Generative AI Used to Escalate Social Engineering Attacks

It is reported that according to the latest research report released by the network security company Darktrace, attackers use generative AI such as ChatGPT to increase the number of social engineering attacks by 135% by adding text descriptions, punctuation mark and sentence length.

Report: ChatGPT and other generative AI led to a 135% increase in phishing email attacks

As per the latest research report by Darktrace, a network security company, it has been found that attackers are using generative AI like ChatGPT to increase social engineering attacks by 135%. They’re doing this by adding text descriptions, punctuation marks, and changing sentence lengths. Such AI advancements often pose a significant threat to cyber security. In this article, we will understand what generative AI is, how it is used in social engineering, and how to prevent such attacks.

What is Generative AI?

Generative AI is a technique that utilizes deep learning algorithms to create new content. It enables machines to create text, images, and even videos that are similar to what humans would create. Generative AI models work by analyzing patterns in similar data and then generating new content based on these patterns. The ChatGPT model is one such technique that employs Generative AI for text generation.

How Generative AI is Used in Social Engineering Attacks

Social engineering attacks are elaborate techniques used by hackers to exploit psychological manipulation on unsuspecting targets to gain access to confidential information. The attacks can be classified as phishing, pretexting, baiting, and many more. These attacks have been used for a long time, but the emergence of generative AI has made them even more sophisticated and dangerous.
With ChatGPT, attackers can create a story that looks genuine and sounds familiar. They analyze the targets’ social media profiles, their likes, preferences, and recent activities to create a story targeting those individuals directly. Attackers can add a personal touch to their messages, which makes them look genuine and credible. They use punctuation marks and lengthen or shorten sentences depending on the targets’ preferences, which further enhances the authenticity of the messages.

How to Prevent Generative AI Enabled Social Engineering Attacks

Educating employees on potential risks of phishing and how to identify them is an essential first step in preventing social engineering attacks. Regular training sessions and phishing simulations can help to sensitize employees to the risks and reduce the number of successful attacks.
Another effective solution is using advanced threat detection systems that can analyze abnormal patterns and behaviors in the network. These systems can alert organizations when any unusual activity is detected, enabling security teams to take action before any significant damage is caused.

Conclusion

Generative AI is a double-edged sword. It brings about many benefits to machine learning, but it also poses a significant risk that needs to be addressed. With an increase in social engineering attacks by 135%, organizations need to step up their cyber-security measures. Educating employees about phishing and using advanced threat detection systems are some of the preventative measures organizations can take.

FAQs

**Q1. What makes generative AI so dangerous?**
Generative AI makes social engineering attacks far more sophisticated and personal. Attackers can create stories that look and sound authentic, making them far more likely to be successful.
**Q2. How can we protect ourselves from social engineering attacks?**
Organizations need to educate employees regularly about the risks of social engineering and how to spot them. Using advanced threat detection systems can also help detect abnormal network behaviors, enabling security teams to take action before damage is caused.
**Q3. Why is phishing such an effective social engineering tactic?**
Phishing messages are personalized and convincing, making them difficult to identify as scams. They often contain urgent requests, which puts pressure on the recipient to act quickly, overriding their usual skeptical instincts.
##Keywords
Generative AI, social engineering attacks, network security, ChatGPT, advanced threat detection.