Summary: ChatGPT security risks include data leaks, AI-powered phishing, and compliance issues. Learn how enterprises can mitigate threats and use AI safely.
ChatGPT is transforming enterprise workflows, but its rapid adoption raises serious security concerns. While artificial intelligence (AI)-powered chatbots streamline tasks and boost efficiency, they also introduce new risks—such as handling sensitive data, generating misleading content, and unknowingly enabling cyber threats. With 74% of breaches involving social engineering, attackers increasingly exploit AI-generated interactions to deceive users.
As artificial intelligence tools like ChatGPT become more advanced, enterprises must be proactive in securing their use of AI. This article will answer the question: "Is ChatGPT safe?", explore real-world incidents, and outline best practices to keep you away from risks.
The advancing role of AI in business security
As businesses integrate AI chatbots into customer support, internal operations, and even cybersecurity processes, the technology becomes both an asset and a target. AI-based technologies can strengthen security by detecting threats, automating compliance, and improving fraud detection. But, they can also introduce risks if misconfigured or maliciously exploited.
For example, AI-driven security tools can analyze vast amounts of data to detect anomalies, helping prevent breaches before they occur. However, bad actors also use AI to automate cyber-attacks, generate convincing phishing emails, and bypass traditional security measures. The challenge for enterprises is to ensure that AI strengthens security rather than becomes an entry point for attackers.
By understanding both the advantages and vulnerabilities of ChatGPT adoption, organizations can implement the right strategies to harness its power safely.
Key ChatGPT security risks
As AI adoption accelerates in the enterprise space, so do the security risks associated with tools like ChatGPT. Understanding these risks is crucial for businesses to implement effective safeguards.
1. Exposure of sensitive data
One of the greatest risks of using AI chatbots is the accidental exposure of sensitive data. Employees may input confidential information, customer records, or proprietary strategies into the chatbot without realizing that OpenAI or third-party providers might store or analyze this data. This can lead to compliance violations and unintended data leaks.
2. Social engineering attacks
Threat actors can use ChatGPT to craft highly convincing phishing emails or impersonate legitimate users in real-time conversations. Cybercriminals may use AI-generated content to trick company employees into revealing login credentials, financial details, or other sensitive data.
3. Data breaches and unauthorized access
Since ChatGPT interacts with users and processes large amounts of information. If APIs and integrations aren’t properly secured, organizations can be exposed to data breaches. If an attacker gains access to stored chatbot interactions, they could retrieve valuable internal data.
4. Data poisoning and AI manipulation
Attackers can attempt data poisoning—feeding malicious or misleading information into AI models to alter their behavior. If enterprises rely on AI-generated insights, manipulated data could lead to false business decisions or even reputational damage.
5. Malicious code generation
Cybercriminals can exploit ChatGPT’s ability to generate code by using it to create malware, ransomware, or exploits. While OpenAI has implemented safeguards, threat actors may still find ways to bypass these restrictions. In fact, purpose-built malicious AI tools have already emerged, designed specifically for generating harmful code without ethical limitations.
6. Regulatory and compliance risks
Industries such as healthcare, finance, and legal services are subject to strict data privacy laws like GDPR, HIPAA, and CCPA. Enterprises using AI tools must ensure that chatbot interactions do not violate these regulations, particularly when handling personal or financial data.
7. Risks of Large Language Models (LLMs)
ChatGPT runs on a Large Language Model (LLM), an advanced AI system trained on vast amounts of text data to generate human-like responses. It can unintentionally produce misleading information or fabricate sources due to their open-ended nature. They are also vulnerable to prompt injections, where malicious inputs are used to manipulate the model’s responses.
By recognizing these security threats, organizations can take a proactive approach to lowering AI-related risks. Whether securing sensitive data, preventing unauthorized access, or addressing compliance challenges, businesses must remain aware of security threats.
ChatGPT’s security features: Safeguards and limitations
While ChatGPT security risks are a growing concern for enterprises, OpenAI has implemented several safeguards to mitigate potential threats. These include content filtering, prompt moderation, and ethical use policies designed to prevent malicious applications such as generating harmful content, phishing emails, or malware. Additionally, OpenAI continuously refines its model to reduce bias, misinformation, and unintended data leakage.
However, these safeguards have limitations. Threat actors test ways to bypass restrictions, using indirect prompts or fragmented queries to elicit restricted information. ChatGPT also lacks full context awareness. It cannot verify the accuracy of its outputs or detect when users manipulate its responses. While OpenAI does not retain chat history for training, enterprises must still assume that any data entered could be processed externally. This makes strict data governance policies a must.
Despite these measures, organizations can’t solely rely on ChatGPT’s security features to safeguard sensitive information. Implementing enterprise-grade security controls, such as access restrictions, API security, and AI monitoring solutions, remains essential in preventing unauthorized data exposure or AI-driven cyber threats.
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Real-world examples of ChatGPT-related threats
AI-powered tools like ChatGPT are already shaping business operations, but their rapid adoption has led to security incidents that highlight potential risks. From accidental data leaks to AI-enhanced cybercrime, enterprises have faced real-world consequences when using these tools without proper safeguards.
The following cases highlight how weak ChatGPT security can expose sensitive information or even allow malicious actors to exploit it.
Samsung’s data leak
In 2023, Samsung Electronics faced a significant security incident when employees inadvertently leaked confidential company information through ChatGPT. Engineers from Samsung's semiconductor division used ChatGPT to help debug and optimize source code. Unknowingly, they entered sensitive data, including proprietary source code and internal meeting notes, into the AI tool.
Since ChatGPT retains user inputs to refine its responses, this action risked exposing Samsung's trade secrets to external parties. This event shows why companies need stringent data-handling policies and employee training on how to use AI tools in corporate environments.
AI-powered phishing campaigns
Cybersecurity researchers have observed that AI-generated phishing emails are not only more grammatically accurate but also more convincing, making them harder to detect. Moreover, AI is now used to craft deepfake voice scams. For instance, 2025 predictions warn of AI-driven phishing kits bypassing multi-factor authentication (MFA) and mimicking trusted voices via voice cloning.
A study highlighted by Harvard Business Review revealed that 60 % of participants were deceived by AI-crafted phishing messages, a success rate comparable to those created by people. This trend highlights the escalating challenge enterprises face in protecting employees from such deceptive tactics.
Fake customer support bots
Scammers have begun deploying AI-driven chatbots that impersonate real customer service representatives. These fraudulent bots engage users in real-time conversations, persuading them to hand over sensitive information such as passwords or payment details.
For instance, reports indicate that these AI chatbots can convincingly mimic the communication styles of reputable companies, leading unsuspecting customers to trust and interact with them.
This exploitation of AI technology shows why businesses must authenticate their customer communication channels and educate consumers recognize legitimate support interactions.
Best practices for safely using ChatGPT in enterprises
As real-world incidents show, organizations must recognize that while AI improves efficiency, it also requires thoughtful management to prevent misuse. To minimize risks, enterprises should adopt proactive security measures that ensure AI-powered tools are used safely.
The following best practices can help businesses leverage AI’s benefits while protecting sensitive information from unauthorized access, cyber threats, and compliance violations.
1. Implement strict data policies
Based on the recent mimecast cybersecurity report, human error remains the main cause of data breaches and cyber incidents. Employees may unknowingly expose sensitive information or interact with AI-generated responses containing malicious code, increasing the risk of security compromises.
To mitigate this, organizations should integrate automated Data Loss Prevention (DLP) tools to detect and block unauthorized data inputs into AI systems. Regular training, policy reinforcement, and security audits will help ensure compliance and minimize accidental data leaks.
2. Enable access controls and monitoring
Limit ChatGPT usage to authorized personnel by integrating it with Role-Based Access Controls (RBAC) and enterprise authentication systems. Implement logging mechanisms to track AI interactions, helping detect anomalies or potential data leaks. Regularly review access logs to ensure compliance with security policies and swiftly address unauthorized activities.
In addition, consider enablin gmulti-factor authentication (MFA) for high-privilege users to further restrict access to AI tools. By combining access controls with real-time monitoring, enterprises can mitigate insider threats and ensure AI usage aligns with security best practices.
3. Use AI detection tools
Deploy AI-driven security solutions to detect and mitigate threats like AI-generated phishing emails, cyber-attacks, or malicious chatbot activities. Advanced threat detection tools can flag suspicious patterns, such as unusual chatbot queries or high-risk prompts, to prevent potential cyber risks before they escalate.
These tools can be integrated with Security Information and Event Management (SIEM) platforms to provide real-time alerts on suspicious AI interactions. Additionally, setting up behavioral analytics can help identify unauthorized attempts to manipulate ChatGPT for malicious purposes, adding an extra layer of protection against AI-enabled threats.
4. Regularly update AI security settings
Ensure that all chatbot integrations comply with industry security standards, including ISO 27001, SOC 2, or GDPR, where applicable. Apply security patches and updates to address vulnerabilities and protect against threats. Conduct routine security assessments to identify weaknesses in chatbot configurations and AI-driven workflows.
Organizations should also perform penetration testing on AI integrations to uncover potential security gaps before they can be exploited. Establishing a structured incident response plan specific to AI security will further enhance the organization’s ability to mitigate risks and react swiftly to potential breaches.
5. Restrict external API access
If integrating ChatGPT into enterprise applications, secure API endpoints using authentication tokens, IP allowlisting, and encryption to prevent unauthorized access and data exfiltration. Implement rate limiting and anomaly detection to identify potential abuse or credential stuffing attacks targeting AI-powered APIs.
Additionally, establish a least privilege access model, ensuring that APIs only provide the minimum necessary data to function. Regularly rotate API keys and monitor unauthorized access attempts. This can further strengthen defenses against API-related threats.
6. Train employees on social engineering risks
People are the first line of defense. Conduct cybersecurity awareness programs to help employees recognize AI-generated phishing emails, deepfake scams, and impersonation tactics. Use simulated phishing exercises and real-world case studies to build awareness.
Employees should also be trained to identify signs of malicious code embedded in chatbot responses or AI-generated links. Encourage a Zero Trust mindset, where verification is prioritized over assumption in all AI-assisted communications.
By adopting these best practices, enterprises can strike a balance between AI-driven efficiency and robust security. Proactive governance, continuous monitoring, and employee awareness are key to using AI safely without compromising sensitive information.
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How NordLayer supports secure enterprise environments
While NordLayer doesn’t directly address AI-specific risks, but it plays a crucial role in protecting the broader network environment where AI tools like ChatGPT are used.
Solutions like Secure Web Gateway, Cloud Firewall, and Zero Trust Network Access (ZTNA) help safeguard against phishing, malicious code delivery, and unauthorized access—common threats that can be amplified by AI-driven tools.
By enforcing strong access policies and maintaining network visibility, NordLayer helps organizations stay secure and compliant while exploring AI technologies.
Why choose NordLayer?
Secure network infrastructure: Keeps your data safe when accessing or integrating AI tools
Zero Trust security: Ensures only authorized users access critical resources
Threat intelligence: Detects and mitigates phishing, malware, and AI-driven social engineering attacks
Compliance-ready solutions: Helps organizations meet NIS2, CIS Controls, HIPAA, and other key industry frameworks
Conclusion
AI-powered tools like ChatGPT offer numerous advantages for enterprises but also introduce significant security risks. From data leaks and cyber-attacks to regulatory concerns, organizations must take proactive measures to safeguard their operations.
By following best practices and using network security solutions like NordLayer, businesses can securely integrate AI chatbots while minimizing potential threats.

Agnė Srėbaliūtė
Senior Creative Copywriter
Agne is a writer with over 15 years of experience in PR, SEO, and creative writing. With a love for playing with words and meanings, she crafts content that’s clear and distinctive. Agne balances her passion for language and tech with hiking adventures in nature—a space that recharges her.