, and artificial intelligence will be the new growth engine. We are in an era of information explosion thanks to mobile internet and different applications.

Introducing Re:scam – an artificially intelligent email bot made to reply to scam emails. Re:scam wastes scammers time with a never-ending series of questions and anecdotes so that scammers have less time to pursue real people. If you think you've received a scam email, forward it to me@rescam.org We'll even send you a transcript of the conversations Re:scam has had with the scammer – sometimes they can be quite funny! Please note, this can take a while as the bot is designed to reply to the scammer at varying times to appear natural – it may take anywhere from a few seconds to a few days to reply to the scammer each time.