Generative AI platforms and chatbots are ready to become progressive technology tools globally, but will the development expand without proper thought given to cybersecurity?
Generative AI tool ChatGPT has taken the business world by storm, assisting in generating new digital content. There is no doubt that this AI system or model is impacting companies in every industry as it shows the potential to transform the future of productive tasks of businesses. Yet, cybersecurity risks of generative AI and ChatGPT are also rising concerns among users and companies, which leaders must not ignore.
While the technology has many potential benefits and uses, there are several concerns, such as malicious exploits, coding replacement, and other effective cyberattacks. However, the question is, what are the possible cybersecurity risks with ChatGPT and generative AI? Are they threats to companies?
Given are some potential cybersecurity risks associated with ChatGPT and generative AI.
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Generative AI proves efficient for many business processes. ChatGPT and other chatbots, as parts of generative AI, set an example of outstanding natural language processes. However, machines also have cyber-incidents or cyber-attacks, which, if left untreated, may result in very harmful business and financial costs.
One of the leading cybersecurity issues with generative AI is a programming error. Generative AI platforms are adept at multiple tasks, but building such potential requires adequate programming, coding, infrastructure, and more. Cyber attackers could use the programming codes for hacking or find other security vulnerabilities. The attackers can convincingly impersonate codes and spread undesired content on platforms like ChatGPT and other chatbots, ruining the brand image. Hackers and cybercriminals are already crossing the tool’s safeguarding gates to add malicious content. In such cases, code bugs are a pathway for hackers to enter the programming slot of generative AI and exploit functionalities adversely. In addition, frontend codes are also susceptible to programming errors by cyber attackers.
Prompt Injection Cyber Attack
Generative AI platforms have their vulnerabilities. The new generative AI platforms, specifically ChatGPT, show a recent attack, ‘prompt injection,’ that finds previously installed instructions fed and makes changes to the new ones in their place. Prompt injection attacks such as ChatGPT’s DAN (Do Anything Now) and Sydney (Bing Chat) is a cybersecurity risk, harming the technology’s content policy and evolving as malicious activities for exploiting the content generation process.
With this new crop of cyber exploits, hackers are influential today. Hackers use various methods to implement prompt engineering attacks in chatbots and are rapidly widening such attack vectors. Malicious threat actors may execute content promptness indirectly without additional input from the user. Such attacks are also counted as advanced social engineering attacks and are used to instantly gain users’ personal information. Generative AI technology has come to users very quickly. The future of it could be even more complicated for companies trying to understand the technology toward security breaches.
Chatbots collect personal information through a user’s IP address, browser type, settings, browsing activities, and website interactions. Chatbots are the easiest and quickest source of gathering data of users, which becomes an easy entry point for threat actors to enter the sources. Generative AI cyber-attacks are easy by gaining the data of users. Generative AI gathers data faster, which is becoming a problematic factor for companies enduring the technology.
Due to these severe factors, companies are putting up stringent data privacy policies and AI systems that can opt out of the collection of personal information of users. Companies also utilize chatbots and generative AI tools to mitigate data privacy risks that should review the privacy policies. The policies comply with appropriate data protection laws to provide opt-out options.
AI-Generated Voice Technology
Voice technology is becoming a prominent part of generative AI tools and platforms like ChatGPTs. Voice replica through AI models is one of the effective methods of threats that may expand sooner. Threat actors use software programs that generate audio to mimic users’ voices or give them a way to access users’ accounts. Such a case highlights how easy it is for threat actors with malicious intent to use AI-generated voice technology to bypass security measures on generative AI platforms. And such cases are anticipated to expand only in the future.
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Generative AI and its associated cybersecurity risks represent a recent expansion of the broad attack surface. The recent attack vectors that hackers can exploit are to create convincing replicas of almost anything, that includes video and voice recordings and images. The image and voice replicas can be used for threat activities such as identity theft and fake identities. These replicas create hate-filled content that can go against companies promoting ChatGPT as an efficient generative AI platform assisting in multiple tasks.
What Should Businesses Do to Secure Generative AI Platforms (If Adopting)
The capabilities of generative AI models are impressive, showing promising signs of continuing to advance and improve. It certainly has the potential to change how businesses are digitally functioning. However, they also need to pay attention to how the technology attracts cyber threats and how they develop and execute attacks.
The headlong development of chatbots and generative AI will show businesses the threat side of the technology and evolving risks with increased uses. While specific facts and circumstances will determine particular cybersecurity risks of this AI model, companies should consider these top-line suggestions to protect their generative AI platforms, such as chatbots or ChatGPT:
- Consider adopting policies that govern how to deploy the technology aligned with threat-defensive measures
- Remember the fact – chatbots can often create errors
- Carefully monitor the addition of business, client, or customer data
- Review privacy policies after intervals
- Bolster cybersecurity and social engineering defensive measures and strategies
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