ChatGPT and other generative AI: Cybersecurity risks?

Generative AI, which utilizes advanced machine learning models, has become increasingly popular for its ability to generate highly realistic and original content like videos, images, and text. In fact, a recent survey of over 500 IT leaders discovered that 67% plan to prioritize the use of generative AI for their businesses within the next 18 months. However, there are some concerns regarding ethics, accuracy, security, and other related issues that need to be addressed.

While generative AI has been acclaimed as a game-changer by many industry experts, it also poses significant security risks. According to a Salesforce report, more than 71% of IT leaders believe that new data security threats will arise, and some are worried that employees lack the knowledge or expertise to use these technologies safely. Wall Street firms such as Bank of America, Goldman Sachs, Citigroup Inc., Deutsche Bank AG, and Wells Fargo & Co. have all banned the use of ChatGPT, but only a small number of HR leaders, accounting for just 3% of those surveyed by Gartner, have prohibited ChatGPT for any business-related activities.

Why are organisations drafting policies around the use of generative AI? Experts have found out some risks that may arise from the improper implementation or unregulated use of generative AI in the workplace, such as:

1. Unauthorized Data Access and Exfiltration:

When employees use generative AI tools, they often upload or feed these models with data. This data may include sensitive company information, intellectual property, or customer data. If not properly secured, it becomes susceptible to unauthorized access or exfiltration. 

2. Compliance and Regulatory Concerns:

Many industries are subject to stringent compliance and regulatory frameworks, such as data protection laws (e.g., GDPR, CCPA) and industry-specific regulations (e.g., HIPAA for healthcare). When employees use generative AI tools, they may inadvertently violate these regulations, especially if the data involved includes personally identifiable information (PII) or protected health information (PHI). 

3. Intellectual Property Infringement:

Generative AI tools rely on vast amounts of training data to produce accurate and creative outputs. If employees use copyrighted or patented material without proper authorization, it may lead to intellectual property infringement.

4. Phishing and Social Engineering Attacks:

The use of generative AI tools can inadvertently expose employees to phishing and social engineering attacks. Hackers and malicious actors may exploit the popularity of generative AI platforms to impersonate legitimate tools or lure employees into downloading malware-infected versions..

5.Malware Injection and Backdoor Vulnerabilities:

Generative AI tools developed by third-party vendors may carry hidden malware or backdoor vulnerabilities. If employees unknowingly use compromised generative AI software, it could expose the company’s network to potential security breaches. 

To safeguard sensitive data, comply with regulations, and establish a secure working environment, companies must comprehend potential risks and take necessary security measures.

Hire the right people!

A proactive approach is the most effective to fight against the risks brought about by generative AI. Implementing security policies will not be as effective when the cybersecurity team of a company is lacking. A dedicated security team or individual on detecting anomalies will be more effective than having to pay thousands to the most popular antivirus softwares. 

Datasearch Consulting specializes in hiring cybersecurity professionals who can help organizations adopt new emerging technologies, such as generative AI. They believe companies should embrace these advancements to improve processes and equip themselves to handle potential attacks. Hiring the right cybersecurity team is crucial for a fruitful future with generative AI.