Is Generative AI a threat to Cybersecurity?
The evolution of technology in recent times has become more interesting than it has ever been and over the last few years, Generative AI, fully known as Generative Artificial Intelligence, has been an excellent innovative addition. Artificial intelligence has now moved from being what we look forward to having in the future to being present, available, and improving.
Since the launch of ChatGPT in November 2022, many more generative tools have surfaced. Examples include GPT 4, AlphaCode, GitHub Copilot, and Bard amongst others.
Across several industries and sectors, generative artificial Intelligence (AI) is changing the world, opening several possibilities and opportunities to work smartly. As a matter of fact, it is gradually becoming a major part of our lives as many more people now use it to generate content, such as text, images, music, sounds, and even videos. Professionals particularly those in the Customer operations, marketing and sales, software engineering, and R&D fields employ generative AI to generate content ideas amongst several other tasks. Users describe what they want, and generative AI gives output according to users’ input. It does this by leveraging machine learning models trained on massive datasets to learn patterns, structures, and relationships in a dataset of human-created content to generate new and unique content similar to existing ones.
Mckinsey, in a report titled The economic potential of Generative AI: The next productivity frontier, states that the era of generative AI is just beginning. It further emphasizes how Generative AI is positioned to unleash the next wave of productivity and could add trillions of dollars in value to the global economy.
We should be excited about this technological advancement. Should we be excited about this or is there anything to be concerned about? Are we safe? Does generative AI expose us to any more cybersecurity threats?
Despite the potential that generative AI promises, there might be something we should be cautious of.
It started with the question “What happens to the data we put into ChatGPT that generates the kind of output we want?”
Terence Jackson, a chief security advisor for Microsoft, in an article for Forbes, reported that the privacy policy of platforms like ChatGPT indicates the collection of crucial user data such as IP address, browser information, and browsing activities, which may be shared with third parties.
As great as Generative AI tools are, they are not immune to generative AI cybersecurity risks and cyber threats. This has led to several conversations and brows have been raised as to how generative AI can be a threat to cybersecurity.
How is Generative AI then a threat to Cybersecurity?
In this article, we will highlight some ways in which generative AI could be perceived as a threat to cybersecurity
1. Phishing and Social Engineering
Cybercriminals can use text-based generative AI such as ChatGPT to create highly convincing and personalized phishing emails, messages, or websites. They can use the tool to craft messages that imitate the exact communication style of a legitimate source. Such emails increase the likelihood of users falling victim as they are likely to divulge sensitive information about themselves to criminals. Attackers can create highly targeted content to display specific information tailored specifically to the victim’s interests, job role, or personal history. Dane Sherrets, senior solutions architect at HackerOne says that “AI-enhanced campaigns could create highly personalized emails to enable spear phishing at scale”.
2. Impersonation
Generative AI tools can be used to produce text, graphics, and even audio that closely resembles the speech of real people. Cyberattackers might utilize this technology to impersonate well-known and high-profile people. For example, a C–Level executive can be impersonated by a cyber attacker to coerce staff members into compromising security-related acts such as transferring money or revealing private information.
3. Automated attacks
Attacks like brute force, password guessing, and data theft might be automated and scaled up using generative AI. This might greatly increase the impact of cyberattacks, overburdening systems and resulting in extensive harm.
4. Unauthorized access by bypassing security measures
AI models trained to bypass security measures like CAPTCHAs will make it easier for automated bots to gain unauthorized access to systems, websites, or applications. This, then makes the system vulnerable to cyber attacks, data theft, and ransomware attacks.
5. Organised malware attack
Generative AI models can be used by cybercriminals to generate and insert malicious content or code on a system that will help them bypass traditional security tools and even be used in various applications like image recognition, natural language processing, or autonomous systems, thereby exposing their victim’s system to security vulnerabilities.
6. Deepfake Attacks
Video-based generative AI such as Runway’s Gen-1 can be used to create convincing deepfake videos or audio to trick people. For example, an attacker could use a video-generating model to create fake footage of a CEO instructing employees to transfer money or disclose sensitive information. This would definitely lead to a huge financial loss if an employee falls into the attacker’s trap.
In spite of all this, Analytics Insights says that generative AI can be used to combat cyber threats by enhancing threat detection capabilities, predicting possible vulnerabilities, and analyzing the characteristics of an attack to generate appropriate responses and help strengthen security strategies,
As the use of generative AI grows, though, so does the concern about cyber security, because the technology has the ability to drive more targeted cyber attacks. Therefore, individuals are to be cautious as well as companies. Companies must implement policies and, use data governance and security tools to avoid significant cyber risks associated with generative AI.
Additionally, it is advisable to read closely the security policies of any generative AI tool before using it. This helps you to know what happens to the data you put into the tool.
When using any of these tools, be careful. Do not put sensitive data into them during use.
Train your employees on the appropriate and ethical use of generative AI to avoid the misuse of the tool which could be costly in the end.
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References
Cybersecurity Risks of Generative AI
The economic potential of generative AI: The next productivity frontier
Six generative AI cyber security threats and how to mitigate them
Revolutionizing Cybersecurity with Generative AI