What are the security risks of chatbots?

The cyber landscape is dynamic and ever-evolving. At this moment in time, the innovation and uptake of new technologies is experiencing an exponential rise.

As discussed in previous blogs, the new frontiers of technological assimilation move further forward at such a pace that adequate security solutions tend to lag behind. This lag leads to weaknesses — and these weaknesses are quickly noticed by threat actors that are always on the lookout for new targets.

One of the latest features of the current technological evolution is the appearance of chatbots. They’re now an integral feature of customer service, providing the convenience of real-time messaging without the inconvenience of holding the line on a phone call, for instance.

With chatbots becoming ubiquitous, it begs the question — “Are there any risks that are being overlooked?”

Read on to find out everything you need to know about chatbots and keeping them secure.

Firstly, let’s delve into the different forms of chatbots and what they look like.

What are chatbots?

Chatbots are computer programs that are designed to create automated replications of human interaction. The interaction you experience is powered by artificial intelligence (AI) and natural language processing (NLP). The aim is to make the exchange seem as close to human conversation as possible while directly addressing the customer’s needs.

The first chatbots were driven by simple text-based responses picked out from a small trove of predetermined phrases. They were novel but inadequate for complex or nuanced questions. In essence, what the simplest chatbots do is just work out how to choose a response out of a knowledge-base.

As time passed, NLP and more advanced rules led to the development of chatbot responses. This streamlined the interactions and made chatbots resemble something closer to genuine human conversation. The more advanced chatbots are able to learn from interactions and broaden their lexicon.

AI and natural language understanding (NLU) underpin the workings of the most accomplished chatbot formats. There’s a notable difference between a standard chatbot that runs on algorithms, and an AI chatbot that uses deep learning to refine its process over time.

Consequently, an AI chatbot that’s been running for a long time will have built a complex network of detail about the variables of a query. This means they can draw upon context and experience to accurately tackle what’s driving a specific question — just as a human can see the background complexities behind a query.

AI chatbots are now familiar to most — take Amazon’s Alexa as an example of a domestic assistant that helps with wide-ranging questions and tasks.

In a business context, AI chatbots ironically help to deliver a personal touch to services. They are used to channel the flow of traffic from customers in a diagnostic way — such as by directing them to the appropriate branches of a company to resolve a query.

Automating basic tasks also takes the strain away from staff members. This is key to freeing up expensive human time and resources — a major benefit for those that run an organization.

AI chatbots assist with customer self-service by cultivating more frictionless movement through funnels. From a customer’s point of view, this engenders a more self-led experience that can be accessed 24 hours a day. This means issues can be addressed outside of traditional business, mitigating previous constraints experienced by service users.

What are the security risks of using a chatbot?

As we’ve explored in another blog post about ChatGPT, there are clear security issues that threat actors are beginning to exploit.

In short, chatbots are seen as a way “in” by bad actors.

Chatbots act as a vector through which hackers can hitch a ride and hijack secure information. Because chatbots are prevalent in customer service, bad actors have recognised that personal information is exchanged in interactions with customers, making this area a target for malicious intent.

In light of this, it’s imperative that customers are aware of the situation and do not reveal personal sensitive information during a chatbot session.However, this is easier said than done.

Irrespective of whether a threat actor has access to the chatbot at the time of customer interaction or not, there is always a risk of customers carelessly disclosing sensitive information, such as payment details, during a chatbot session.

Not only can hackers spy on exchanges during a session, but they’re also able to operate the chatbot to carry out scans of a network or request information, extending their reach to other customers.

This increases the risks related to chatbots relative to simpler systems where exactly what information they store and have access to is known. Chatbots may be storing sensitive information that customers were either tricked into inputting or offered unprompted, leading to the potential that hackers could gain access to a trove of personal information stored on chatbots if the system becomes compromised.

Encryption is an effective way of mitigating the vulnerabilities inherent in chatbot use. However, few chatbot programs are encrypted and associated staff don’t have the training or knowledge to identify potential issues before it’s too late.

How can you ensure that your chatbot is secure?

Here are a few useful tactics to protect your data. It is worth noting that these tips are mainly focused on securing and authenticating who interacts with the chatbot. With anonymous users, it is not usually possible to provide robust authentication, thus leaving these types of chatbots more vulnerable. However, there are still things that you can do to protect user data in these situations.

• Two-Factor Authentication (2FA) — In the case of chatbot interactions with an authenticated customer, 2FA adds another level of security by requiring a secondary form of information to allow access. It adds another barrier to threat actors. However, this form of security is not possible with anonymous users.
• Employ biometrics — biometrics use the physical features of authorized personnel to enable access. This proves incredibly effective since hackers cannot easily replicate a fingerprint or facial features. However, this may prove challenging to implement as chatbots are broadly accessible to users across the internet.
• Use encryption — encryption essentially secures your data to make exchanges safer and private. Traffic between the end user and the website is typically encrypted via transport layer security (TLS). Thought must also be put into how data at rest is protected.
• Train employees — run an education program to upskill your staff and help them spot tell-tale signs of malicious intent. This helps to mitigate threats before they become a breach event.
• Include warnings at the start of interactions — it is best practice to warn users at the start of every interaction not to disclose sensitive information like payment card details, medical information, or social security numbers. Although this can’t fully prevent users from inputting sensitive information, it will reduce instances of careless sharing of information and hopefully raise suspicion in the customer if the chatbot requests this type of data.
• If possible, detect sensitive information — although this will not be possible in every scenario, if developers know that sensitive information will be or has been shared with a chatbot for any reason, they should ensure that this data is not stored.
• Use an effective cybersecurity provider — doing so will shore up loose ends where bad actors look to exploit and nip threats in the bud before they become emergencies.

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