Web scraping refers to the automated collection of data and information, often for both legal and illegal purposes, from one website to another. Almost half (49.6%) of all web traffic globally comes from bots. However, a good portion of this traffic goes towards scraping data via automated means.
Organizations such as DataDome offer protection against fraudulent activities, which is the primary focus of these services.
Let’s explore more about these services and, most importantly, how to stop them!
KEY TAKEAWAYS
- Bot-driven crawling or automated bots perform a variety of functions on behalf of legitimate users.
- DataDome is one of the many bot management services available, which works on dealing with sensitive information and assets.
- Identifying and preventing malicious intent associated with bot use will continue to create challenges in managing the malicious actions of these automated agents.
- As web scraping bots change their behavior, DataDome has continued to adjust to keep pace with these changes and developments.
Web scraping is generally powered by software tools or bots, or sometimes headless browsers, that crawl web pages and gather important (and sometimes non-essential) information.
Often, they follow pre-written collections of commands or dialogue flows that instruct automated software to perform specific tasks. The process of web scraping is extremely complicated, making it virtually impossible to block or prevent bots from scraping data on the internet manually.
Consequently, companies such as DataDome have emerged as leaders in the field of bot management. Their artificial intelligence uses 5 trillion data points daily to identify the highest level of sophisticated attacks, while also providing fine-grained access control for legitimate bots.
Instead of the superficial bots or automated scraping of the early days of web scraping, modern, more sophisticated techniques use AI-driven tools and advanced machine learning algorithms that easily beat traditional web protection systems. Many bots can currently even ignore the once highly suggested robots.txt entirely, by design or by spoofing known bots.
The evolution makes the task of detecting fair users and malicious bots so difficult.
The basis of web scraping is programming automated bots, typically run by software, to mimic user web interactions.
The issue for websites is that most, if not all, depend on user engagement metrics and interactions to shape marketing campaigns, content optimization, online visibility, and the overall online presence.
Bot activity, specifically malicious bot activity, completely interferes with this by generating undesirable traffic that can risk security and engagement metrics.
That said, you can usually tell web scrapers from legitimate web users, either because they’re self-identifying (the good ones) or because they observe an almost scripted movement that goes something like this:
Use web scraping for legitimate purposes, such as in multiple industries, especially marketing.
Some of the legitimate use cases include the following:
And the list could move on. These legitimate reasons for web scraping are steered by verified, secure web scraping tools. They cause liability or security risks and are authorized for web scraping.
Most of what’s online related to web scraping is the malicious side of it. Organizations and attackers abuse software and technology with the intent of fraud, data theft, or causing harm.
Here are a few of the most common forms of malicious web scraping:
Understanding the malicious kinds of intent for web scraping can help businesses, developers, and security teams tackle the issue.
Preventing malicious web scraping and allowing legitimate bots can be difficult, but there are multiple techniques and industry-leading assistance businesses can use to create a combination of best practices.
IP blocking limits user access. It analyzes users’ IP addresses and can actually block unknown IPs, with unknown IPs typically being malicious. That said, there are restrictions, and scrapers can now easily turn IP addresses and use proxy servers or VPNs.
CAPTCHA issues are so common that we have all used them as web users. However annoying they can be, the puzzles or tasks we conclude are actually designed to distinguish between humans and bots. Adaptive CAPTCHA adjusts its predicament based on user behavior, so it is effective against scrapers.
Still, sophisticated writings can bypass even adaptive CAPTCHA.
Firewalls such as Web Application Firewalls (WAF) filter traffic and block requests showing scraping behavior. They analyze various ways to show a pattern of behavior, for example, from the same IP accessing several web pages and suddenly experiencing an influx of transactions.
Firewalls should form part of a multi-tiered defense system, as they also perform well in conjunction with both CAPTCHA and IP blocking features.
Unlike basic defenses that depend on static rules, DataDome’s service operates in real time, analyzing vast volumes of data to differentiate between legitimate users and malicious bots with a high degree of accuracy. Its platform considers trillions of signals daily, allowing it to identify even the most unpretentious patterns associated with automated scraping tools.
One of the key stability features of DataDome’s solution is its ability to deliver granular control over traffic. This means industries don’t have to take a blunt “block everything suspicious” process. Instead, they can:
This multilayer approach allows valid traffic to flow freely, while malicious web scrapers are prevented from causing any damage or defrauding a server by using the server’s resources for processing and storage, like how humans use them.
The other unique aspect is that DataDome has real-time reactivity. By rotating their IP addresses, employing artificial intelligence (AI), or using methods designed to mimic human behavior.
Furthermore, DataDome’s machine learning models are developed and refined using real-time network traffic designs, which allows for ongoing improvement in its ability to protect each entity as compared to relying solely on its earlier methodologies.
There are many different types of web scraping, but all share the goal of extracting data from the internet, often without authorization. Because of the continued evolution in both the sophistication of bot and web scraping software and technology, managing malicious intent requires a multi-layer and proactive approach.
It is the process of automated data theft/collection from websites.
It works by imitating human browsing behavior, where a script sends requests to a server, receives page content, and parses it to extract detailed information
Public data scraping is generally legal, but scraping behind logins, stealing personal data (GDPR), or causing service disruptions is considered illegal.
