Automated customer service chatbots can benefit businesses, but related security issues are more common than you may think. Cyberattackers take advantage of their unique vulnerabilities. Here are a few of the most significant risks your business may face.
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1. Data Exfiltration
Data exfiltration is one of the most significant chatbot security issues. A cyberattacker can maliciously redirect it with various injections because its configuration files are the foundation for communication. For example, they could set it up to request additional personally identifiable information during customer conversations. In addition to asking about an order number, it would prompt for their name, email address and credit card information.
People would likely be unaware of exploitative activity, considering the dialogue would look completely normal. Additionally, your business may not initially recognize unusual actions. The attacker can collect information within the artificial intelligence’s (AIs) application memory. You won’t detect unusual behavior until they take out massive amounts of sensitive data simultaneously.
Typically, you can monitor logs to have adequate security. However, you may get no indication something is wrong until after a successful attack. Prevent this by ensuring the integrity of the AI’s configuration files. An attacker can typically only take advantage of customer interactions when they can alter them, which is why it’s an essential aspect of cybersecurity.
2. Model Alteration
Most people want to feel like they’re speaking with a real person when they talk with an AI. According to one survey, around 71% of consumers believe natural communication is essential. Most businesses utilize the latest AI technology to make that happen, but you should be wary of doing so.
Advanced chatbots often utilize complex technology like natural language processing or neural networks. They optimize learning capabilities but can make detecting unusual activity much more challenging. It can be incredibly time-consuming to understand how such an algorithm comes to a conclusion, making it more likely for you not to notice an attacker.
You must have control over which data sets you feed your AI. In addition, you must ensure the integrity of the information it operates on. You can protect your AI from intentional negative bias if you understand how it processes information and comes to conclusions.
3. Data Set Poisoning
In February of 2023, a research team found they could intentionally bias a chatbot to permanently alter its behavior in whatever way they desired. Their method, data set poisoning, maliciously targets the learning process. It presents the AI with tons of examples while scraping for information, immediately changing it.
It’s one of the more significant chatbot risks. A cyberattacker could inject malicious prompts to get the AI to ignore its directives or safety protocols. Essentially, they manipulate it into acting outside of its bounds in a way that could cause your business harm.
You can monitor file changes and analyze data sets to ensure your algorithm’s integrity. Additionally, you could routinely test its output to see if its behavior is still within the bounds you initially set.
4. Source Code Alteration
In 2022, nearly 80% of companies expected to implement some sort of chatbot. Many likely had to rely on public resources to get their automated customer service assistant. Plenty of open-source options are available online, but they pose security risks.
Since anyone can modify an open-source language learning model (LLM), integrating it into your codebase could be less than ideal. It’s a relatively popular method because it’s reliable and more manageable than starting from scratch, but cyberattackers can easily exploit it.
According to researchers, the most popular LLMs pose severe security risks on average. An individual with enough motivation and the right skill set could make minor changes to eventually take advantage. Prevent this by avoiding open-source options. If you use them, thoroughly analyze their integrity and check for potential vulnerabilities.
5. Prompt Injection Attack
A prompt injection attack involves a file invisible to the human eye. While it’s relatively uncommon, it’s still one of the most significant chatbot security issues. Its purpose is to alter behavior discreetly. For example, one person created an attack to change the dialogue restrictions of Bing’s LLM. Although the file was invisible to humans, the AI could analyze it. It overrode the settings and made it function in a way the developers didn’t intend.
Even after the company fixed the initial attack, the individual used the same prompt injection differently to get it working again. It was indirect but significantly altered the algorithm’s behavior and purpose. This type of risk to your business could happen due to a simple document upload or website integration.
Most chatbots only encrypt point-to-point with hypertext transfer protocol secure (HTTPS) to secure data transfers. Instead, you should focus on end-to-end encryption for increased cybersecurity. It protects dialogue between the customer and the AI, making it much more difficult for cyberattackers to gain access.
This method prevents malicious code injection by keeping them from altering the chatbot’s configuration files. In addition, they can’t collect personally identifiable information from customers when everything is encrypted. Only parties you trust can access it with cryptographic keys.
A plugin could also assist you. For instance, Wordfence prevented over 90 billion fraudulent logins — 2,800 attempts per second — aimed at WordPress. A cyberattacker can’t enter malicious prompts if they cannot gain access. You can ensure chatbot security if you have the right software in place.
Enhance Your Chatbot Security
While you can mitigate chatbot security issues with the correct methods, keeping their vulnerabilities in mind is always helpful. Cyberattackers continuously find ways to take advantage of new attack surfaces, so it takes effort to say ahead of them. However, you can prepare for chatbot risks before integrating AI to optimize your business’s cybersecurity
