Rise of the Machines: A Practical Approach to Bot Management

BOT-MANAGEMENT

Bot management refers to the practice of managing and controlling the activities of automated programs, commonly known as bots, on the internet. Bots can serve various purposes, from benign tasks like web indexing by search engines to more malicious activities such as spamming, scraping content, launching DDoS attacks, or engaging in fraud.

Firstly, It’s important for organizations to implement measures to detect and mitigate bad bot activities while allowing legitimate good bots to operate effectively. This involves deploying bot management solutions, implementing security protocols, and staying vigilant against emerging threats in the ever-evolving landscape of bot-based attacks.

1-Good Bots:

Good bots are designed for constructive purposes, such as enhancing user experience, improving efficiency, or providing valuable services.

They typically adhere to ethical guidelines and legal regulations, and their activities contribute positively to the online ecosystem.

• Search engine bots: Also known as web crawlers or spiders : These bots “crawl,” or review, content on almost every website on the Internet, and then index that content so that it can show up in search engine results for relevant user searches. They’re operated by search engines like Google, Bing, or Yandex.
• Copyright bots: Bots that crawl platforms or websites looking for content that may violate copyright law. These bots can be operated by any person or company who owns copyrighted material. Copyright bots can look for duplicated text, music, images, or even videos.
• Site monitoring bots: These bots monitor website metrics — for example, monitoring for backlinks or system outages — and can alert users of major changes or downtime. .
• Commercial bots: Bots operated by commercial companies that crawl the Internet for information. These bots may be operated by market research companies monitoring news reports or customer reviews, ad networks optimizing the places where they display ads, or SEO agencies that crawl clients’ websites.
• Feed bots: These bots crawl the Internet looking for newsworthy content to add to a platform’s news feed. Content aggregator sites or social media networks may operate these bots.
• Chatbots: Chatbots imitate human conversation by answering users with preprogrammed responses. Some chatbots are complex enough to carry on lengthy conversations.
• Personal assistant bots: : Although these programs are much more advanced than the typical bot, they are bots nonetheless: computer programs that browse the web for data.

2-Bad Bots:

Bad bots are programmed with malicious intent to disrupt, exploit, or deceive systems, users, or organizations.

• Bad bots often violate terms of service, infringe upon privacy rights, and undermine the security and integrity of digital platforms.
• They can be deployed by cybercriminals, competitors engaging in unethical practices, or individuals seeking to gain unfair advantages.

Bot management solutions currently follow three approaches namely static, challenge-based, and behavioral to identify and stop bot-driven attacks. Depending on the level of threat they face, digital businesses use one or a combination of these approaches.

1-Static Approach

With a static approach, you use a predetermined range of rules that block traffic. This could include blacklisting suspicious IP addresses or traffic that falls outside of acceptable parameters, such as the number of requests made during a session. You can also block traffic from old browsers, which may be used to launch bots because they have outdated security settings.

1.1 Ip Address, Reputation (AllowList-BlockList)

How can you accurately score the risk from a given bot and its requests? The regularly updated list of malicious IP addresses in bot management solutions makes doing so much more straightforward. IP reputation analysis also lets you know if a bot originates from a risky domain with a history of being involved in cyberattacks.

1.2 Ip Location

The system matches the ISP and Organization name against known search engines and cloud providers. Once the lookup is done and decision is taken, the client is marked either as Bot or Undetermined. Confidence level is also assigned.

1.3 User-Agent

For bot management, that’s basically how allowlists work. An allowlist is a list of bots that are allowed to access a web property. Typically this works via something called the “user agent,” the bot’s IP address , or a combination of the two. A user agent is a string of text that identifies the type of user (or bot) to a web server.

1.4 Robots.txt File To Set Up a Honeypot

Good bots will read the robots.txt file and avoid that webpage; some bad bots will crawl the webpage. By tracking the IP address of the bots that access the honeypot, bad bots can be identified and blocked.

if an administrator wants a certain page to show up in Google search results but not Bing searches, they could include two sets of commands in the robots.txt file: one set preceded by “User-agent: Bingbot” and one set preceded by “User-agent: Googlebot”.

One important thing to note is that all subdomains need their own robots.txt file.

In a robots.txt file, website administrators are able to provide specific instructions for specific bots by writing different instructions for bot user agents. For instance, Googlebot / Googlebot-Image (for images) / Googlebot-News (for news) / Googlebot-Video (for video) / Bingbot / MSNBot-Media (for images and video) / Baiduspider..

Moreover a well-constructed robots.txt file keeps a website optimized for SEO and keeps good bot activity under control.

1.5 Rate Limiting

Rate Limiting and request throttling are techniques used to control the rate at which users can access a website or API. Rate limiting restricts the number of requests that a user can make within a given time frame, while request throttling slows down the rate at which requests are processed. These techniques can be set up to restrict the number of requests from a single IP address within a given time frame. If an IP address exceeds this limit, any additional requests from that IP address will be blocked until the next minute.

1.6 Bot signature files and profiles

A bot management platform maintains an active, up-to-date list of known bots and their signatures, which can be added to bot profiles for more reliable bot protection. By drawing upon this information, bot management solutions can then identify anomalous bot activity on the network and block it before it accesses and attacks important applications and/or APIs.

2-Challenge-Based Approach

The challenge-based approach can make it hard for a robot to get to a site by forcing it to do something difficult for a robot such as read, do math, or recognize objects within images. The challenge-based approach is the driving principle behind Captcha, which prescribes tasks that are easy for humans but very difficult for robots.

2.1 JavaScript challenges (which determines whether or not a traditional web browser is being used)

You can set up JavaScript to send an alert if there is bot activity. When the JavaScript, embedded in your site, detects a bot, it can signal you to the intrusion.

2.2 Captcha

The user has to do something that is very difficult for a bot, such as read text or indicate where certain types of objects are located. This can prevent many different kinds of bots from attacking your site.

3-Behavioral Approach

The behavioral approach involves identifying acceptable, harmless behavior and then flagging anomalous behavior that violates the acceptable parameters. Behavioral tactics also include using human traits, such as biometric activity, because it is very hard for a bot to present accurate biometric data.

3.1 Artificial Intelligence (AI): This field focuses on creating intelligent machines capable of mimicking human cognitive functions such as learning, problem-solving, and decision-making.

3.2 Machine Learning: A subset of AI, machine learning involves developing algorithms that enable computers to learn from and make predictions or decisions based on data without explicit programming.

3.3 Behavioral Analysis: This involves the study of patterns of behavior in individuals or groups, often using data-driven techniques to identify trends, anomalies, or potential risks.

3.4 Data Analytics: The process of analyzing and interpreting large datasets to uncover meaningful insights, patterns, and trends that can inform decision-making.

3.5 Behavioral Biometrics Device Fingerprinting: With bot management, you can deploy multiple forms of behavior-based bot detection and control, including device fingerprinting. A device fingerprint identifies a client as a unique entity, based on attributes such as its IP address, screen resolution, browser attributes, HTTP request headers, and installed fonts. This fingerprint in turn can be used to block malicious yet legitimate-seeming bad bots as necessary.

Parameters To Detect Bot Traffic Hitting a Website

1.Transactions per second (TPS): Monitor the rate of transactions occurring on the website. A sudden spike in TPS may indicate bot activity.

2. Bot traps: Implement traps designed to catch bots, such as hidden links or fields in forms. Legitimate users won’t interact with these, but bots may trigger them.

3. Rate limiting and traffic controls: Set limits on the number of requests allowed from a single IP address within a certain time frame to prevent bot-driven overload.

4. Allow list and block list deployment: Maintain lists of trusted and suspicious IP addresses, user agents, or other identifiers to selectively allow or block traffic.

5. Reporting and follow-up: Regularly review reports and logs to identify patterns or anomalies in traffic, and take appropriate action to mitigate bot activity.

6. Traffic trends: Analyze trends in website traffic over time to identify abnormal patterns that may indicate bot activity, such as sudden spikes or unusual fluctuations.

7. Bounce rate: Monitor the bounce rate, which measures the percentage of visitors who leave the site after viewing only one page. High bounce rates may indicate bot-generated traffic.

8. Traffic sources: Identify the sources of incoming traffic to distinguish between legitimate sources (e.g., search engines, social media) and suspicious sources (e.g., known bot networks).

9. Server performance: Monitor server performance metrics such as CPU usage, memory consumption, and network bandwidth to detect and respond to unusual resource usage caused by bot traffic.

10. Suspicious IPs: Flag and investigate IP addresses that exhibit suspicious behavior, such as generating excessive requests or accessing restricted areas of the website.

11. Language sources: Analyze the language used in requests to identify patterns associated with bot activity, such as non-human language patterns or unusual combinations of languages.

How Can Bad Bots Harm Your Business?

Negatively affects SEO — Web-scraping bots can copy and extract copyrighted or trademarked data from websites and reuse it — often for competitive purposes — on other websites. Because there are two versions of the content online, this can greatly diminish your site’s search authority.

Deteriorates customer trust — Bots can fill your customers’ inboxes with unwanted email containing malicious links, write fake product reviews, create fake social media accounts to write false or biased content, inflate views or follower counts, write provocative comments online to stir up controversy, rig votes, and more. These types of activities can frustrate customers, drive them away from your site, and ruin your reputation.

Skews analytics — Attackers can use botnets to launch DDoS attacks that make an application or network unavailable. which can affect traffic metrics. In addition, bots can create non-existent leads by creating and then abandoning online shopping carts on an e-commerce site. The poor metrics that result can lead to poor marketing decisions later.

Destroys advertising ROI — Bots can commit click fraud by automatically clicking on an ad. This skews data reported to advertisers and costs companies a lot of money because they end up paying for non-human clicks. Even worse, those companies get no revenue from fake “shoppers.” Click fraud can also be used by companies to deliberately drive up the advertising costs of their competitors.

Loss of revenue — Malicious bots can negatively impact the bottom line, whether it be from an unresponsive or flagged website, visitors redirected to a competitor, sales personnel chasing false opportunities or leads, paying more for clicked ads, or simply making poor business decisions based on bad data.