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.
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.
Chatbots, which interact with personal and confidential information and are interconnected with both organizational systems and the internet, represent a significant vulnerability point for security breaches. 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.
Chatbots are subject to a wide variety of threats and vulnerabilities. The main chatbot security risks include:
Data Breaches and Privacy Issues
AI chatbots often handle sensitive personal data, including names, addresses, and even payment information. Unauthorized access to this data due to insufficient security measures can lead to significant data breaches. This puts users at risk of their data being used for identity theft, fraud, or other malicious uses.
Interception of Data Transmission
The communication channel between the user and the chatbot can also be a vector for attacks. If the data transmission is not adequately encrypted, it could be intercepted by third parties, leading to the potential exposure of sensitive information.
Impersonation and Social Engineering Attacks
Attackers may use sophisticated techniques to impersonate users or the chatbot itself, engaging in social engineering attacks. This might involve tricking the chatbot into revealing sensitive information or manipulating users into divulging confidential data. In other cases, chatbots can be re-purposed by hackers to spread malware or spam.
AI Model Vulnerabilities
The underlying AI models behind AI chatbots can be susceptible to various forms of attacks, such as model inversion attacks, where an attacker reconstructs sensitive training data, or adversarial attacks, where slight changes to input data can cause the model to make incorrect decisions or reveal sensitive information.
Similar to traditional web applications, chatbots can be vulnerable to injection attacks. In these types of attacks, the attacker inputs malicious data that the chatbot mistakenly executes or processes. This can lead to unauthorized access or the retrieval of sensitive data.
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 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.
Securing AI chatbots can help reduce the risks of the threats and vulnerabilities that plague the use of chatbots. Best practices to implement include:
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.
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.
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:
- Assess the risk – Which types of sensitive data are chatbots interacting with? For owned chatbots – analyze how attackers might target your chatbot.
- 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.
- Implement security controls – authentication and authorization, encryption input validation, and ChatGPT DLP.
- 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.
- 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.