Category: Chat

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Chatbots are here to stay

Chatbots have been around for a long time and based on the global chatbot market size (and the expected growth), they will stick around for a long time and gain importance. In the past they’ve rarely met customer expectations or provided much positive experience. However, over the last few years, advances in conversational AI have transformed how they can be used. Since chatbots offer a wide range of applications, in certain cases they become responsible for collecting and protecting personal information as well. Consequently, they are a great attraction for hackers and malicious attacks too. The responsibility of ensuring chatbot security has become more pronounced after the introduction of GDPR in Europe. As statistics show that this technology will be a determining factor in our lives, security testing must also become part of our daily tasks, so that these chatbots can be used with confidence.

Security Risks, Threats and Vulnerabilities

The words risk, threat and vulnerability are often confused or used interchangeably when reading about computer security, so let’s first clarify the terminology:

• Vulnerability refers to a weakness in your software (or hardware, or in your processes, or anything related). In other words, it’s a way hackers could find their way into and exploit your systems.
• A threat exploits a vulnerability and can cause loss, damage or destruction of an asset — threats exploit vulnerabilities
• Risk refers to the potential for lost, damaged, or destroyed assets — threats + vulnerability = risk!

The well-known OWASP Top 10 is a list of top security risks for a web application. Most chatbots out there are available over a public web frontend, and as such all the OWASP security risks apply to those chatbots as well. Out of these risks there are two especially important to defend against, as in contrast to the other risks, those two are nearly always a serious threat — XSS (Cross Site Scripting) and SQL Injection.

In addition, for artificial intelligence enabled chatbots, there is an increased risk for Denial of Service attacks, due to the higher amount of computing resources involved.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Vulnerability 1: XSS — Cross Site Scripting

A typical implementation of a chatbot user interface:

• There is a chat window with an input box
• Everything the user enters in the input box is mirrored in the chat window
• Chatbot response is shown in the chat window

The XSS vulnerability is in the second step — when entering text including malicious Javascript code, the XSS attack is fulfilled when the web browser is running the injected code:

<script>alert(document.cookie)</script>

Possible Attack Vector

For exploiting an XSS vulnerability the attacker has to trick the victim to send malicious input text.

1. Attacker tricks the victim to click a hyperlink pointing to the chatbot including some malicious code in the hyperlink
2. The malicious code is injected into the website, reads the victims cookies and sends it to the attacker without the victim even noticing
3. The attacker can use those cookies to get access to the victim’s account on the company website

Defense

This vulnerability is actually easy to defend by validating and sanitizing user input, but still we are seeing this happening over and over again.

Vulnerability 2: SQL Injection

A typical implementation of a task-oriented chatbot backend:

• User tells the chatbot some information item
• The chatbot backend queries a data source for this information item
• Based on the result a natural language response is generated and presented to the user

With SQL Injection, the attacker tricks the chatbot backend to consider malicious content as part of the information item:

my order number is “1234; DELETE FROM ORDERS”

Possible Chatbot Attack Vector

When the attacker has personal access to the chatbot, an SQL injection is exploitable directly by the attacker (see example above), doing all kinds of SQL (or no-SQL) queries.

Defense

Developers typically trust their tokenizers and entity extractors to defend against injection attack. Additionally, simple regular expression checks of user input will in most cases close this vulnerability.

Vulnerability 3: Denial of Service

Artificial intelligence requires high computing power, especially when deep learning as in state-of-the-art natural language understanding (NLU) algorithms is involved. The Denial of Service (DoS) attack is focused on making a resource unavailable for the purpose it was designed, and it is not hard to imagine that chatbots are more vulnerable to Denial of Service (DoS) attacks than the usual backends based on highly optimized database systems. If a chatbot receives a very large number of requests, it may cease to be available to legitimate users. These attacks introduce large response delays, excessive losses, and service interruptions, resulting in direct impact on availability.

Possible Chatbot Attack Vector

A typical DoS attack sends a large number of large requests to the chatbot to intentionally exhaust the available resources. It will happen that the computing resources are not available anymore to legitimate users.

But there is an additional risk to consider: it is quite common for chatbot developers to use cloud based services like IBM Watson or Google Dialogflow. Depending on the chosen plan there are usage limits and/or quotas in effect which can be exhausted pretty quickly — for example, the Google Dialogflow Essential free plan limits access to 180 requests per minute, all other requests will be denied. For a usage-based plan without any limits a DoS attack can easily cost a fortune due to the increased number of requests.

Defense

The established methods for defending against Denial of Service attacks apply for chatbots as well.

Mitigation Strategies

Apart from the defense strategies from above, there are generic rules for mitigating the risks of system breaches.

Software Developer Education

Naturally, the best way to defend against vulnerabilities is to not even let them occur in the first place. Software developers should get special training to consider system security as part of their day-to-day development routine. Establishing the mindset and processes in the development team is the first and most important step.

Continuous Security Testing

Security testing should be part of your continuous testing pipeline. The earlier in the release timeline a security vulnerability is identified and fixed the cheaper.

Basic tests based on the OWASP Top 10 should be done on API level as well as on End-2-End-level. Typically, defense against SQL Injections is tested best on API level (because of speed), while defense against XSS is tested best on End-2-End level (because of Javascript execution).

Specialised tools like Botium help in setting up your continuous security testing pipeline for chatbots.

Conclusion

Chatbots open the same kind of vulnerabilities, threats and risks as other customer facing web applications. Due to the nature of chatbots, some vulnerabilities are more probable than others, but the well established defense strategies will work for chatbots.

Don’t forget to give us your 👏 !

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Top 3 Chatbot Security Vulnerabilities in 2022 was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

The idea of incorporating robots into your marketing mix is a little bit intimidating. Many users are still hesitant to bring AI into their business, making the thought of using chatbots for marketing scary. But truth be told, robots aren’t here to make our life harder– they are here to enhance it. Online chatbots are easy to use and provide an effective way for brands to engage their users. They streamline many processes and help brands save time and money.

Whether you’re looking to solve customer issues promptly or provide relevant information to your users, chatbots are valuable tools to have right now. This article explains how using chatbots for marketing contributes to business growth.

Let’s get started!

What Are Chatbots?

A chatbot is a marketing tool that imitates human communication to help brands optimize their marketing efforts and engage with customers throughout the day. They leverage messaging mediums like SMS, social media sites, and website pop-ups to receive and respond to messages. Brands can program their chatbots marketing tool to respond to certain messages the same way or use machine learning to give appropriate responses to specific questions.

They allow brands to respond to pressing customer issues on time, whether users want to book a flight or return an item. Customers expect quick responses from the brands they are buying from, and chatbots for marketing allow them to reply instantly.

Other than getting quick answers to their questions, customers are messaging chatbots to:

• Resolve complaints or problems.
• Get detailed information about their queries.
• Reach a customer service agent.

These important use cases make chatbots a vital tool that every brand needs to invest in. Chatbot marketing statistics show that many brands are now using these tiny robots to engage their customers, resulting in improved customer satisfaction.

How Are Chatbots Set Up?

While chatbots for marketing aren’t a new business tool, their adoption has gained momentum in the last couple of years as businesses seek ways to streamline customer communication and drive sales. If you’re looking to add them to your marketing toolkit, you should note that it isn’t a feature within an app. It needs to be built externally depending on the API. You can do this in-house with a developer or through a third-party company specializing in chatbots.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Types of Chatbots

Not all bots are created equal. You can incorporate two types of chatbots into your digital communication channels to streamline customer communications. They include:

Conversational Chatbots

Conversational chatbots use artificial intelligence (AI) to understand the context and intent. Such chatbots for marketing are more sophisticated and deliver personalized responses to customer queries.

Rule-Based Chatbots

Rule-based chatbots respond to specific queries based on pre-set rules. These offer basic user engagement capabilities through pre-programmed answers, and their responses often resemble website FAQs.

Steps To Setup AChatbot

Eager to set up your own chatbot? Here’s what you need to build an effective chatbot to engage your customers.

Define Use Cases

With the different ways bots can be used for marketing, you need to define how you’ll use them to shape your chatbot communication strategy. Take time to research the circumstances that will require you to use chatbots. Are you looking to solve customer issues quickly, promote new products or generate quality leads?

The answers to these questions will help you figure out how to set up your chatbot. Reach out to your social media and website teams and tell them about the challenges they face with customer engagement. If they find it challenging to respond to all the messages, you need to set up a chatbot to handle customer queries.

Choose Platforms

Where do you want to install the bots? On your website to help customers find products and complete their orders, or on social media to respond to customer queries about your products and services? Instead of choosing one or the other, you can also set up chatbots for both your website and social media pages.

Check your marketing data to understand the areas that can be improved with a chatbot. If you are seeing lower conversion rates on your website, a chatbot marketing communication structure that provides users with all the information they need about your products or services would be ideal. For your social media chatbots, you want a program that answers common questions.

Content Strategy

The next step is to determine the information you want visitors to interact with when engaging the chatbot. Think about the popular questions users are likely to ask the chatbot and build useful information flows based on that. If you are unsure of the questions users are likely to ask, talk to your customer service, sales, and marketing reps for insights into user queries and concerns. You can also check Quorra for common questions regarding your brand.

Craft the Bot’s Language

Give your bot a personality to humanize its interaction with visitors. Craft the responses the bot will give when responding to customer queries. Make sure to set a consistent voice for all your chatbot’s messages to maintain uniformity in your customer communication.

Map the User Journey

Map out how the conversation journey will go after the first questions. You want to know the questions that will come next after a client starts engaging the chatbot. For example, if a customer asks if you have a specific product in stock, they will likely ask its price and how long it will take to ship the product. Add all these questions together and the possible replies to satisfy the user’s needs. Ask your sales team to guide you on this process.

Use CTAs for Checkout

Your chatbot interactions should culminate with a CTA after responding to all of your customer’s questions. Create a call-to-action that takes users to a specific page on your website or directly to checkout if the user was inquiring about a particular product.

Most Commonly Used Chatbots

The following are the most common chatbots based on the current chatbot marketing trends;

Facebook Chatbots

Facebook chatbots are popular with brands that want to maintain constant communication with their users. More than 100,000 bots are being used on Facebook to respond to customer queries, share product information, take orders, and collect customer information. Facebook chatbots are mainly used on Messenger and are activated when the user visits the brand’s page. They often drive action through discount codes.

Twitter Chatbots

Twitter bots are among the most effective social media chatbots for digital brands. Twitter for Business is a fantastic place for brands to deliver valuable information to their customers, and Twitter bots help brands respond to specific queries from their users. Take Audible, for example. The podcast company uses a Twitter chatbot to allow users to find appropriate listening material. The bot can take the user to the correct location after answering a series of prompts.

Figure 1: Twitter chatbot example. Source: Later

WhatsApp Chatbots

WhatsApp recently released an application to help businesses communicate more effectively with their users on the platform. The update comes with a suite of tools, including creating chatbots.

WhatsApp bots make it easy for brands to address customer service queries and provide customer support. With over 2 billion users globally, WhatsApp is the most popular messaging app, and their chatbots help brands communicate with their users through a set of automated replies.

Website Chatbots

Website chatbots have replaced live chat on most websites. These bots are intelligent and can complete a host of tasks, from booking consultative sessions with sales reps to delivering engaging content that pushes prospects down the marketing funnel. Website bots are launched as soon as a user lands on a site and use AI to help with user queries.

Benefits Of Chatbots

AI bots can fit seamlessly into your marketing activities to help you push customers through the sales funnel. Here are some benefits of using chatbots for marketing:

• Personalized experience — Chatbots gather data about your visitors to offer them personalized shopping advice.
• More engagement — Chatbots keep users connected for longer to provide you with more engagement opportunities.
• Wider audience reach — You can integrate them into multiple applications to help you reach more people.
• Data to analyze — Chatbots collect valuable customer data to help you understand your users better.
• Make brands more proactive and fun — Chatbots deliver quality information to users while making your engagements fun and interactive.
• Automate notifications — Chatbots allow you to automate your customer engagements to make your brand more proactive.

Messaging applications have become the preferred way for brands to engage their customers, which is why chatbots are very popular. By using chatbots for marketing, you can learn more about your audience, automate customer support and push prospects further down the sales funnel.

Atisfyreach, our AI-driven platform, has automated the entire influencer marketing process to make it easy for brands to find appropriate influencers to collaborate with for marketing activations. Campaigns run through the platform to ensure transparency and to help brands get value for their money.

Register on the platform today to get started!

Don’t forget to give us your 👏 !

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The Complete Guide To Mastering Chatbots To Market Your Brand was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Create chatbot using bot framework sdk and LUIS — Part 5

This the last part of this blog series.

In this part we will complete the coding for view orders and cancel order conversation flow.

Changes in vieworder_dialog

In the waterfall steps add a step view_step. Define the async functionfor view_step. Fetch user_id from context object. We have already defined a function getOrders in orderApp module (see previous parts of the blog) to fetch the orders from csv, which are not in “Cancelled” status, for the given user id. Now we will call that function. Function getOrders returns the result in dataframe. Read each row from the dataframe and display the result to the user as bot response. End the dialog to go back to the main dialog.

Below is the final code for vieworder_dialog.py

Changes in cancelorder_dialog.py

In cancelorder_dialog we will add 2 steps in the waterfall steps- intro_step and act_step.

In the intro_step, add code to prompt the user to provide the order id which he wants to delete.

In the act_step read the order id provided by the user. We have already defined a function cancelOrder in the module orderApp in previous parts of this blog series. As per our use case we will accept an order for cancellation only if it is in “Order Received” status. If the order is already picked for processing then it cannot be cancelled. Hence, in cancelOrder function, for the provided user id and order id parameters, status of the order is verified. If status is “Order Received” then the order status is updated to cancelled.

This cancelOrder fucntion is called in act_step. Message returned from cancelOrder function is displayed as the bot response to the user.

Final code for cancelorder_dialog:

We have now completed coding for all the modules. Time to test the bot. Run the bot framework emulator to connect to the bot service and test it. Follow the steps mentioned in Part 1 to test the bot using emulator.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Run the bot and select “Existing User” option. Provide the user id for which there are few orders available in the csv. Then select view orders option to verify if the order details displayed are correct or not.

After verifying view order flow, now select cancel order and provide an order id which exists in the csv.

Repeat the test for orders which are not in “Order Recieved” status.

Links for previous parts of this blog series.

Part 1, Part 2, Part 3, Part 4.

Source code for the bot is here.

Don’t forget to give us your 👏 !

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Create chatbot using bot framework sdk and LUIS — Part 5 was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

How to Create a Telegram Chatbot in 2022

Telegram has been growing in popularity ever since it was launched close to a decade ago. The app has close to 540 million users, 38% of whom are from Asia. The app offers a powerful alternative to WhatsApp and Facebook Messenger and claims to be more secure than both these platforms. In fact, speed and security are Telegram’s USP.

What is a telegram bot?

As the name suggests, a Telegram chatbot is a chatbot that lives on the Telegram platform and facilitates automated conversations between a human and a computer through the Telegram app.

The chatbot functions just like a human being with whom you are chatting using Telegram, with the only difference being that the responses are canned and you might get the same response for similar questions.

Why use a telegram chatbot?

If a large percentage of your target audience is active on Telegram, then it only makes sense to use the platform to provide better customer engagement using chatbots. Chatbots can give replies to common queries within seconds, rather than days.

Telegram is considered to be one of the most secure messaging platforms out there, thanks to its end to end encryption. This means customers will feel more secure dealing with a Telegram Chatbot than say, a human agent. Telegram is available on Android, iOS, Windows phones, desktop apps and also has a web version. This platform-agnostic feature of Telegram makes a strong case for creating a Telegram chatbot for your customers who may be using different devices.

How does a Telegram chatbot work?

Just like a normal person, a Telegram chatbot first analyzes what the user is asking for and then tries to give a response it feels best suits the situation. For example, imagine chatting with a Telegram bot of a restaurant. If you ask the question, “Can I see the menu, please?”, the bot understands the word “menu” and returns the Menu to the user. While there may be a lot of programming magic behind all this and we may be over-simplifying things, this is the gist of how a Telegram chatbot works.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Pricing of Telegram Chatbot

The pricing of the Telegram chatbot varies depending on the chatbot builder that you use. There are a tonne of chatbot builders available in the market, and a simple Google search will reveal that building a bot for say, 1000 messages will range from anywhere between $17 a month to $37 a month. For most users though, creating a chatbot is free, and all you have to do is search for Botfather and follow the on-screen instructions.

Without further ado, here are the steps involved in integrating Telegram with Kommunicate.

The integration presented in this blog post will teach you to:

• How to Integrate a Chatbot with Telegram.
• How to Connect a Bot to Kommunicate.

How to create a bot in Telegram

Open Telegram messenger, sign in to your account or create a new one.

Add the steps for this also a telegram.

Step 1: In the search bar, search for @botfather

Note, official Telegram bots have a blue checkmark beside their name

Step 2: Select the botfather channel and click /start.

Click on the “Send” button.

Step 3: Select /newbot — create a new bot.

Step 4 :Add a bot name to call ( channuJan22Bot) and enter bot name to display ( kmJan22Bot)

Step 5: Copy the API key that is generated under “Use this token to access the HTTP API”

How to Integrate a Chatbot with Telegram

Open Your Kommunicate Dashboard

Step 1: Click on Integrations

Step 2: Click on telegram card setting link

Step 3: Paste the API key into the Telegram integration card from the Kommunicate Dashboard and click the “Save and Integrate” button.

Step 4: Go to the channel that you have just created ( kmJan22bot) in Telegram and start a conversation.

You can now receive messages in the Kommunicate dashboard.

At Kommunicate, we are envisioning a world-beating customer support solution to empower the new era of customer support. We would love to have you on board to have a first-hand experience of Kommunicate. You can signup here and start delighting your customers right away.

Don’t forget to give us your 👏 !

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How to Create a Telegram Chatbot in 2022 — Kommunicate Blog was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

By now, most of us know that every learner requires different approaches to learning. There are many newer-age teaching methods including flipped learning, universal design for learning, and blended learning design.

The future of education is here and it brings countless new learning trends in 2022.

With our constantly-changing environment with regards to technology and the workforce, it’s not surprising that there are all sorts of new jobs (and even industries) that we’re hearing for the first time.

Not every student will follow the traditional path in their education or career, which is why relevant and specific industry skills and knowledge is highly valuable.

How can you equip students with targeted knowledge? That’s where just-in-time learning comes in.

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