Generative Artificial Intelligence (AI) — such as technologies like the large-language models (LLMs) as well as text-to-image and deepfake systems -has provided powerful tools to increase efficiency and creativity. However, these tools are being increasingly used by criminals and other adversaries to unleash increasingly sophisticated and scalable and difficult-to-detect cyberattacks. In this blog we look at the ways that the use of generative AI is becoming more prevalent in cybercrime as well as real-world examples and what security experts need to know to keep ahead of the curve. MakeUseOf+1
1. AI-Powered Phishing and Social Engineering Attacks
One of the biggest applications of the generative AI in cyber-attacks is the creation of deceitful communications to trick victims into giving information or performing fraudulent actions.
Hyper-Convincing Phishing Emails
Generative AI can create emails containing phishing that are accurate in context perfectly grammatically correct, and personalised to the specific needs of each target. In contrast to traditional frauds, these messages are akin to official correspondence, that is, with the appropriate tone, format and even a localized version of the language which makes them more effective in defying the spam filter and avoiding human suspicion. threatsys.co.in+1
Deepfake Audio & Video Impersonation
Attackers employ AI voice the cloning process and deepfake technology to fake the appearance of executives, clients or other trusted contacts during telephone calls or virtual meetings. It can be used to approve fraudulent transactions, change credentials, or alter the behavior of workers in real time. reinhardtsecurity.com+1
Automated Phishing Sites
Certain threat actors have employed generators to construct convincing phishing websites in just a few seconds and trick users into entering login credentials onto replicating platforms. Axios
2. Malware Creation and Evasion
Generative AI doesn’t just serve for deceit, it’s also used to develop and improve malware.
AI-Assisted Malware and Ransomware
Generative AI tools can assist cybercriminals to write ransomware, malware and exploit codes quickly even without a deep understanding of programming. In a few emerging instances, ransomware has been observed to use AI to modify its behavior, and evade detection by conventional security tools. Tom’s Hardware+1
Polymorphic Code
AI can create polymorphic malware – malicious code that alters its signature every time it runs, which makes it difficult for antivirus systems that rely on signatures to detect and stop it. reinhardtsecurity.com
3. Social Engineering Beyond Email
Generative AI isn’t only limited to emails, it’s opening up new avenues for Social Engineering.
Voice Phishing (Vishing)
AI voice cloning technology can create real-looking voicemails or phone calls from trusted numbers, luring victims into divulging sensitive information or making transfers of funds. Forcepoint
Synthetic Identities and Deepfake Profiles
Attackers create realistic fake social profiles or identities to build trust, gain reconnaissance, or penetrate networks. This can be done with fake pictures or personas, as well as fake resumes. Forcepoint
4. Automated Exploit Discovery & Vulnerability Analysis
Generative AI can be utilized to automatize tasks that previously required skilled human expertise.
Finding Software Vulnerabilities
AI models can analyze code bases and find weaknesses that attackers could exploit, thus speeding the process of reconnaissance for an attack. Palo Alto Networks
Automated Hacking Workflows
Advanced threat actors are using the world’s AI models to automate complete attack chains ranging from reconnaissance through exploitationwithout human supervision. The Verge
5. Misinformation, Disinformation & Psychological Operations
Generative AI can be a source of risks that go beyond intrusions by technical means.
Disinformation Campaigns
Criminals use AI-generated content (text videos, images, text) to alter public opinion, create false stories, or cause confusion. Recent events have demonstrated the power of AI to create inaccurate media at a large the scale of the internet, causing distrust in the online world. The Guardian
AI Voice Cloning by Extremists
Extremist groups are making use of technologies that generate voice to create propaganda and recruiting content in a variety of languages, extending their reach on the internet. The Guardian
Real-World Examples of AI-Driven Cyber Threats
Here are a few notable instances that show the way that the generative AI is being used in cyber attacks that are offensive:
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National-state-linked actors automatized parts of their hacking operations using AI models, which reduces the role of humans in strategic choices. The Verge
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Tools that can speed up creating phishing sites have been released freely, allowing low-skill actors to create convincing attacks swiftly. Axios
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AI-generated misinformation triggered by real-world incidents spread quickly across social media platforms, demonstrating how AI can increase confusion. The Guardian
Why Generative AI Makes Cyber Attacks More Dangerous
Generative AI enhances traditional threats in a variety of important ways:
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Size and Speed Attacks that took hours to create can be crafted in just a few minutes. TechTarget
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Lowered skills barrier Tools allow novice attackers to run sophisticated campaigns. Seventh Sense Research Group(r)
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Realism and personalization AI-generated content appears more genuine, which increases chances of success. threatsys.co.in
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Bypassing detection bypassing detection Polymorphic and AI-obfuscated codes elude the traditional security defenses. reinhardtsecurity.com
Conclusion — The Double-Edged Sword of Generative AI
Generative AI is undoubtedly changing the cyber-security landscape. Although these technologies provide huge advantages in terms of efficiency and automation however, they also enable attackers by providing tools that are more efficient, less expensive, and more efficient. As AI-driven attacks increase in sophistication, security professionals have to adjust their strategiesincluding artificial intelligence-aided detection and analysis, in real time and a robust education for usersto counter this rapidly growing security frontier.
Security against AI-enhanced attacks is no anymore a choice, it’s crucial.
