Chatbots are an extremely popular type of software application used across websites and apps to simulate conversations with users and provide information. Recently, GenAI chatbots (ChatGPT, Bard) also rose in popularity, with millions of users interacting with them daily. This widespread use and chatbots’ proximity to sensitive information and organizational systems make them a cyber security risk. How can organizations ensure they benefit from chatbot productivity while protecting themselves and their users? Get the answers below.

What are AI Chatbots?

A chatbot is a software application designed to simulate a conversation with human users. By using pre-programmed rules, and sometimes AI, chatbots can interpret and respond to user messages. Chatbots are used for a wide variety of use cases, from customer service and marketing to collecting data from users to acting as personal assistants.

In their basic form, chatbots often rely on a set of predefined inputs and responses. For example, a chatbot on a retail website might recognize phrases like “track my order” or “return policy” and provide corresponding information. More advanced chatbots use AI, ML, and NLP to understand and respond to a wide range of user inputs with more flexibility and conversational context. They can also learn from interactions to improve their responses over time.

While chatbots can provide information and simulate conversations, they don’t possess human-like understanding or consciousness. Their responses are generated based on algorithms and data, not personal experience or emotions. As such, they are subject to certain types of security threats and chatbot vulnerabilities that can put users and the organization operating the chatbot at risk. Let’s see which kinds and how to protect against them.

Are Chatbots Secure?

Chatbots interact with personal and confidential information and are interconnected with both organizational systems and the Internet. This makes them an organizational vulnerability point, susceptible to security breaches. Various experiments run on AI chatbots demonstrate how they can be used for attacks like prompt injection attacks, and attackers are discussing their potentially malicious applications in underground forums. Therefore, ensuring their security is important for protecting both users and the organization.

Chatbot security refers to the measures and practices to protect chatbots and users from various security threats and vulnerabilities. These measures are designed to safeguard them from unauthorized access, data breaches, being used for chatbot phishing, and other forms of cyber-attacks that raise chatbot security issues.

Chatbot Security Vulnerabilities

The growing use of AI chatbots within organizational systems supports innovative applications, like automating customer service, enhancing user engagement and streamlining information retrieval. However, insecure and unmonitored use could jeopardize an organization’s operations and their data security.

Sensitive business data that is leaked could be used by the enterprise’s competitors or by attackers for activities like ransomware. This could significantly impact an organization’s business plans, the way their customers perceive them and the trust given to them by legal authorities.

For example, if an upcoming marketing announcement is leaked and competitors decide to run an adversarial campaign, the business could lose significant market share. If attackers aim to reveal customer data publicly, the business might be subject to a heavy ransom. If the data is leaked, the business might be fined by authorities and scrutinized for other mismanagement failures. Therefore, it’s important to employ the right security measures in place, to protect from these risks.

Chatbot Security Risks for Enterprises

1. Data Confidentiality and Integrity

Data Breaches/Data Theft/Data Leak

When sensitive information is inputted into the model and then leaked or exfiltrated, through breaches to the database or through the models’ responses.

Information Gathering

When attackers gather sensitive information by prompting the chatbot about systems, network components, coding, security practices, user preferences and more.

Dissemination of Misinformation

When ChatGPT spreads false misinformation, fabricated data or inaccurate facts, due to hallucinations or when false information is inputted into ChatGPT purposely.

Fabricated and Inaccurate Answers

When incorrect and misleading answers are presented as factual responses to prompts.

Automated Propaganda

When misinformation is used to manipulate public opinion through propaganda.

2. Malicious Attacks

Malicious Phishing Emails

When attackers prompt ChatGPT to write phishing emails that sound like legitimate and trustworthy personas in a wide variety of languages.

Social Engineering Attacks

When attackers prompt ChatGPT to create convincing messages that are used to trick victims.


When attackers prompt ChatGPT to impersonate legitimate users for fraud, social engineering and other malicious purposes.

Bypassing Content Moderation Systems

When attackers prompt ChatGPT to create messages that bypass content moderations systems and gain unauthorized access to systems.

Malware Development and Ransomware

When attackers prompt ChatGPT to write malware and ransomware scripts or help debug such scripts.

Malicious Code Generation

When attackers prompt ChatGPT to help exploit vulnerabilities through code.

3. Business and Operational Disruption

Jailbreak Attacks (Attacks on ChatGPT)

When attackers exploit OpenAI vulnerabilities to access sensitive data or create fabricated content. 

ChatGPT Privacy Bugs (Attack on ChatGPT)

When ChatGPT vulnerabilities compromise user privacy by exposing sensitive information.

Intellectual Property (IP) and Copyright Risks

When ChatGPT creates content that too closely resembles copyright assets, potentially infringing IP rights.

Intellectual Property Theft

When ChatGPT provides responses to other users that infringe your IP.

OpenAI Company Policy Changes

If OpenAI changes user privacy guidelines, data usage policies, or ethical frameworks, impacting enterprises’ ability to assure com continuous for users, operations and compliance alignment.

4. Ethical AI, Bias and Toxicity

Model and Output Bias

When ChatGPT responses are biased, due to biases in training data, inaccurate training or lack of guardrails.

Bias Mitigation

When biases are unaddressed, resulting in discriminatory practices or outputs.

Consumer Protection Risks

When enterprises inadvertently share sensitive customer data or provide unethical outputs to customers.

ChatGPT Security

One of the most popular AI chatbots in use is ChatGPT, an online GenAI application developed by OpenAI. ChatGPT is designed to generate human-like text based on the input it receives, enabling a wide range of uses across conversation, content creation, and information synthesis use cases.

Security in the context of ChatGPT involves multiple layers to overcome chatbot security risk:

  • Safeguarding user data against unauthorized access.
  • Protecting the model against adversarial attacks designed to manipulate or extract sensitive information.
  • Ensuring the security of the infrastructure hosting the AI model, including defenses against cyber threats like hacking and DDoS attacks.
  • Compliance with legal frameworks like GDPR to ensure respect for user consent and data rights, aligning the AI system with ethical guidelines.
  • Monitoring and filtering inputs to prevent the AI model being exposed to or learning from harmful, illegal, or unethical content.
  • Output control and moderation to prevent the AI model from generating harmful or biased content.
  • Addressing potential biases in model training.
  • Educating users about the AI’s safe and appropriate use, including its limitations and interaction best practices.
  • In addition, ChatGPT DLP solutions can protect sensitive data from exposure without disrupting the user experience. This is done by preventing organizational data from being pasted into ChatGPT or limiting the types of data employees can insert.

Bard Security

Bard is another popular GenAI chatbot, developed by Google. Improving Bard AI chatbot security is identical to ChatGPT security. This includes strategies for implementing strong security measures like encryption, access controls, and firewalls to safeguard data, monitoring AI chatbots for unusual activities using ML algorithms, educating users about the inherent risks associated with AI chatbots, developing and adhering to ethical guidelines for the creation and usage of AI chatbots, and more.

Chatbot Security Checklist for Enterprises

Securing AI chatbots can help reduce the risks of the threats and vulnerabilities that plague the use of chatbots. Best practices to implement include:

Data Encryption

Ensure that data transmitted to and from the chatbot is encrypted. This includes not only the messages but also any user data stored by the chatbot. Utilize protocols like HTTPS and SSL/TLS for data transmission.

Access Control and Authentication

Implement strong authentication methods to prevent unauthorized access to the chatbot’s administrative functions. This could involve multi-factor authentication or the use of secure tokens.

Regular Security Audits and Penetration Testing

Regularly conduct security audits and penetration tests to identify and fix vulnerabilities.

Data Minimization and Privacy

Follow the principle of data minimization. Only collect data that is absolutely necessary for the chatbot’s functionality. This reduces the risk in case of a data breach.

Compliance with Data Protection Regulations

Ensure compliance with relevant data protection laws like GDPR, HIPAA, etc. This includes obtaining user consent for data collection and providing options for users to access or delete their data.

User Input Validation

Sanitize user inputs to prevent injection attacks. This means checking the data entered by users and ensuring it doesn’t contain malicious code or scripts.

Securing the Backend Infrastructure

Secure the servers and databases where the chatbot operates. This includes regular updates, patch management, and using firewalls and intrusion detection systems.

Monitoring and Incident Response

Continuously monitor the chatbot for suspicious activities. Have an incident response plan in place in case of a security breach.

AI-Specific Threats

Address AI-specific threats such as model poisoning or adversarial attacks, where malicious inputs are designed to confuse the AI model.

User Awareness and Training

Educate users about secure interactions with the chatbot. This can involve guidelines on not sharing sensitive information unless absolutely necessary.

Use a Secure Browser Extension

Use a secure browser extension to protect sensitive organizational data from exposure on websites with chatbots. Map and define the data that needs protection, such as source code, business plans, and intellectual property. An extension offers various control options, like pop-up warnings or complete blocking, which can be activated when using the chatbot  or when attempting to paste or type into its interface. This enables utilizing the chatbots’ productivity potential while safeguarding against unintentional sensitive data exposure.

Next Steps for Security and IT Teams: Your 5 Step Plan

As the use of owned chatbots and GenAI chatbots surges, organizations need to address chatbot security in their overall security and IT plans. To do so, follow these steps:

  1. Assess the risk – Which types of sensitive data are chatbots interacting with? For owned chatbots – analyze how attackers might target your chatbot.
  2. Minimize data exposure – Map the types of data chatbots can collect. Ensure it is only essential data. For owned chatbots, verify secure communication channels, data storage, and processing mechanisms.
  3. Implement security controls – authentication and authorization, encryption input validation, and ChatGPT DLP.
  4. Testing and Monitoring – Monitor which data users attempted to expose and how your solutions behaved in these cases, blocking or alerting about the risk. For owned chatbots, conduct penetration testing to identify and address vulnerabilities.
  5. Training and awareness – Regularly train employees and your users on chatbot on security best practices and the need to limit the data exposed to the chatbot.

To see LayerX’s ChatGPT DLP in action, click here.