The Rise of Generative AI and the Question of Accountability for Cyber Threats

Sophisticated Malware Attacks and Generative AI

The sudden increase in sophisticated malware attacks, advanced persistent threats (APTs), and organizational data breaches have raised concerns and questions of accountability. Investigations have revealed that these attacks are crafted by cybercriminals who have been empowered with generative AI technologies. The question that arises is who should be held accountable for such attacks?

Accountability for Generative AI Cyberattacks

Should the cybercriminals themselves be held accountable, or should the generative AI bots be blamed? Should the organizations that created these bots be responsible, or should the government that lacks regulation and accountability take responsibility?

Generative AI technology is a form of artificial intelligence that can generate text, images, sounds, and other content based on natural language instructions or data inputs. AI-powered chatbots such as ChatGPT, Google Bard, Perplexity, and others are accessible to anyone who wants to chat, generate human-like text, create scripts, and even write complex code. However, a common problem with these chatbots is that they can produce inappropriate or harmful content based on user input, which may violate ethical standards, damage reputation, or even constitute criminal offenses.

Chatbot Security Measures and their Effectiveness

Therefore, these chatbots have onboard security mechanisms and content filters intended to ensure their output is within ethical boundaries and does not produce harmful or malicious content. But how effective are these defensive content moderation measures, and how much do they align with cyber defense?

Hackers are reported to be using AI-powered chatbots to create and deploy malware using the latest chatbots. These chatbots can be “tricked” into writing phishing emails and spam messages, and they even help malicious actors write pieces of code that evade security mechanisms and sabotage computer networks.

Bypassing Chatbot Security Filters

For research purposes, and with the intention of improving the technology, some techniques that proved effective in bypassing chatbot security filters were explored. For instance:

• Crafting a fictional environment to prompt the chatbot into behaving in a specific way.
• Jailbreaking the chatbot and forcing it to stay in character empowers it to create almost anything imaginable.
• Reverse psychology can also trick chatbots into revealing information that otherwise would not display due to community guidelines.
• Using emojis can trick chatbots into creating content that they would not generate otherwise.

These techniques for bypassing ethical and community guidelines are just the tip of the iceberg, as there are countless other ways these chatbots could be used to mount devastating cyberattacks.

Searching for Vulnerabilities

As AI-based systems trained on conceivable knowledge of the modern world, contemporary chatbots know existing vulnerabilities and ways to exploit them. With a little effort, an attacker can use these chatbots to write code that circumvents antiviruses, intrusion detection systems (IDS), and next-generation firewalls (NGFW).

These chatbots can be misused and “tricked” into creating obfuscated code, generating payloads, writing exploits, launching zero-day attacks, and even developing advanced persistent threats (APTs). Therefore, these chatbots need to be regulated by a clear and fair mechanism that should be transparent, accountable, and resilient for both producers of such chatbots and consumers.

Discussion and Advice

The rise in sophisticated cyber attacks indicates a need to re-think the accountability framework for the use of generative AI technologies. Governments, organizations, and AI developers must take responsibility for the potential harm that these technologies can cause in the wrong hands.

AI accountability should be considered a critical component of cybersecurity, artificial intelligence, and future technological advancements. Accountability measures for generative AI technology should include cybersecurity considerations such as security reviews, security testing, and auditing processes to monitor and assess their performance.

The advancement of technologies such as generative AI and AI chatbots is inevitable. However, developers, governments, and users have the responsibility to ensure that such technologies are used for ethical purposes and not to harm individuals or the society at large.

Therefore, it is important to raise awareness of the potential challenges and risks associated with generative AI and AI chatbots and to take proactive measures to mitigate such risks. Governments, organizations, and developers should work to establish clear regulations and guidelines for the use of such technologies, along with regular security checks and audits to ensure that they are being used ethically and in compliance with the set regulations.

By doing so, we can ensure that generative AI and AI chatbots are used to serve the greater good and contribute positively to society without posing a threat to individual and organizational cybersecurity.