Is web Scraping Legal or Illegal ?

Before getting to the legal aspects, first we need to know what it is and how and where it is used.

What is web scraping?

Web scraping is a technique that is used to collect content in the form of data from the internet, and usually saved in a local file so that it can be manipulated and analyzed as per needed, web scraping can be used for various purposes such as extracting product information, customer reviews, news articles, social media posts and so on. It requires two parts, a crawler and a scraper. Web Crawler is an algorithm that is used to browse the web to search for particular data that is required, by following the links across the internet, while scraper is a tool that extracts the data from website’s HTML code, and outputs that extracted data in a structured format as well. It can be an easy and challenging task at the same time, some challenges that can be faced by scrapers listed here.

Challenges of Web Scraping

Anti-scraping mechanisms :

Several websites employ anti-scraping measures to prevent web scraping bots, including CAPTCHAs, IP blocking, honeypot traps, dynamic content, and some even prevent scraping by implementation of Login Requirements. Web scrapers need to use various techniques to bypass these obstacles or anti-scraping mechanisms. The main techniques to bypass are like,

• To use a proxy
• To use a captha solver
• To use a headless browser

Large Proxy infrastructures :

Web Scrapers need to use a proxy to hide their real IP address to avoid being detected or blocked by the website. However managing a large number of proxies can be costly and complicated at the same time, web scrapers need to choose reliable and ethical proxy providers that can offer high quality diverse IP addresses to them.

Geo-Specific Scraping :

Some websites do not allow access from specific certain regions or display different content based on the user’s location. Web scrapers need to use a geo-targeted proxy or Virtual Proxy Network (VPN) to access those websites and get the desired data from them.

Website Structure Changes :

Websites often change their content and layout as well to improve user experience or to add new features. This can affect the scraper’s ability to extract data from html code. Web scrapers need to monitor these changes and need to update their scraping abilities according to them.

Large Scale Scraping or Distributed Scraping :

When web scrapers require large amounts of data or need to extract data from multiple websites, they need to use distributed systems that can handle concurrency, scalability, fault tolerance and load balancing techniques as well. Scrapers also need to respect the website’s crawler rate limitations in order to avoid overloading to the required website’s servers.

Quality of the data :

The output data can result in incomplete, inaccurate, outdated or even irrelevant data that can be extracted if the scraping is not done properly. Web scrapers need to ensure that the extracted data is from reliable sources, and they have to validate and clean up data and remove the irrelevant part before storing that output data in a structured format to avoid inconvenience in future.

Tools used in web scraping :

There are many tools that are used to scrap the web based data depending on scrapers preference, needs and skill sets. Some most used scraping tools are:

1. Piloterr : this is an API that handles proxies, browsers and CAPTCHA for the scrapers. This API can be used with any programming language or framework as per needed.
2. Scrap Box : this is a desktop software specially designed for web scrapers. This allows you to scrape websites by providing various tools like keyword scraper, link extractor, email scraping etc.
3. Screaming Frog : this desktop software crawls websites and audits them for added benefits of SEO purposes. You can use it to extract meta-data like titles, meta tags, images, hyperlinks and others.
4. Scrapy : it is an open-source framework to scrape data from the web and crawl using python language. This tool is used to create spiders that can scrape data from multiple websites at the same time.
5. Pyspider : it is also an open-source tool or framework for python with added benefits of a web-based UI which allows you to write scripts, monitor tasks and even debug errors as well.
6. Beautiful Soup : it is also an open-source library for scrapers that pursues HTML and XML documents in python, this can be used to extract data from websites using methods like CSS selectors or regular expressions as per required.
7. Diffbot : Diffbot is an API that uses computer vision and natural language processing to extract structured data from any kind of website, this tool can be used with all kinds of programming languages or frameworks.
8. Common Crawl : it is also an open-source project that crawls the large-scale web data and gives you raw HTML data that is available to access and analyses according to requirements of scrapers. It can be used to obtain data from millions of websites without the hectic process of scraping them yourself.

Importance of Web Scraping

Web Scraping allows you to access and analyze large amounts of data from various websites, the reasons that make this process important are:

Automation

Web scrapers can automate the process of extraction of data from different websites, which help them to save some time and resources. These tools and APIs can collect large amounts of data with just one click.

Cost-Effectiveness

Web Scraping can reduce the cost of data acquisition by eliminating the need for manual data entry or even hiring a workforce that can be too costly for some organizations. You can use web scraping to obtain data that is otherwise, either not available for the public or is too costly to access that data.

Easy Implementation

Web Scraping can be easily implemented by using various tools and techniques that depend solely on your preference and skill sets. You can use web scraping software, frameworks, libraries or APIS to extract web data using any programming language or framework of your choice.

Low Maintenance

If you are using a reliable scraping tool or service, that will help you to minimize the efforts of maintenance required for data mining. you can monitor website changes, handle errors and update your scrapers accordingly.

Speed

Web Scraping can extract data from websites at a fast rate especially if you are using a distributed system that can handle concurrency and scalability. You can use it to obtain large chunks of data with bare minimum time needed.

Data Accuracy

Web Scraping tools extract data directly from the source website. This ensures data accuracy, you can use web scraping techniques such as regular expressions or CSS selectors to validate data and clean it before storing in a structured format.

Effective Management of Data

Web Scraping can be helpful to effectively manage data by allowing you to export in various formats like CSV, JSON, XML or whatever you want. You can also use it to integrate data with other sources, databases or APIs as well.

Innovation

Web Scraping can enable innovation by allowing you to create new products and services based on the data you mine. You can use it to obtain insights of your local market, customers and competitor information, look for local trends and watch the market closely.

Legal aspects of web scraping

In simple words, web scraping is not illegal itself. Publicly available data is available for the mass audience to use it for their use. But there are some legal issues that can be faced by web scrapers depending on how and what they scrape or mine data from the web. Some of the legal issues faced by scrapers are :

Breach of Contract

Some websites issue terms of services to prohibit web scraping, and even  impose certain limitations on the use of their data. If you violate those terms and conditions, they can sue you and charge you for breach of the contract.

Copyright Infringement

Some websites copyright their content and protect it by law. If you try to scrape that content and data without permission, then you may face copyright infringement due to use of that data.

Computer Fraud and Abuse Act (CFAA)

The US Federal government imposed this law to prohibit unauthorized access to computers or networks. If you scrape data bypassing the security measures like CAPTCHA, IP blocking, Login Requirements and others, you may violate CFAA. This act is imposed anywhere in the US.

Trade Secrets

Some websites have confidential or proprietary forms of data or information that gives them a competitive advantage for their business. If you happen to scrape that data and disclose it to others, you may be liable for trade secret misappropriation which is unethical use of web scraping.

Data Protection Regulations

Some websites have personal or sensitive data that require protection regulations. In the European Union, these regulations are called GDPR and in California, these are named as CCPA. Un consented use of that data may result in violations of these regulations so you need to be aware of that.

How to avoid legal issues while scraping the web?

To avoid inconvenience and legal issues while scraping web, the scrapers need to follow the best practices listed here:

• Respect the website’s ToS and robot.txt file.
• Obtain permission from the source website owners (if possible).
• Use the scraping tools or services that are reliable and don’t use unethical means for data mining.
• Limit the scraping frequency to avoid overloading issues for the website server and follow the browsing limits or traffic limits of the website.
• Do not scrape personal or sensitive data without consent.
• Do not use scraped data for illegal purposes.
• Regulations and authorities concerned with web scraping.

CFAA

Computer fraud and Abuse Act or CFAA is a US federal law that prohibits unauthorized access to computers or networks. This act started back in 1986 as an amendment to existing computer fraud law which had been included in the comprehensive crime control act of 1984. CFAA covers various kinds of cyber and computer-based crimes and offenses like obtaining national security information, accessing a computer to obtain information, trespassing in a government computer, accessing a computer to defraud or obtain value, internationally or recklessly damaging by knowledge transmission, trafficking in passwords or similar things like this. CFAA also provides precautions and remedies for victims that faced some kind of computer or cyber crimes as well. This law has been criticized widely for being vague, broad and outdated, while it has been amended several times over years to address new forms of cybercrimes and implementations of new technology like AI.

GDPR

GDPR is an EU law, which regulates the collection of personal data of an individual in the EU or EEA, it regulates the collection of data, processing and protection of that data by organizations inside or outside the EU. GDPR gives more control to individuals over their personal data, and ensures that their rights are respected by organizations and penalties on organizations that fail to comply or violate their rules as well. Here's a list of measures of GDPR regarding the regulation of web scraping:

• Lawful basis : web scraping must have a valid legal reason for collecting and using personal data, GDPR provides six possible lawful bases which are consent, contract, legal obligation, vital interest, public interest and legitimate interest. Web scrapers need to determine any one of these bases that is applied for their activity and document it accordingly.
• Transparency : Web scraping needs to be transparent and inform individuals about how their personal data is collected and where it will be used. GDPR requires web scrapers to provide clear and concise information about their identity, purpose of mining data, legal basis, recipients, retention period, individual rights etc.
• Data minimization : web scrapers must limit the collection and use of personal data that is relevant and necessary for specific purposes only. GDPR requires web scrapers to limit their data extraction to what is adequate and proportionate to the objectives.
• Data Quality : Web scraping must ensure that personal data is accurate and always up-to-date as well. GDPR requires web scrapers to correct and delete any inaccurate data without any delay.
• Data Security : Web scraping must protect personal data from unauthorized access or loss of personal data. GDPR requires the implementation of appropriate technical and organizational measures to ensure a level of security that matches the risks involved in processing of personal data.
• Data protection impact assessment (DPIA) : Web scrapers need to conduct a DPIA if involved high-risk in processing of personal data. DPIA is a systematic process that evaluates the impact of processing individual rights and freedom, and even identifies measures to mitigate these risks as well.

GDPA

General Data Protection Act (GDPA) is a Brazilian law that regulates personal data of individuals in Brazil, it regulates how this data is collected and processed, and even protects data inside and outside Brazil similar to GDPR.

Terms of Services

It is a legal agreement between website owners and users that define terms and conditions to use their data or information on the web. ToS for web scraping refer to the clauses or sanctions that regulate and prohibit web scraping activities or limit them for the website.

These terms and conditions are important as they can affect the legality and ethics of scraping the information from the web. Scrapers should respect the terms of service of the website they are scraping, in order to avoid violations of the ethics and rules of the website, otherwise, they may face legal actions from the website owners as well.

Terms of service of some major groups are:

• Ryanair ToS explicitly prohibits web scraping for commercial purposes unless there is a written license agreement with Ryanair itself.
• Linkedin’s ToS states that the users are not allowed to scrape data or copy profile information of others through any means like crawlers, browser plugins, addons or any other technology.
• Amazon’s ToS states that their users are not allowed or permitted to use any robot, spider, scraper or other automated means to access their services for any purpose without a written permission by Amazon Express.
• Facebook’s ToS states that their users are not allowed to collect or access data using any kind of automated means like harvesting, bots, robots, spiders or scrapers without prior permission. Users are thus not allowed to use data obtained from facebook for any kind of unauthorized purposes as well.
• Twitter’s ToS states that their users are not allowed to access or search twitter services by any means other than publicly supported interface (their own web interface). Their users are also not allowed to use twitter services for unlawful or unethical purposes as well.
• Youtube’s ToS states that users are not allowed to access or use their services through any technology or means other than those provided by youtube itself. Their services cannot be used for any illegal activities or breach of their guidelines.
• SnapChat’s ToS states that their users are not allowed to create accounts or access their services through unauthorized means like bots etc. users are thus not allowed to use their services for any unlawful purposes or in conflict with their terms and conditions.
• Instagram’s ToS states that users are not allowed to collect information from Instagram using automated scripts, and they cannot use the services of Instagram for any kind of illegal activities or in violation of their rules.  

Ethical Uses of web scraping

Web scraping is not considered illegal when done ethically. It means when you scrape data that is publicly available, not protected or restricted by any kind of laws and regulations, and is used for beneficial and legitimate purposes only. Some ethical use case scenarios of web scraping are:

• Scraping data for academic research and educational purposes.
• Scraping for market analysis or business intelligence.
• Scraping for content aggregation and news curation.
• Scraping for SEO or web analytics.

Prohibited or Illegal Use of Web Scraping

Web Scraping gets illegal when used for unethical purposes, like publishing the collected data to harm someone, or trying to mine confidential or not-so publicly available data that is prohibited for a reason. Some examples of illegal use cases of web scraping are:

• Scraping personal data like names, emails, phone numbers or contact information without consent or compliance with data protection regulations, GDPR or CCPA.
• Scraping copyrighted content like Books, Images, Articles, Music etc. without permission from the owner for fair use.
• Scraping confidential or proprietary information like trade secrets, business strategy, customers list or so on, without the authorization from the relevant business group.
• Scraping data by bypassing security measures like CAPTCHA, IP blocking, Login and others, or violating CFAA and other laws.
• Scraping data by violating Terms of Service or robot.txt file that prohibits or limits web scraping.
• Scraping data by overloading the web server or disrupting functionality of a website.
• Scraping data for spamming, phishing, fraudulent activities, identity theft and cyberattacks etc.

Case studies

Some is a list of most cases of misuse of web scraping reported in recent times, for which companies sued and have taken legal actions :

Meta Inc. vs BrandTotal LTD and Unimania Inc.

This case involved two companies that used browser extensions to scrape data from meta platforms including Facebook, Instagram, Twitter, Youtube, Linkedin and Amazon. Those two companies were doing it without the permissions of these platforms, so Meta sued them for violation of their terms of services and other laws regarding data access. This case was settled in 2022 with a permanent injunction and a significant financial payment or called penalty from defendant groups.

HiQ labs vs Linkedin

This case involved HiQ labs, a company that scraped data from public profiles of Linked in users to provide analytic services to employers. Linkedin sued them for violation Terms of Service and CFAA laws. This case ended in favor of HiQ Labs by Ninth Circuit court of appeal back in 2019, with a verdict that scraping publicly available data is not illegal under CFAA act.

Ryanair Limited vs PR Aviation case

This case involved a company that scraped flight information from Ryanair’s website and provided price comparisons for airline ticketing. Ryanair sued them for violating their terms of service and database protection rights, the case was ended in favor of Ryanair by EU Court of Justice in 2015, which stated that website owners can contractually. limit web scraping by third parties.

Conclusion

Web Scraping is legal if you scrape publicly available data from the internet. In order to avoid any legal issues you need to avoid scraping personal data that is protected by some kind of law or has some regulations on the use of it. You also need to respect the terms of service and robots/txt file and try not to overload website servers or bypass the security measures. Web scraping can be illegal if you use the scraped data for harmful or illegal purposes, or if you violate the rights that the owner has copyrighted for their content.