This is personally my favourite video call application which is approved by TDRA. The BOTIM app allows the user to make audio or video calls to the contacts saved on their device. The app is available on both- Apple and Android devices and is free to use.

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How to Develop Botim Like Messenger App? - Explore detail guide for botim like messenger app development with key features and required tech.

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UAE – BOTIM, a mobile app owned by Dubai-based Astra Tech, registered transactions amounting to more than AED 1.30 billion through its fintech arm PayBy in four months (4M), according to a press release. The platform has grown 41 times since it was ...

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IBS Intelligence (IBSi) is the world’s only pure-play Financial Technology focused research, advisory, and fintech news analysis firm, with a 30-year track record and clients globally. We take pride in covering 400+ technology vendors globally – the largest by any analyst firm in this space.

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Botim

botim

Taming LLMs with Langchain + Langgraph

I’m a huge fan of automating working processes. I try to automate everything and save my coworkers time. This article I will show you how to improve the community onboarding journey with a custom Slack bot using the Slack Events API, hosted on AWS Lambda. Motivation We used to have a greeting new members in the . It messages new members with an introduction to help get an overview of the Ory community and products. Since this way of onboarding new members is and so the Ory DevRel team was looking for ways to improve it by making it and : bot Ory Community Slack impersonal one-way personal two-way Message each new member personally. Ask them what their biggest challenges or struggles are or what they want to achieve by joining the Ory community. Point them to the right place or people who can help with that challenge or help them achieve their goals. To keep the workload manageable, the initial message is pre-composed. A bot would either notify the team when new members join or message new members from a "human" account. So the options are: Ping the Ory DevRel team and notify them to greet a user. Send a greeting message from a Slack user. We landed on the second option and let the bot use a to send messages as a user. In the next part of the blog post, I’ll tell you how to build this bot. User OAuth Token Using Slack API Slack offers you a few examples of using APIs: Realtime API Webhook integration Events API I built Slack bots before, and the following two chapters are about the difference between integration and the . Just for convenience, let’s say that the Events API and webhook integration work almost the same way. WebSockets Events API Websockets Websocket is an excellent protocol. It's easy to implement, developer-friendly, and works on top of HTTP1/1. The protocol was first described in 2008, and in 2010 there was broad browser support. Websockets made the developer experience building real-time web applications much more enjoyable back in the day because you don't need to deal with and of HTTP1/1. Furthermore, new architectural patterns and paradigms such as and were described. BOSH chunked encoding Event-Driven Architecture Event-Driven SOA Despite the benefits described above, WebSockets have drawbacks. One of the most significant drawbacks is that it's built on-top-of HTTP/1.1 and keeps the connection open. It leads to scaling problems when you have more users for your application. We have two ways to scale our application: Vertical scaling. You add more resources such as RAM/disk/CPU or buy a new server. Horizontal scaling. You add more servers. You can move a database, webserver, or something else to a different server. Sometimes you need to scale your application horizontally. Horizontal scaling requires load balancing between the servers. Balancing HTTP traffic is easier than WebSocket traffic, and almost all load balancers such as Nginx, Envoy, or Istio balance traffic on L4 of the . It would be best to implement load balancing mechanisms on L7 when you work with WebSockets to have evenly loaded servers. OSI model Furthermore, it would be best to keep in mind that networks are unreliable or third parties may close connections and your application needs to handle it gracefully. In addition, you need to have a persistent listener of incoming events, which leads to the situation when you need to have EC2/VPS or any other server to run your code, but this is a cost-ineffective solution. Events API The Slack Events API works differently. You need to have a web server that is be publicly accessible and an event handler implemented in your app. According to the documentation of the Slack Events API, you need to implement the following steps: Use their signing tokens for incoming requests. Handle the URL verification challenge by your app. The app needs to sign the incoming request and return the incoming challenge parameter. The only thing we need to have is a web server with a simple REST API endpoint. It allows us to use various cloud features to run our bot and save money. For instance, we can use AWS Lambda, trigger it with API Gateway. The best part of this is that we can use the Free tier plan. That's why I'm a huge fan of the Events API from Slack. ![Illustration of Gopher at work](https://cdn.hackernoon.com/images/illustration-of-gopher-at-work.jpg"Illustration of Gopher at work") Let's build our bot, huh? Implementing the bot We will use the Go programming language to build our bot. What we need: Configuration for the bot using 12factors.net. In that case we will use the package because of its simplicity. envconfig package for local development and testing. net/http to make our web app accessible from the internet. Ngrok . AWS Go SDK Implementing configuration Let's create a package config package config

import "github.com/kelseyhightower/envconfig"

const (
	// EnvProduction is a production environment
	EnvProduction = "production"
	// EnvDevelopment is a development environment
	EnvDevelopment = "development"
)

// BotConfig is a struct that stores configuration parsed by `envconfig`
// environment variables
type BotConfig struct {
	Env            string `envconfig:"ENV" default:"development"`
	BindAddr       string `envconfig:"BIND_ADDR" default:":12022"`
	SigningSecret  string `envconfig:"SLACK_SIGNING_SECRET"`
	SlackBotToken  string `envconfig:"SLACK_BOT_TOKEN"`
	WelcomeMessage string `envconfig:"WELCOME_MESSAGE"`
}

// Parse parses and returns BotConfig structure
func Parse() (*BotConfig, error) {
	var c BotConfig
	err := envconfig.Process("", &c)
	return &c, err
} It's always a good idea to have some tests. package config

import (
	"os"
	"testing"

	"github.com/stretchr/testify/assert"
)

func TestParse(t *testing.T) {
	os.Setenv("SLACK_SIGNING_SECRET", "something")
	os.Setenv("SLACK_BOT_TOKEN", "amazing")
	os.Setenv("WELCOME_MESSAGE", "i guess")
	c, err := Parse()
	assert.NoError(t, err)
	assert.Equal(t, "something", c.SigningSecret)
	assert.Equal(t, "amazing", c.SlackBotToken)
	assert.Equal(t, "i guess", c.WelcomeMessage)
	assert.Equal(t, EnvDevelopment, c.Env)
	assert.Equal(t, ":12022", c.BindAddr)
} We can check it by simply running go test ./… Slack events API handler We can start with the example taken from the because of its simplicity. We need to extend this example with the following parts: Slack Go SDK Make it configurable what message we want to send as welcome. Support of AWS Lambda since it has its SDK. To get support for Go we can use the library. Check out the code below. algnhsa package app

import (
	"encoding/json"
	"greeter_bot/config"
	"io/ioutil"
	"net/http"
	"strings"

	"github.com/akrylysov/algnhsa"
	"github.com/slack-go/slack"
	"github.com/slack-go/slack/slackevents"
)

type (
	// Handler is an interface for the webserver that handles
	// incoming requests from Slack events API
	//
	// You can add support of any cloud provider by implementing this interface
	Handler interface {
		Init(c *config.BotConfig)
		Start() error
	}
	// HTTPHandler is an implementation of webserver for local development/testing
	HTTPHandler struct {
		Handler
		config *config.BotConfig
	}
)

// NewHandler creates slack events api handler
// It creates HTTPHandler for development environment
// and LambdaHandler for production env
func NewHandler(c *config.BotConfig) Handler {
	var h Handler
	h = &HTTPHandler{}
	h.Init(c)
	return h

}

// Init initializes handler
func (h *HTTPHandler) Init(c *config.BotConfig) {
	h.config = c
	http.HandleFunc("/", h.handle)
}

// handle handles incoming data from
func (h *HTTPHandler) handle(w http.ResponseWriter, r *http.Request) {
	var api = slack.New(h.config.SlackBotToken)
	body, err := ioutil.ReadAll(r.Body)
	if err != nil {
		w.WriteHeader(http.StatusBadRequest)
		return
	}
	sv, err := slack.NewSecretsVerifier(r.Header, h.config.SigningSecret)
	if err != nil {
		w.WriteHeader(http.StatusBadRequest)
		return
	}
	if _, err := sv.Write(body); err != nil {
		w.WriteHeader(http.StatusInternalServerError)
		return
	}
	if err := sv.Ensure(); err != nil {
		w.WriteHeader(http.StatusUnauthorized)
		return
	}
	eventsAPIEvent, err := slackevents.ParseEvent(json.RawMessage(body), slackevents.OptionNoVerifyToken())
	if err != nil {
		w.WriteHeader(http.StatusInternalServerError)
		return
	}

	if eventsAPIEvent.Type == slackevents.URLVerification {
		var r *slackevents.ChallengeResponse
		err := json.Unmarshal([]byte(body), &r)
		if err != nil {
			w.WriteHeader(http.StatusInternalServerError)
			return
		}
		w.Header().Set("Content-Type", "text")
		w.Write([]byte(r.Challenge))
	}
	if eventsAPIEvent.Type == slackevents.CallbackEvent {
		innerEvent := eventsAPIEvent.InnerEvent
		switch ev := innerEvent.Data.(type) {
		case *slackevents.TeamJoinEvent:
			text := strings.Replace(h.config.WelcomeMessage, "\\n", "\n", -1)
			api.PostMessage(ev.User.ID, slack.MsgOptionText(text, false))
		}
	}
}

// Start starts the server
func (h *HTTPHandler) Start() error {
	if h.config.Env == config.EnvDevelopment {
		return http.ListenAndServe(h.config.BindAddr, nil)
	}
	algnhsa.ListenAndServe(http.DefaultServeMux, nil)
	return nil
} To start everything up we need : cmd/mrrobot/main.go package main

import (
	"greeter_bot/app"
	"greeter_bot/config"
	"log"
)

func main() {
	c, err := config.Parse()
	if err != nil {
		log.Fatal(err)
	}
	handler := app.NewHandler(c)
	log.Fatal(handler.Start())
} Creating Slack bot Press button on . Create New App Slack apps page Click on and then input your bot name and choose a workspace to install the bot. From scratch Copy the and store it somewhere. You'll need it to configure AWS Lambda function. Signing Secret Go to the and generate access tokens under . You need the when you want to send message from a user and the for the bot user. You'll need it to configure AWS Lambda. OAuth & Permissions Oauth Tokens for YOur Workspace User Oauth Token Bot User Oauth Token Under the scopes add for both the and scopes. chat:write Bot Token User token Deploying to AWS Lambda Sign in to . AWS Console Go to the Lambda section and press button. Create function Choose input the name of the function. Choose for the runtime and architecture and then create a function. Author from scratch Go 1.x x86_64 Open -> . Configuration Environment variables Set your to variable. Signing Token SLACK_SIGNING_SECRET Set your welcome message to variable. WELCOME_MESSAGE Set your bot token to variable. SLACK_BOT_TOKEN Set to variable. production ENV Go to the section and scroll down to and change from to . Code Runtime settings Handler hello mrrobot Configuring AWS Gateway Create a new REST API. In the "Resources" section create a new method to handle requests to (check "Use Lambda Proxy Integration"). ANY / Add a catch-all resource to handle requests to every other path (check "Configure as proxy resource"). {proxy+} Final steps You need to upload the zip archive with compiled binary to the AWS lambda. In that case, can help us - allows us to automate operations since 1976. Also it always a great idea to have them self-documented: make make .PHONY: help

help:
            @grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'

lint: ## Runs linter against the code
            golangci-lint run ./...

test: ## Run tests locally
            go test ./...

build_docker: ## Build docker image
            docker build -t mrrobot .

build_linux: ## Build executable for linux system
            GOOS=linux GOARCH=amd64 go build -o mrrobot cmd/mrrobot/main.go

zip: build_linux  ## Build and create a zip archive for deploying to AWS lambda
            zip main.zip mrrobot Run . make zip Open your function on . AWS Lambda Choose under the source code section. Upload from Upload it and run. Choose your application on on Slack, click on and choose . Apps page Add features and functionality Event subscriptions Insert URL of your API Gateway to the field, pass the verification step, and click . Request URL Save Open and choose event and then press . Subscribe to bot events team_join Save That's it. You can now invite a new member to your Slack and test the bot. Conclusion and takeaways As you can see the Slack Events API helps you to build bots and automate your routine. Also, if you just build a simple bot you don’t need to spend money on hosting. Also Published Here

Using the Events API to Build a Slack Bot 

The world has been evolving ever since its inception. There is no doubt that Generation-Z (1997-2012) has witnessed many changes. These changes were related especially with the advancement of science and technology. The concept of video calling dates back to the year 1910, and back then it was termed as video telephony. So, the concept is pretty antiquated, but with time innovation played its part and kept it looking contemporary. Having said that, we’ll now look at the options we have when it comes to video calling. The above-shown picture is the earliest concept of Video calling by an artist of the year 1910. According to the artist, this is how people were supposed to communicate by the year 2000. The year 2000 is now behind us past 20 years, and apparently we have exceeded the expectations of the people in the past. In year 2020, the top video chat apps are mentioned below; Skype: For many people, Skype is one of the earliest memories of video calling. They remember using it for making video calls to family members living abroad. And people still use it to do a video chat, with anyone they want to or need to. The app for Skype is free and you can easily make free calls from any device that’s in your use. Facebook Messenger: Facebook messenger is one of user’s favorite video apps. It is quite comfortable and easy to use. Facebook Messenger can also be used with or without Facebook. But Facebook for phone can’t be used without messenger. As we connect on Facebook with people all over the world, we make friends, we have video chats to exchange knowledge and we showcase our expertise there. Anyone who uses Facebook can organically. This way you can make a very good social media presence and you can also have a lot of people to have live video chat with.  For this purpose Facebook messenger is a must have app. It is like a Facebook exclusive WhatsApp. buy Facebook Likes WhatsApp: In the year 2020, if you aren’t aware of WhatsApp, then you are probably an alien. It is impossible not to have WhatsApp if you have a phone. It allows free calls to the numbers in your phone contact list. So, if you don’t have credit to make a call from the SIM network you are using, then you always have the option to use WhatsApp as long as you have an Internet connection. It allows simple text messaging, voice messaging (we also refer to them as voice notes), simple calls (video off) and video calls with video on, of course. WhatsApp is a necessity for smartphones. You may have many apps for making video calls, but you’ll always revert back to WhatsApp. Botim: Relatively new app to facilitate video calling, chatting through typing messages and voice notes. It is pretty similar to WhatsApp, and as mentioned it is comparatively new. So in the year 2020, in all the options that you have, you can also have Botim as another option. Microsoft Teams: Considering, the current pandemic situation which is created by Corona virus. Microsoft teams is the one app that is on the phone of every other student. The students are using it because countries have decided to stay in quarantine. The use of Microsoft team is more suited for educational and professional use. Although once the teams are created, the members can chat and do video calling with their own discretion as well.  Microsoft Teams is a pretty engaging platform, more then we realize. During lectures it allows you to share material. Take, for instance, you have a presentation to deliver and you want your PowerPoint slides to be shown. In such a case, Microsoft teams gives you an option of ‘slide share’ and your task is done. There is so much to learn at Microsoft teams.

How to Build a ChatOps-Bot with Slack and Kubernetes

I’m a part-time trader. I trade on stock markets, and recently, at the beginning of 2019, I've tried trading on crypto markets. People often think that the life of a trader is swimming for hours on end in money, but that is so far from the truth. Sometimes you lose money, sometimes you think that you should have found a better application for your time instead of staring at the screen for half a day. But I love trading and I'm profitable most of the time. When I started trading crypto, it was a little bit overwhelming because the crypto market is open 24/7. I've adapted since then, and I want to share with you all the little tricks that I've learned about trading crypto, and how I've optimized my trading to be in the green without being chained to the trading interface. Hopefully you'll find my experience useful and avoid the mistakes I made. Trader’s life: illusion vs. reality Being a trader, I don’t have a gold Rolex or a yacht. I don’t yell into my phone “SELL, SELL, SELL IT ALL RIGHT NOW, JOHNNY” as ticker tape streams from the ceiling behind me. Also, I live in a normal house, not under the shadows of palm trees with beautiful women sitting on my lap (my wife wouldn’t like that very much). Sorry to say, I don’t live the stereotype that so many people have about traders. In reality, when I actively trade, it's a boring activity, that requires a special, non-dramatic mindset: You have to wait for opportunities. You have to learn to be patient, because patience is the only way to win in the market. You trade against countless other trades, and the money that you win is always someone else’s money they are losing. Source: xkcd.com I spend a lot of my time watching the charts and price movement of various assets. I drink coffee to keep myself focused. Sometimes I go for a walk when I’m out of positions, but I often return to find, with great disappointment, that I’ve missed some good opportunities, and it’s already too late to enter. But my first lesson that I’ve learned by losing money was: you can’t afford to get distracted when you’re trading. The market can go the opposite direction, and you have to get out quick. If you don’t, it can be really bad for you. So I have to spend a lot of time in front of my screen during trading hours. You know, coffee and red eyes; the trader’s starter pack. Don’t forget the constant stress when you’re not winning. And all of this got even worse when I entered the crypto market. The cryptocurrency market: a non-stop rodeo For a day trader, the crypto market is a rollercoaster ride that never stops. You can get amused, or you can get nausea if you ride too much. It requires even more concentration, because it's open all hours of the day! It's basically a stock market on steroids. It took me some time to truly grasp that concept. The Toronto Stock Exchange is for 7.5 hours every weekday, from 9:30 a.m. to 5 p.m., so I wasn't accustomed to trading the whole day and night. Everything I've told you about markets applies to crypto too; you still need to watch all market movements, but it's stretched around a 24-hour period. Every 8 hours some large part of the world wakes up and starts trading. Asia, USA, Europe - all of them can dump or pump the market, and you have to respect that. open If I have to compare the crypto market to the stock market, I would compare it to - it goes up and down with crazy swings, and if you trade with leverage (which I don't recommend) you'll get liquidated very quickly. I didn't lose all my money by liquidation, but I know traders who did. Thus, the second lesson I've learned on the market by observing other traders is to never trade on margins. It's even more punishing in the crypto market simply because you often see price moving 20% during the day, and your wins and losses are multiplied by that much. penny stocks Source: bullvestorbb.com Another thing that distinguishes crypto markets from the stock market is that it’s heavily based on trading patterns. Crypto doesn’t generate revenue, it doesn’t have quarterly reports to influence the price, so the most important thing is the trading patterns, and you have to watch out for them. It’s certainly not the most interesting thing in the world. At some point, I got really tired of trading that much, and I had to stop and reevaluate my approach to crypto. I wanted to live a life instead of stare at the screen. What options I had and what did I choose In my situation, I had three options: To become a 24/7 trader To put my money into a fund Use trading bots The first option didn't suit me at all, as you probably understand. I wasn't feeling any delight from trading every waking hour of the day. The second option was potentially dangerous for the safety of my funds, as only the trading gods know what can happen when you don’t have control over your money. Crypto is a very young industry, so it doesn’t have any established industry standards yet and I’m not ready to trust my money to any other person. That left me with only one option: trading bots. I wasn't familiar with trading bots before, so I tried a few of them; , , , , , . By reading the reviews, I guessed these were the most popular bots among crypto traders, and after much deliberation I finally made my choice. To this day, I still use TradeSanta. TradeSanta Shrimpy CryptoTrader CryptoHopper 3Commas Levidge You make money and you save time Lesson number three: my time is valuable too. I didn't want to spend it on such things as watching charts all day, every day, so I configured a trading bot that now trades according to its predetermined strategy; finding certain patterns, buying, and selling when necessary. My choice of TradeSanta was dictated by obvious reasons; I wanted a simple interface and an easy configuration. I'm no novice, but I love simplicity: You don't have to install TradeSanta on your computer, it's cloud-based and you can check on it from a mobile phone. It doesn't need your private keys, as it connects directly to an exchange of your choice, and sends commands to the exchange according to your configuration. Remember, I'm not ready to trust my money to anyone. It follows the trading signals. After seeing an opportunity on the chart, it opens and closes the deal. The whole process can take only a few seconds, much faster than any human interaction on a laggy interface. That's how it makes money (for me!). Source: tradesanta.com The initial configuration isn't very complicated either. You set the parameters, choose the long and short strategy, and choose the trading pair. You can also choose the amount of extra orders (the orders to be executed if the price goes in the wrong direction). After that setup you choose the exchange you want to connect it to. Currently, you can choose from Bitfinex, Bittrex, HitBTC, Binance, and several others. BitMEX, OKEX, and Huobi are promised to be added in the future. Most importantly, it doesn't cost a fortune but it puts money in my pocket. I use a paid plan, but if you're a small-time trader, you can use the , which gives you access to five bots. free plan Fifteen dollars per month isn’t an expensive price to pay for all the help that I get from this bot. Which is precisely why I will continue using it in the future. For anyone who’s interested in using it, I would recommend starting from small volumes and expand if you find it comfortable. Do you have to follow my advice? Not at all! But remember: the crypto market is a place where you can make a lot of money with its high volatility, but the market is just that… volatile. In exchange for all these profits, though, you have to sacrifice all your free time, wake up at night to check your positions, or outsource it to a trading bot, like I did. Trading bots are trading tools, and there's nothing wrong with using one. Who would blame software that can make money 24/7 even when you’re asleep, when you're at work, or while you're out on the town spending some of that money? Not me. As a trader, I’m just getting started.

3 Lessons I Learned while Trading on the 24/7 Crypto Market

I recently had an idea for a for the community, which I thought would be a fun project with half a day worth of work. Moreover, I wanted to use AWS Lambda function for the sake of learning. Why AWS Lambda? Because it’s practically free for maintaining a twitter bot and I got hands on experience with a seemingly complex tool used widely in the industry. You get 1,000,000 free requests and 400,000 seconds of compute time per month for AWS Lambda. My bot uses 0.02% of the above numbers. Twitter bot #LearnInPublic In the process I found a cool use-case Webpack. I had fun reading the webpack docs and figuring learning about the gotchas. Even though it was a very primitive use-case, felt like a true Sean Larkinn for a day. Here is a detailed article on how you could do the same. A little about the bot itself. About half a year ago when , it resonated with me like nothing had ever before. It felt like a nudge in the right direction and I ended up saving the post to read it every now and then for motivation. I thought it’d be cool to write a bot which tweets the same post periodically (so that it keeps resurfacing on my feed) and retweet all the posts with the #LearnInPublic hashtag concentrating the community’s work under a single roof (profile). Shaun Weng wrote about learning in public swyx Prerequisites Goes without saying, you’ll need Node.js installed on your computer, a Twitter account for the bot, and an AWS account. This tutorial also assumes you’re familiar with node and won’t go into great depth of the bot’s workings. The tutorial is divided into three main sections Setting everything up (Twitter, AWS Console, Bot config). Writing the bot and building it with Webpack. Deploy with AWS Lambda! SETUP This section handles all of the account setups you need to take care of for each of the platforms that you’ll be using. Twitter You’ve to make a new account for the bot which is going to responsible for posting/retweeting on its profile. Once you’re done with that goto and setup a developer’s account. https://developer.twitter.com/ Create a new app at by filling in the appropriate information. Once the app is successfully created, note down the API keys and access tokens. https://developer.twitter.com/en/apps/create AWS You should have an AWS Account to proceed, If you don’t, you can create one at . Once done we can proceed with he setup for the lambda function(s). https://aws.amazon.com/account/ I was using AWS for the first time so I’m not sure If I am understood the Identity tools (IAM Users and Roles) correctly or If I used them right, however these are the steps I took from my best understanding of the docs and it does work, so here goes nothing ¯\_(ツ)_/¯ . When you make an account on AWS and sign in using the email/password, you are logging in as the root user. The root user has complete access to all AWS services and resources, hence it is recommend to not use the root user for everyday tasks. For greater security and organisation, you can give access to your AWS account to specific users — identities that you create with custom permissions. This is where AWS IAM comes into play. AWS Identity and Access Management (IAM) enables you to manage access to services and resources securely. Using IAM, you can create and manage AWS users and groups, and use permissions to allow and deny their access to AWS resources. Go to the to create a new User. Name it such that you Identify what it’s purpose is (e.g twitter-bot). Make sure the User has AWSLambdaFullAcces policy attached to it. AWS IAM Console Additionally also create a IAM Role, IAM roles are a secure way to grant permissions to entities that you trust. You can create a role from the same AWS IAM Console. Select Lambda as the service which will use this role. You’ve to attach the same permission policy of AWSLambdaFullAcces for this Role as well. Give it an appropriate name (e.g lambda-twitter-bot), description and create the role. Twitter Bot I used the npm package which is a Twitter API Client for node to interact with the Twitter API. Once you’ve written the bot, you’ll need to upload a compressed zip file of the folder with code to the AWS Lambda console. twit Instead of uploading the entire which may have dev dependencies and other config folders adding to the bloat, we will bundle the app using Webpack and zip a single file for the upload. node_modules Make a folder for your project and initialize your node project after changing into that directory. Then, install twit as a dependency for your project. mkdir twitter-bot cd twitter-bot && npm init -y npm install --save twit Next, we need to setup the API Keys we acquired from twitter for both the development and production environments. We are going to maintain a with local copy of the API keys and to access the production environment variables bound to the same API keys, that we will eventually set on the AWS Lambda Console. If you’re uploading your code to GitHub, make sure you don’t commit , add it to .gitignore. Depending on the environment we’ll export the appropriate file. dev.js prod.js dev.js mkdir config && cd config touch index.jstouch dev.jstouch prod.jS index.js if (process.env.NODE_ENV === 'production') {module.exports = require('./prod');} else {module.exports = require('./dev');} dev.js module.exports = {consumer_key: 'YOUR CONSUMER KEY HERE',consumer_secret: 'YOUR CONSUMER SECRET HERE',access_token: 'YOUR ACCESS TOKEN HERE',access_token_secret: 'YOUR ACCESS TOKEN  HERE'}; prod.js module.exports = {consumer_key: process.env.CONSUMER_KEY,consumer_secret: process.env.CONSUMER_SECRET,access_token: process.env.ACCESS_TOKEN,access_token_secret: process.env.ACCESS_TOKEN_SECRET} Writing the bot and building it with Webpack For my bot I needed two different functionalities (tweet and retweet) to be triggered by AWS Lambda at different time intervals. Let’s proceed with only one of them as an example. (If you have a use-case similar to mine just deploy two lambda functions like I did). The example is of a bot which retweets posts a certain hashtag, but doesn’t retweet it’s own posts. The format for an AWS lambda function is as follows, hence you will need to export your function: exports.handler = (event, context, callback) => {//function logic} Fun fact: Don’t use a forEach loop as they don’t work with asynchronous code. Here’s a great article on the same . I’ll not dive too deep into the working of the bot’s code, it’s quite straightforward if you read the . You query for all the recent tweets with the given hashtag. On receiving the response, you de-structure out the all the statuses, loop over them and retweet them. The loop works well with the asynchronous async/await. docs for twit for .. of You can test the code by entering the Node.js console. > node> let retweeter = require('index.js');> retweeter.retweet(); WEBPACK!!!!!! Next we bundle the code for easier deployment to AWS Lambda because we don’t need no in our zip. node_modules is a for modern JavaScript applications. When webpack processes your application, it internally builds a which maps every module your project needs and generates one or more . Webpack static module bundler dependency graph bundles Webpack v4 is easier to use than ever before, and does not even require a config file by default. It can look daunting to beginners (like it did to me for the longest time) but it is very well documented and it’s easy to find your way around it. Step 1: Install Webpack as dev dependencies. npm install --save-dev webpack wepback-cli Step 2: Modify **package.json** to add the build script. //package.json {"name": "twitter-bot","version": "1.0.0",..."scripts":{** "build": "webpack",**....},......"devDependencies": {"webpack": "^4.29.0","webpack-cli": "^3.2.1"},"dependencies": {"twit": "^2.2.11"}} Step 3: Add Webpack config. Add to the root level of your project directory. webpack.config.js //webpack.config.js const path = require('path'); module.exports = {entry: './index.js',output: {path: path.resolve(__dirname, './dist'),filename: 'index.js',libraryTarget: 'commonjs'},target: 'node',mode: 'production'} Here’s a list of what all the parameters are for Note: If you have more than one functions with different configuration (like I did as I needed two different outputs for different lambda functions) you can export multiple configurations by exporting an array of config objects. module.exports = [{//config 1},{//config 2}] Entry An entry point indicates which module webpack should use to begin building out its internal . Webpack will figure out which other modules and libraries that entry point depends on (directly and indirectly). dependency graph The entry point for this bot is . index.js Output The output property tells webpack where to emit the it creates and how to name these files. bundles tells webpack where to emit the bundle and is used to specify the bundle name. output.path output.filename Since exports an object with the function as per AWS specification, our bundle should do the same. You can test this behaviour in the node console. index.js retweet > var library = require('./index.js'); > library {  retweet: [AsyncFunction: hashtagRetweet]  } makes sure that in the bundle itself, the function that is generated by webpack from the entry point will be assigned to the object. output.libraryTarget: "commonjs" exports Target Instructs webpack to target a specific environment. Use to compile for usage in a Node.js-like environment node Mode By setting the parameter to either , or , you can enable webpack's built-in optimizations that correspond to each environment. The default value is . mode development production none production And that’s about it for webpack! Whip up your terminal and to generate your production grade bundle in . Zip up the dist folder as the Lambda console only accepts .zip files. npm run build ./dist > > cd dist> zip bot.zip index.js npm run build Deploy using AWS Lambda! At the final stage of our journey, we’ll make this bad boy live! We want to upload our lambda function and make sure it is triggered in set intervals. The CloudWatch Event which comes with AWS is the perfect solution for it. The CloudWatch Event trigger lets you schedule it’s your function calls. It is basically a cronjob for your lambda function. Go to your Lambda Management Console, you can access it from Services in your navbar. Create a new lambda function there. Give it a suitable name, choose the Node.js 8.10 Runtime and choose the Role you created earlier in the setup stage. New features such as async/await syntax works because the LATEST node runtime is supported by AWS Lambda. In the lambda console you’ll have various options to trigger your function. Upload the zip file from the dist folder. Change the filename to In this example, it’ll be [filename].[function name] index.retweet Next we add the production environment variables. Scroll down to find the section to input environment variables. Open you file and copy the environment variables one by one. Pay special attention and make that sure you copy the exact variable name. prod.js Finally, add a CloudWatch Event trigger in the function Designer. Select the CloudWatch Event and scroll down to configure it. Create a new rule where you declare the rate at which your function should be called. //Syntax: rate(V ) _alue_ U _nit_ // is a positive number// can be minute | minutes | hour | hours | day | days Value Unit E.g, For a duration between function calls to be 5 minutes, the expression should be rate(5 minutes) Save the function and your bot should be ready to go! Test out your function with the Test button on top. Out bot’s function doesn’t take any parameters. Your bot will be up and ready, doing its magic and saving you time and money. In case you wan’t some metrics for your lambda function, the CloudWatch metrics under the monitoring tab provides some cool charts on invocation, duration, errors, availability etc to give you an estimate of your function’s performance. You can also read CloudWatch Logs that captures as well, this might help you debug stuff. console.log BUT YOUR BOT IS UP AND RUNNING TWEETING WITHOUT ANY HUMAN HELP AT THIS POINT! BE PROUD OF YOURSELF! THANKS FOR READING I am a web and mobile developer based in India. I love React/React Native/JavaScript. I write about my adventures with tech, projects and Hackathons. If the article helped you, smash that like button (jk but you can clap em). I’m on Twitter, if you want to me talk about React, tech, JS, football, anime, eSports and just about anything. I’m also redoing my website and I’ll link it as soon as I finish,Cheers. soumikcv

Deploying a Node.js Twitter Bot on AWS Lambda using Webpack

Hi! This article is aimed at developers who already possess working knowledge of , and want to implement a monetization option. I will outline the basic steps which must be undertaken to get your bot to start accepting payments using the official Bot payment API and provider. Telegram-Powered Bots Paymentwall This article does not go into technical detail and discuss any code necessary for implementation, but it can give you a basic general understanding of the integration process. What is Bot Payments API? Last year, Telegram released an important which facilitated the creation of bots to generate invoice message and show native payment dialogue. However, this feature is currently only supported on mobile devices and is not compatible with the desktop and web version. As Telegram official says: update documentation Telegram bots can accept payments for goods and services from users as of . Users will need or higher to pay for your goods and services. Bot API v.3.0 Telegram v.4.0 Using Telegram Web, the user will not be able to get even invoice message. Attempting to open a payment dialogue with the desktop or web version will result in the following error message: However, don’t fret as almost all payment processors offer you the opportunity to generate a payment widget which can be integrated in your bot and opened using a browser. You will need to add all the relevant product details. You will need to specify your product details, like price, name, currency, etc to get the link. All payment processors will provide technical documentation about implementation: So now you have two possibilities for using your bot: In-app payment (Bot Payments API) Using web payment widget (Payment provider API should support this) I decided to implement both in my bot game, see the screenshot below: In-app and web payments Using Telegram Bot API you , which means that you will be unable to specify the necessary currency for invoicing. There are no chance to track user location even through analytics tools like Yandex AppMetrica or Google Analytics (you will track as a location for every user). But you still can give your user a UI to select currency. won’t be able to get user location Botswana Also, there is from your bot message data**.** So you can’t switch payment options on the fly based on user platform. no chance to get user client platform Summing up: Only credit card payments Available for Telegram mobile apps only Users will pay inside the application 💳 Payment provider Telegram does not process payments from users and instead relies on 3rd party . They are the ones that will handle and store all the sensitive information such as card details, name and address. Neither Telegram nor the bot developers have access to it. payment processors So, Telegram acts like a middleware between user and payment provider, and it also doesn’t charge any commission for this option. At the moment Telegram Bot Payments API is integrated with several payment processors: Stripe Paymentwall Yandex.Money Sberbank Payme CLICK Rave by Flutterwave Tranzzo I was looking for payment provider which will support processing for users from CIS region and came across as the best option for myself. It’s API provides support for generating payment widget for the browser as well as processing credit cards payments through Bot Payments API, furthermore, it supports a far larger number of countries in comparison to the providers mentioned in the list above. Paymentwall 🇺🇸 🇨🇦 🇩🇿 🇦🇸 🇦🇩 🇦🇷 🇦🇲 🇸🇭 🇦🇺 🇦🇹 🇦🇿 🇧🇸 🇧🇭 🇧🇩 🇧🇧 🇧🇪 🇧🇿 🇧🇲 🇧🇷 🇧🇳 🇧🇬 🇰🇭 🇰🇾 🇨🇱 🇨🇳 🇨🇰 🇨🇷 🇭🇷 🇨🇾 🇨🇿 🇩🇰 🇩🇲 🇩🇴 🇪🇨 🇪🇬 🇸🇻 🇪🇪 🇫🇰 🇫🇴 🇫🇯 🇫🇮 🇫🇷 🇬🇫 🇵🇫 🇬🇪 🇩🇪 🇬🇮 🇬🇷 🇬🇱 🇬🇩 🇬🇵 🇬🇺 🇬🇹 🇬🇾 🇭🇳 🇭🇰 🇭🇺 🇮🇸 🇮🇳 🇮🇩 🇮🇪 🇮🇲 🇮🇱 🇮🇹 🇯🇲 🇯🇵 🇯🇴 🇰🇿 🇰🇷 🇰🇼 🇰🇬 🇱🇻 🇱🇮 🇱🇹 🇱🇺 🇲🇴 🇲🇰 🇲🇾 🇲🇻 🇲🇹 🇲🇭 🇲🇶 🇲🇺 🇲🇽 🇲🇩 🇲🇨 🇲🇪 🇲🇦 🇳🇵 🇳🇱 🇳🇨 🇳🇿 🇳🇮 🇳🇺 🇳🇫 🇲🇵 🇳🇴 🇴🇲 🇵🇼 🇵🇦 🇵🇾 🇵🇪 🇵🇭 🇵🇳 🇵🇱 🇵🇹 🇵🇷 🇶🇦 🇷🇪 🇷🇴 🇷🇺 🇻🇨 🇸🇲 🇸🇦 🇷🇸 🇸🇨 🇸🇬 🇸🇰 🇸🇮 🇿🇦 🇬🇸 🇪🇸 🇱🇰 🇰🇳 🇱🇨 🇵🇲 🇸🇷 🇸🇪 🇨🇭 🇹🇼 🇹🇭 🇹🇰 🇹🇴 🇹🇹 🇹🇷 🇹🇲 🇹🇨 🇹🇻 🇺🇦 🇦🇪 🇬🇧 🇺🇾 🇻🇳 🇻🇬 🇻🇮 🇼🇫 🇼🇸 🇦🇼 I haven’t made a comparison between rates and the commission surcharge for each and every, so it’s entirely possible that other providers might be cheaper than Paymentwall. You can carry out some independent research and pick the one that will fit your bill. The main requirement is that your provider’s API should have an option to generate payment widget for the browser as well as support Bot Payments API. Please note, that every provider will verify you as a merchant, and you should be ready to send them all of required documents when requested. Products you want to sell, and your bot will be verified based on provider rules and restrictions. They will verify you in order to make sure that you are selling authentic products. For example, here is the list of prohibited areas that Paymentwall will not be able to work with. In my case, I was planning to sell an in-game virtual currency, so it was a typical case for verification process. My verification took , but that’s because I wasn’t able to prepare all documents in time, so it could be faster. I was receiving full support about needed documents and technical integration during set up. approximately 2 weeks Summing up: Your provider should support Bot Payments API as well as payment widget generation for the browser. It should have convenient rates and commissions that will fit your expectations. Should support your target countries, and credit cards processing in that countries. 📃 Terms and conditions You must have clear document with Users should accept it before actual payment or before registration. You also must provide and be able to handle refund or other payments related requests from your bot users, they shouldn’t go to payment provider or Telegram support. terms and conditions the refund policy. customer support There are no strict rules about writing terms and conditions, but the main point that you should specify in which period your user can request a refund after the payment was done. — Product return, a process in which a consumer returns a product to the original retailer in exchange for money previously paid. Money back guarantee — a guarantee that, if a buyer is not satisfied with a product or service, a will be made. Refund refund Here are the from my bot game. Feel free to use it as an example for your bot. I’m showing it in the payments step because I don’t want to block the user with it during registration. Terms and Conditions Payment step message from bot Summing up: You need terms and conditions with the refund policy Users should accept your terms and conditions before payment You need to provide customer support for your users, every user should easily find support link. 📝 Registration and integration I’m using for my bot game, so next words will be about integration with this payment provider. Paymentwall First of all, you need to connect your bot to the payment provider you select. For that you need to go to the , select your bot, click select Paymentwall from the list and click (you will be able to after test integration) BotFather Payments, Connect Paymentwall Test Connect Paymentwall Live After the click, you will be redirected to the provider’s authorization bot. Here you just click like in regular Telegram Bot, and then you will see next message: Start, Paymentwall authorization bot The link from button leads to Paymentwall step, where you will be asked for approval to authorize your account if you have one. OAuth Paymentwall oAuth step But probably you don’t, so after redirect you will see account registration form. Proceed with it and then you will be redirected to that step. After authorization, you should be redirected back to the Paymentwall Bot where you will get a message that your account was successfully authorized in the system. Authorization complete BotFather will show you for Bot Payments API, you will use it for sending invoice messages. Telegram has an and about how to implement invoice messages logic in your bot. test token article API docs During test integration, you will need to make test payments. You can use test credit cards and codes from Paymentwall to emulate different responses. sandbox In your Paymentwall dashboard you will see section where all your projects are listed. After registration there will be two tests projects, one for bot payments, it’s name will start from numbers and contain label. The second project is created by default, you will be able to use it for displaying payment widget in the browser. You can read more about payment widget integration in . My Projects Test API docs Note, that payment web widget provides , which depend on user country and your project settings, while Bot Payment API supports several payment options credit cards only. Now you can start to fill in business profile and upload required documents ( . Documents list is based on your country of registration and business type (individual or company) and you will see it on the last step of the business profile form. If you will have any issues, feel free to contact the support team, they should consult you during merchant validation process. Go to Account -> Business Profile) Summing up: Authorize through BotFather and connect Test project. Implement send invoice mechanism in your bot. Complete your business profile and upload required documents. Docs: Bot Payments API integration Paymentwall Widget API Test credit cards 🚀 Going live Once your merchant account will be approved and test integration will be done, you can go to the @BotFather and You will go through the same process as connecting test. New project with label in the name, will be created in your projects list. BotFather will show you a for bot payments. Connect Paymentwall Live. Live live token Now you can submit your for review by Paymentwall integration team. On this step, they will verify how legal is your product and whether it satisfies all requirements. They will be checking your user policies, so you should prepare this documents before this step. live projects They will also check how technical integration was made and does your application correctly handles service from Paymentwall. pingbacks And once project review process is done, you are ready to start accepting payments from mobile, web and desktop Telegram users 🎉 Your telegram mobile and Paymentwall Web widget (on the yellow background) P.S. If you want to see a live demo, check my bot game by this . You will need to register your character and the go to the 🏘 🏦 💎 to be able to check payments flow. link Town — Bank — Buy diamonds Thank you for reading! Cheers! 🍻

How to start accepting payments with your Telegram Bot

Photo by on Andy Kelly Unsplash I’m frustrated. have the potential to be amazing. The Star Trek computer seemed like it was finally becoming a reality. So far, we’ve been let down. Most chatbots are rubbish and it’s the that are to blame. If I want to build a chatbot with some semblance of intelligence I have to design for a myriad of possibilities. Surely this is what AI should be doing for me? Chatbots tools It doesn’t have to be this way. There is some amazing that could help. That technology is still stuck in the world of academia, but I want to change that. technology These are the technologies that could make chatbots intelligent: converts user expressions into a form that the computer can understand Semantic parsing chooses a series of actions to achieve a desired goal Automated planning allows computers to respond to people in their own language Natural language generation Semantic parsing for pizza joy “I’d like a pizza with anchovies.” It’s quite clear (to you and me) that I want the anchovies on the pizza. But what about “I want a pizza with fries”? I would probably be surprised if my pizza was delivered with a topping of fries. This particular problem is called . Does the the prepositional phrase “with fries” attach to “pizza” or “want”? prepositional phrase attachment Photo by on Igor Ovsyannykov Unsplash Traditional natural language parsers such as also have to deal with this problem. However, a traditional parser will only tell you the sentence structure. It won’t attempt to describe the meaning of the sentence as a whole. Parsey McParseface A parser, on the other hand, will translate the sentence into a form the computer can understand. In the case of a chatbot, this would normally be a structure that is referred to as an . An intent for “I’d like a pizza with anchovies” might look like this: semantic intent {"intent": "order-items","items": [{"item-name": "pizza","toppings": ["anchovies"]}]} On the other hand, the intent for “I want a pizza with fries” would look like this: {"intent": "order-items","items": [{"item-name": "pizza"},{"item-name": "fries"}]} In the first case, the anchovies are bundled with the pizza in a “toppings” property. In the second case we have two items, pizza and fries. Some chatbot tools, such as , incorporate semantic parsers that can do this type of analysis. However, their sophistication is currently limited. They do not output intents with the kind of deep structure we have described. Dialogflow Semantic parsers that do deep analysis have been around for a while. For example, the Geoquery dataset was described in a by John Zelle and Raymond Mooney in 1996. paper Their system took input queries like this: What are the high points of states surrounding Mississippi? How large is the largest city in Alaska? It translated these to queries that could be evaluated directly on the database, returning the answer to the user. The current state-of-the-art for this dataset is 91% accuracy, by Percy Liang and colleagues in 2011. achieved So if the technology is there, why don’t chatbot tools support this type of more complex analysis? There are probably several reasons: No-one is asking for it. Chatbot designers don’t even know that it’s possible. It doesn’t make sense to build something no-one wants. It adds complexity to the tools. The intents handled by most current systems are nice simple flat structures. If they became trees of arbitrary depth and complexity, it would make everything more difficult. It makes things harder for the chatbot designer, who now has to figure out how to handle these trees. Basically, doing AI is hard. Who knew? Until chatbot designers start demanding more from their tools, and until they are willing to commit serious effort to crafting intelligence, we can expect chatbots to remain stupid. Automated planning to the rescue Photo by on mwangi gatheca Unsplash Let’s say we’re able to overcome some of these barriers and we get some nice complex trees from our users. What are we to do with them? We can view a user request as specifying a goal or desire of the user. It turns out there’s a whole branch of AI dedicated to figuring out how to satisfy these goals automatically: . Wouldn’t it be nice if we didn’t have to tell the chatbot what to do, but it just figured out the best sequence of actions in each situation? Well, that’s the promise of automated planning. automated planning There would still be work to do, of course. We would need to describe the “world” that the chatbot resides in, so that it knows what actions it can take, and what the effect of those actions is. There are formal languages designed to do this. The most commonly used is Planning Domain Definition Language, or for short. PDDL In fact there are a whole bunch of variations of PDDL for different types of problems. One type of problem that may be useful for chatbots is Partially Observable Markov Decision Processes, or for short. These allow for uncertainty not just in the result of actions, but also in the current state of the world. They have been with success to spoken dialogue systems by Steve Young at Cambridge, and his colleagues. POMDPs applied Steve Young et al’s system In this diagram, “SLU” is a spoken language understanding unit, and “NLG” is a natural language generation unit. The design is partly motivated by the challenges specific to speech recognition. Here the output of the spoken language understanding unit may include uncertainty about what the user said. In my opinion, this also applies to chatbots, where there is still uncertainty and ambiguity about the meaning that the user intended. For example, maybe I really did want fries as a topping. This type of ambiguity relates to sentence structure. Ambiguous words can also be a problem. For example the word “run” has 606 meanings in the . Uncertainty from any type of ambiguity can easily be incorporated into a POMDP. Oxford English Dictionary Instead of tracking a single state, in the POMDP approach the system keeps track of a distribution over possible states. The planning system chooses the best action to maximise the expected reward given this distribution over states. This means it is able to act rationally despite uncertainty. (The planning system is depicted as the “dialogue manager” in the above diagram.) So we’ve saved ourselves a bunch of work. Instead of describing how the chatbot should act in every situation, we’ve just described the world, and the chatbot figures out the best thing to do. This should allow our bots to be much more intelligent. But we still need to list out all the things the bot can say. What if we want our bot to be more expressive? What if it could construct sentences of its own accord? That’s where natural language generation comes in. Talking ‘bout my natural language generation Photo by on Khairul Arifin Unsplash This is another huge sub-field of natural language processing. Current systems will generally take a template sentence with perhaps one or two slots that can be filled, and return this to the user. But what if we want to give the user more detailed information? An example from a pollen forecast system described in the Wikipedia on the topic is: article Grass pollen levels for Friday have increased from the moderate to high levels of yesterday with values of around 6 to 7 across most parts of the country. However, in Northern areas, pollen levels will be moderate with values of 4. This is generated automatically from data on the pollen levels in different parts of Scotland. Imagine if you could do the same for your data. You could ask for a summary of your web analytics; you could ask about retention, new users, or landing pages. Your queries could be translated into a set of database queries whose results are then summarised for you. The possibilities are endless. Back to the chatbot future The chatbot market is to grow around 25% a year between now and 2025. But can that expectation be made a reality? expected I talk to very few people that know what a chatbot is, and even fewer that have used one. I only know one person that enjoys using chatbots. The growth of the chatbot market is predicated on the phenomenal growth of messaging platforms. But if these users cannot be converted to chatbot users, the chatbot market will not grow. Personally, I doubt we can convince a majority of people to use chatbots in their current state. The future of chatbot technology is in our hands. Will we demand more from our chatbot tools? Or will we expect users to adapt to our limited technology, and learn not to expect intelligence? It’s up to us.

Three AI technologies that could make chatbots intelligent

The development of the Internet of Things has shaped our modern life, connected thousands of devices, and improved the intelligence and efficiency of everything we use, from houses to urban areas. However, this interconnection has brought some weaknesses, as criminals are hackers are increasingly using IoT devices for large-scale attacks. The emergency of botnets is among the top risks currently faced by IoT ecosystems. These networks of compromised devices can be used as tools to carry out cyber-attacks that can bring severe consequences. The need to understand how IoT botnets work, their effects, and the mechanism to reduce their threat is very important in the current interconnected world. The Development of IoT and Its Security Concerns IoT devices consist of security cameras, smart thermostats, sensors, home appliances, smart TVs, and medical devices. According to the report, it is estimated that over 75 billion IoT devices will be connected globally, a tremendous increase from the millions in use. While the devices make lives easy and convenient for human usage, they bring some set of security issues. The majority of IoT devices are built for functionality rather than security. Some come with weak default passwords, lack automatic security update installations, or operate under minimal processing power, which reduces advanced security features. The rise in these insecure devices has generated a breeding ground for manipulation. Cybercriminals take advantage of these loopholes by using malware to control vulnerable IoT devices and integrate them into botnets. Once in the hands of a hacker, these devices can be used to carry out cyber attacks without user knowledge. What is an IoT Botnet? The botnet is a group of internet-connected devices infected with malware and controlled by one or more bots called the “botmaster.” In IoT, this network comprises various internet-connected devices that have been compromised through vulnerabilities. These include weak passwords or unpatched software. The botmaster can control the compromised device remotely, making it a power tool for cyber-attacks. IoT botnets pose a significant threat because of the large quantity of IoT gadgets, while an individual IoT device may not have as much computing power as a regular computer; their effectiveness increases significantly when they are joined together due to their large numbers. Furthermore, numerous IoT devices run non-top and can go unnoticed when hacked, enabling the botnet to endure for extended periods undetected. How IoT Botnets are Weaponized in Cyber Attacks Cyber attacks of different forms have been carried out via the Internet of Things botnet, with Distributed Denial of Service attacks being the most prevalent. DDOS attacks overload a target’s network or server with heavy traffic, slowing down the service or crashing it so that legitimate users can not have access. IoT botnets can produce enormous volumes of bandwidth due to their large number of infiltrated devices, which makes these attacks more sophisticated, effective, and difficult to defend. For example, the famous Mirai botnet attack in 2016 infected hundreds of IoT devices, such as security cameras and home routers is a clear example of how dangerous this attack can be. One of the largest attacks in history, which targeted services like Netflix, Twitter, and Reddit, was caused by the Mirai botnet. The attack shows how a DDOS attack can disrupt services across different platforms. Aside from DDOS attacks, IoT botnets have been used for a variety of nefarious activities, such as email spam, data theft, click fraud, and cryptocurrency mining. Because these devices are frequently forgotten by the users, hackers then use them to build a massive infrastructure for unlawful activities, all while the device owners are ignorant of malicious activities. Vulnerabilities that Allow IoT Botnets There are different factors that contribute to the vulnerability of IoT devices, making them attractive to target for botnets: Weak Authentication: The majority of IoT devices come with a default username and password that users barely change after purchase. Hackers leverage human ignorance and use automated tools to search the internet for a gadget that still has default credentials, illegally gaining access to them without any restriction. Unpatched Firmware: Many IoT devices lack ways of obtaining automatic security upgrades. As vulnerabilities in devices and software are uncovered, a lot stay unpatched, making the devices vulnerable to attack. Limited Security Feature: Because of the economic constraints or the requirements for efficiency, many IoT devices offer few security measures. Firewalls, encryption, and advanced intrusion detection systems are often unavailable, allowing attackers to hack the devices. Inconsistent Security Standards: IoT manufacturers’ approaches to security vary and there are sometimes no industry standards in place. This gap leads to a variety of vulnerabilities across several devices. Impact of IoT Botnets The increase of IoT botnets poses serious threats to both users and business owners. An IoT botnet attack can have serious effects on an organization ranging from financial loss to reputation damage, and operational downtime. Massive DDOS attacks can shut down websites, online services, and critical infrastructure, with far-reaching consequences for global markets. National Security is under serious threat on a broader scale because more essential infrastructures such as power grids, transportation, systems, military equipment and healthcare networks, linked to IoT could be affected by IoT botnets. The possibility of botnet attacks on this critical infrastructure could cause disruption and risk lives. Defending Against IoT Botnets Fighting against the threat of IoT botnets requires a multi-dimension approach, involving all stakeholders that’s both users and manufacturers. For manufacturers, it’s imperative to design with security consciousness in mind.  This approach includes using strong usernames and passwords, ensuring that automatic firmware is enabled, and using secure coding practices. The usage of industry standards and regulations to checkmate the security features will help in reducing risks and threats. For users and enterprises, protecting IoT devices should be a top priority because everything we do depends on it. The security of the devices should be a must not a choice and the responsibility includes changing default credentials, enabling multifactor authentication (MFA), updating devices constantly, and placing IoT devices on separate networks from critical systems. The adoption of firewalls, intrusion detection systems, and monitoring of traffic for anomalous behavior helps to detect and prevent IoT botnet activity. Conclusion The increase of IoT botnets demonstrated the rise of complexity in cyber threats in the age of connected devices. As more gadgets become available, the probability of cyber-attacks targeting them will grow. Defending the weaponization of IoT cyber attacks needs a collaborative effort with manufacturers, regulators, and users. Without addressing the current weakness in IoT devices, the digital world would continue to be vulnerable to botnets capable of causing massive disruption to lives. We can reduce risks and fully realize the potential of linked devices by ensuring security improvement in IoT development and usage. The development of the Internet of Things has shaped our modern life, connected thousands of devices, and improved the intelligence and efficiency of everything we use, from houses to urban areas. However, this interconnection has brought some weaknesses, as criminals are hackers are increasingly using IoT devices for large-scale attacks. The emergency of botnets is among the top risks currently faced by IoT ecosystems. These networks of compromised devices can be used as tools to carry out cyber-attacks that can bring severe consequences. The need to understand how IoT botnets work, their effects, and the mechanism to reduce their threat is very important in the current interconnected world. The Development of IoT and Its Security Concerns The Development of IoT and Its Security Concerns IoT devices consist of security cameras, smart thermostats, sensors, home appliances, smart TVs, and medical devices. According to the report, it is estimated that over 75 billion IoT devices will be connected globally, a tremendous increase from the millions in use. While the devices make lives easy and convenient for human usage, they bring some set of security issues. The majority of IoT devices are built for functionality rather than security. Some come with weak default passwords, lack automatic security update installations, or operate under minimal processing power, which reduces advanced security features. The rise in these insecure devices has generated a breeding ground for manipulation. Cybercriminals take advantage of these loopholes by using malware to control vulnerable IoT devices and integrate them into botnets. Once in the hands of a hacker, these devices can be used to carry out cyber attacks without user knowledge. What is an IoT Botnet? What is an IoT Botnet? The botnet is a group of internet-connected devices infected with malware and controlled by one or more bots called the “botmaster.” In IoT, this network comprises various internet-connected devices that have been compromised through vulnerabilities. These include weak passwords or unpatched software. The botmaster can control the compromised device remotely, making it a power tool for cyber-attacks. IoT botnets pose a significant threat because of the large quantity of IoT gadgets, while an individual IoT device may not have as much computing power as a regular computer; their effectiveness increases significantly when they are joined together due to their large numbers. Furthermore, numerous IoT devices run non-top and can go unnoticed when hacked, enabling the botnet to endure for extended periods undetected. How IoT Botnets are Weaponized in Cyber Attacks How IoT Botnets are Weaponized in Cyber Attacks Cyber attacks of different forms have been carried out via the Internet of Things botnet, with Distributed Denial of Service attacks being the most prevalent. DDOS attacks overload a target’s network or server with heavy traffic, slowing down the service or crashing it so that legitimate users can not have access. IoT botnets can produce enormous volumes of bandwidth due to their large number of infiltrated devices, which makes these attacks more sophisticated, effective, and difficult to defend. For example, the famous Mirai botnet attack in 2016 infected hundreds of IoT devices, such as security cameras and home routers is a clear example of how dangerous this attack can be. One of the largest attacks in history, which targeted services like Netflix, Twitter, and Reddit, was caused by the Mirai botnet. The attack shows how a DDOS attack can disrupt services across different platforms. Aside from DDOS attacks, IoT botnets have been used for a variety of nefarious activities, such as email spam, data theft, click fraud, and cryptocurrency mining. Because these devices are frequently forgotten by the users, hackers then use them to build a massive infrastructure for unlawful activities, all while the device owners are ignorant of malicious activities. Vulnerabilities that Allow IoT Botnets Vulnerabilities that Allow IoT Botnets There are different factors that contribute to the vulnerability of IoT devices, making them attractive to target for botnets: Weak Authentication: The majority of IoT devices come with a default username and password that users barely change after purchase. Hackers leverage human ignorance and use automated tools to search the internet for a gadget that still has default credentials, illegally gaining access to them without any restriction. Weak Authentication: The majority of IoT devices come with a default username and password that users barely change after purchase. Hackers leverage human ignorance and use automated tools to search the internet for a gadget that still has default credentials, illegally gaining access to them without any restriction. Unpatched Firmware: Many IoT devices lack ways of obtaining automatic security upgrades. As vulnerabilities in devices and software are uncovered, a lot stay unpatched, making the devices vulnerable to attack. Unpatched Firmware: Many IoT devices lack ways of obtaining automatic security upgrades. As vulnerabilities in devices and software are uncovered, a lot stay unpatched, making the devices vulnerable to attack. Limited Security Feature: Because of the economic constraints or the requirements for efficiency, many IoT devices offer few security measures. Firewalls, encryption, and advanced intrusion detection systems are often unavailable, allowing attackers to hack the devices. Limited Security Feature: Because of the economic constraints or the requirements for efficiency, many IoT devices offer few security measures. Firewalls, encryption, and advanced intrusion detection systems are often unavailable, allowing attackers to hack the devices. Inconsistent Security Standards: IoT manufacturers’ approaches to security vary and there are sometimes no industry standards in place. This gap leads to a variety of vulnerabilities across several devices. Inconsistent Security Standards: IoT manufacturers’ approaches to security vary and there are sometimes no industry standards in place. This gap leads to a variety of vulnerabilities across several devices. Impact of IoT Botnets Impact of IoT Botnets The increase of IoT botnets poses serious threats to both users and business owners. An IoT botnet attack can have serious effects on an organization ranging from financial loss to reputation damage, and operational downtime. Massive DDOS attacks can shut down websites, online services, and critical infrastructure, with far-reaching consequences for global markets. National Security is under serious threat on a broader scale because more essential infrastructures such as power grids, transportation, systems, military equipment and healthcare networks, linked to IoT could be affected by IoT botnets. The possibility of botnet attacks on this critical infrastructure could cause disruption and risk lives. Defending Against IoT Botnets Fighting against the threat of IoT botnets requires a multi-dimension approach, involving all stakeholders that’s both users and manufacturers. For manufacturers, it’s imperative to design with security consciousness in mind.  This approach includes using strong usernames and passwords, ensuring that automatic firmware is enabled, and using secure coding practices. The usage of industry standards and regulations to checkmate the security features will help in reducing risks and threats. For users and enterprises, protecting IoT devices should be a top priority because everything we do depends on it. The security of the devices should be a must not a choice and the responsibility includes changing default credentials, enabling multifactor authentication (MFA), updating devices constantly, and placing IoT devices on separate networks from critical systems. The adoption of firewalls, intrusion detection systems, and monitoring of traffic for anomalous behavior helps to detect and prevent IoT botnet activity. Conclusion Conclusion The increase of IoT botnets demonstrated the rise of complexity in cyber threats in the age of connected devices. As more gadgets become available, the probability of cyber-attacks targeting them will grow. Defending the weaponization of IoT cyber attacks needs a collaborative effort with manufacturers, regulators, and users. Without addressing the current weakness in IoT devices, the digital world would continue to be vulnerable to botnets capable of causing massive disruption to lives. We can reduce risks and fully realize the potential of linked devices by ensuring security improvement in IoT development and usage.

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