Using Residential-Proxies to Address Bot Traffic Challenges: A Guide to Identification, Use, and Detection

Have you ever been asked to enter a verification code or complete some other verification step when visiting a website? These measures are usually taken to prevent bot traffic from affecting the website. Bot traffic is generated by automated software rather than real people, which can have a huge impact on the website's analytics data, overall security, and performance. Therefore, many websites use tools such as CAPTCHA to identify and prevent bot traffic from entering. This article will explain what bot traffic is, how to use it legally through residential-proxies, and how to detect malicious bot traffic.

What is Bot Traffic and How Does It Work?

Before understanding robot traffic, we need to understand what human traffic is. Human traffic refers to those interactions with the website generated by real users through the use of web browsers , such as browsing pages, filling out forms, and clicking links, which are all achieved through manual operations.

However, bot traffic is generated by computer programs (i.e., "bots"). Bot traffic does not require manual action from a user, but rather interacts with a website through automated scripts. These scripts can be written to simulate the behavior of a real user, visiting web pages, clicking links, filling out forms, and even performing more complex actions.

Bot traffic is usually generated through the following steps:

1. Creating a bot: Developers write code or scripts that enable a bot to automatically perform a specific task, such as scraping web content or automatically filling out a form.
2. Deploy the robot: Once the robot is created, it is deployed to a server or PC so that it can run automatically, such as using Selenium to automate browser operations.
3. Execute tasks: The robot performs specific tasks on the target website according to the script written. These tasks may be data collection, content crawling, such as simulated data collection or automated form filling.
4. Data collection and interaction: After completing the task, the robot sends the collected data back to the server, or further interacts with the target website, such as initiating more requests, visiting more pages, etc.

Where Does Bot Traffic Come from?

The sources of bot traffic are very wide, which is inseparable from the diversity of bots themselves. Bots can come from personal computers, servers, and even cloud service providers around the world. But bots themselves are not inherently good or bad , they are just tools that people use for various purposes. The difference lies in how the bot is programmed and the intentions of the people who use it . For example, ad fraud bots automatically click on ads to earn a lot of ad revenue, while legitimate advertisers use ad verification bots for detection and verification.

Bot traffic used Legitimately

Legitimate uses of robot traffic usually achieve beneficial purposes while complying with the site's rules and protocols and avoiding excessive load on the server. Here are some examples of legitimate uses:

• Search Engine Crawler

Search engines such as Google and Bing use crawlers to crawl and index web page content so that users can find relevant information through search engines.

• Data Scraping

Some legitimate companies use robots to crawl public data. For example, price comparison websites automatically crawl price information from different e-commerce websites in order to provide comparison services to users.

• Website Monitoring

Use robots to monitor the performance, response time, and availability of their website to ensure it is always performing at its best.

Bot traffic used maliciously

In contrast to ethical use, malicious use of robot traffic often has a negative impact on a website or even causes damage. The goal of malicious robots is usually to make illegal profits or disrupt the normal operations of competitors. The following are some common malicious use scenarios:

• Cyber Attacks

Malicious bots can be used to perform DDoS (distributed denial of service) attacks, sending a large number of requests to a target website in an attempt to overwhelm the server and make the website inaccessible.

• Account hacking

Some bots attempt to crack user accounts using a large number of username and password combinations to gain unauthorized access.

• Content theft

Malicious robots scrape content from other websites and publish it to other platforms without authorization to generate advertising revenue or other benefits.

How to Avoid Being Blocked when Using Robots Legally?

In the process of ethical use of robots, although the goal is a legitimate task (such as data scraping, website monitoring, etc.), you may still encounter the website's anti-robot measures, such as CAPTCHA, IP blocking, rate limiting, etc. To avoid these blocking measures, the following are some common strategies:

Follow robots.txt file

The robots.txt file is a file used by webmasters to instruct search engine crawlers which pages they can and cannot access. Respecting the robots.txt file can reduce the risk of being blocked and ensure that the crawling behavior meets the requirements of the webmaster.

# Example: Checking the robots.txt file
import requests

url = 'https://example.com/robots.txt'
response = requests.get(url)

print(response.text)

Controlling the crawl rate

Too high a crawl rate may trigger the website's anti-bot measures, resulting in IP blocking or request blocking. By setting a reasonable crawl interval and simulating the behavior of human users, the risk of being detected and blocked can be effectively reduced.

import time
import requests

urls = ['https://example.com/page1', 'https://example.com/page2']

for url in urls:
response = requests.get(url)
print(response.status_code)
time.sleep(5) #5 seconds interval to simulate human behavior

Use a residential proxy or rotate IP addresses

Residential-Proxies, such as 911Proxy, route traffic through real home networks. Their IP addresses are often seen as residential addresses of ordinary users, so they are not easily identified as robot traffic by websites. In addition, by rotating different IP addresses, Avoid frequent use of a single IP and reduce the risk of being blocked.

# Example: Making requests using a residential proxy
proxies = {
'http': 'http://user:password@proxy-residential.example.com:port',
'https': 'http://user:password@proxy-residential.example.com:port',
}

response = requests.get('https://example.com', proxies=proxies)
print(response.status_code)

Simulate real user behavior

By using tools like Selenium, you can simulate the behavior of real users in the browser, such as clicks, scrolling, mouse movements, etc. Simulating real user behavior can deceive some anti-bot measures based on behavioral analysis.

from selenium import webdriver
from selenium.webdriver.common.by import By

driver = webdriver.Chrome()
driver.get('https://example.com')

# Simulate user scrolling the page
driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")

# Simulate click
button = driver.find_element(By.ID, 'some-button')
button.click()

driver.quit()

Avoid triggering CAPTCHA

CAPTCHA is one of the most common anti-bot measures and often blocks access to automated tools. While bypassing CAPTCHAs directly is unethical and potentially illegal, it is possible to avoid triggering CAPTCHAs by using reasonable crawling rates, using Residential-Proxies, etc. For specific operations , please refer to my other blog to bypass the verification code.

Use request headers and cookies to simulate normal browsing

By setting reasonable request headers (such as User-Agent, Referer, etc.) and maintaining session cookies, real browser requests can be better simulated, thereby reducing the possibility of being intercepted.

headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
'Referer': 'https://example.com',
}

cookies = {
'session': 'your-session-cookie-value'
}

response = requests.get('https://example.com', headers=headers, cookies=cookies)
print(response.text)

Randomize request pattern

By randomizing the crawling time interval, request order, and using different browser configurations (such as User-Agent), the risk of being detected as a robot can be effectively reduced.

import random
import time

urls = ['https://example.com/page1', 'https://example.com/page2']

for url in urls:
response = requests.get(url)
print(response.status_code)
time.sleep(random.uniform(3, 10)) # Random interval of 3 to 10 seconds

How to Detect Malicious Bot Traffic?

Detecting and identifying malicious robot traffic is critical to protecting website security and maintaining normal operation. Malicious robot traffic often exhibits abnormal behavior patterns and may pose a threat to the website. The following are several common detection methods to identify malicious robot traffic:

• Analyze traffic data

By analyzing website traffic data, administrators can find some abnormal patterns that may be signs of robot traffic. For example, if a certain IP address initiates a large number of requests in a very short period of time, or the traffic of certain access paths increases abnormally, these may be manifestations of robot traffic.

• Use behavioral analysis tools

Behavioral analysis tools can help administrators identify abnormal user behaviors, such as excessively fast click speeds, unreasonable page dwell time, etc. By analyzing these behaviors, administrators can identify possible robot traffic.

• IP address and geolocation screening

Sometimes, bot traffic is concentrated in certain IP addresses or geographic locations. If your site is receiving traffic from unusual locations, or if those locations send a large number of requests in a short period of time, then that traffic is likely coming from bots.

• Introduce CAPTCHAs and other verification measures

Introducing verification codes or other forms of verification measures is an effective way to block robot traffic. Although this may have a certain impact on the user experience, by setting reasonable trigger conditions, the impact can be minimized while ensuring security.

Summarize

In the modern web environment, robot traffic has become a major challenge faced by major websites. Although robot traffic can sometimes be used for legitimate and beneficial purposes, malicious robot traffic can pose a serious threat to the security and performance of a website. To meet this challenge, website administrators need to master the methods of identifying and blocking robot traffic. For those users who need to bypass website blocking measures, using residential proxy services such as 911Proxy is undoubtedly an effective solution. In the end, both website administrators and ordinary users need to remain vigilant at all times and use the appropriate tools and strategies to deal with the challenges posed by robot traffic.

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