Website Screen Scraping

Website Screen Scraping

Web Scraper – The #1 web scraping extension

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More than
400, 000 users are proud of using our solutions!
Point and click
interface
Our goal is to make web data extraction as simple as possible.
Configure scraper by simply pointing and clicking on elements.
No coding required.
Extract data from dynamic
web sites
Web Scraper can extract data from sites with multiple levels of navigation. It can navigate a
website on all levels.
Categories and subcategories
Pagination
Product pages
Built for the modern web
Websites today are built on top of JavaScript frameworks that make user interface easier to use but
are less accessible to scrapers. Web Scraper solves this by:
Full JavaScript execution
Waiting for Ajax requests
Pagination handlers
Page scroll down
Modular selector system
Web Scraper allows you to build Site Maps from different types of selectors.
This system makes it possible to tailor data extraction to different site structures.
Export data in CSV, XLSX and JSON
formats
Build scrapers, scrape sites and export data in CSV format directly from your browser.
Use Web Scraper Cloud to export data in CSV, XLSX and JSON formats, access it via API, webhooks or
get it exported via Dropbox.
Diego Kremer
Simply AMAZING. Was thinking about coding myself a simple scraper for a project
and then found this super easy to use and very powerful scraper. Worked
perfectly with all the websites I tried on. Saves a lot of time. Thanks for
that!
Carlos Figueroa
Powerful tool that beats the others out there. Has a learning curve to it but
once you conquer that the sky’s the limit. Definitely a tool worth making a
donation on and supporting for continued development. Way to go for the
authoring crew behind this tool.
Jonathan H
This is fantastic! I’m saving hours, possibly days. I was trying to scrap and old
site, badly made, no proper divs or markup.
Using the WebScraper magic, it somehow “knew” the pattern after I selected 2
elements. Amazing.
Yes, it’s a learning curve and you HAVE to watch the video and read the docs.
Don’t rate it down just because you can’t be bothered to learn it. If you put
the effort in, this will save your butt one day!
Is Web Scraping Illegal? Depends on What the Meaning of the Word Is

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Is Web Scraping Illegal? Depends on What the Meaning of the Word Is

Depending on who you ask, web scraping can be loved or hated.
Web scraping has existed for a long time and, in its good form, it’s a key underpinning of the internet. “Good bots” enable, for example, search engines to index web content, price comparison services to save consumers money, and market researchers to gauge sentiment on social media.
“Bad bots, ” however, fetch content from a website with the intent of using it for purposes outside the site owner’s control. Bad bots make up 20 percent of all web traffic and are used to conduct a variety of harmful activities, such as denial of service attacks, competitive data mining, online fraud, account hijacking, data theft, stealing of intellectual property, unauthorized vulnerability scans, spam and digital ad fraud.
So, is it Illegal to Scrape a Website?
So is it legal or illegal? Web scraping and crawling aren’t illegal by themselves. After all, you could scrape or crawl your own website, without a hitch.
Startups love it because it’s a cheap and powerful way to gather data without the need for partnerships. Big companies use web scrapers for their own gain but also don’t want others to use bots against them.
The general opinion on the matter does not seem to matter anymore because in the past 12 months it has become very clear that the federal court system is cracking down more than ever.
Let’s take a look back. Web scraping started in a legal grey area where the use of bots to scrape a website was simply a nuisance. Not much could be done about the practice until in 2000 eBay filed a preliminary injunction against Bidder’s Edge. In the injunction eBay claimed that the use of bots on the site, against the will of the company violated Trespass to Chattels law.
The court granted the injunction because users had to opt in and agree to the terms of service on the site and that a large number of bots could be disruptive to eBay’s computer systems. The lawsuit was settled out of court so it all never came to a head but the legal precedent was set.
In 2001 however, a travel agency sued a competitor who had “scraped” its prices from its Web site to help the rival set its own prices. The judge ruled that the fact that this scraping was not welcomed by the site’s owner was not sufficient to make it “unauthorized access” for the purpose of federal hacking laws.
Two years later the legal standing for eBay v Bidder’s Edge was implicitly overruled in the “Intel v. Hamidi”, a case interpreting California’s common law trespass to chattels. It was the wild west once again. Over the next several years the courts ruled time and time again that simply putting “do not scrape us” in your website terms of service was not enough to warrant a legally binding agreement. For you to enforce that term, a user must explicitly agree or consent to the terms. This left the field wide open for scrapers to do as they wish.
Fast forward a few years and you start seeing a shift in opinion. In 2009 Facebook won one of the first copyright suits against a web scraper. This laid the groundwork for numerous lawsuits that tie any web scraping with a direct copyright violation and very clear monetary damages. The most recent case being AP v Meltwater where the courts stripped what is referred to as fair use on the internet.
Previously, for academic, personal, or information aggregation people could rely on fair use and use web scrapers. The court now gutted the fair use clause that companies had used to defend web scraping. The court determined that even small percentages, sometimes as little as 4. 5% of the content, are significant enough to not fall under fair use. The only caveat the court made was based on the simple fact that this data was available for purchase. Had it not been, it is unclear how they would have ruled. Then a few months back the gauntlet was dropped.
Andrew Auernheimer was convicted of hacking based on the act of web scraping. Although the data was unprotected and publically available via AT&T’s website, the fact that he wrote web scrapers to harvest that data in mass amounted to “brute force attack”. He did not have to consent to terms of service to deploy his bots and conduct the web scraping. The data was not available for purchase. It wasn’t behind a login. He did not even financially gain from the aggregation of the data. Most importantly, it was buggy programing by AT&T that exposed this information in the first place. Yet Andrew was at fault. This isn’t just a civil suit anymore. This charge is a felony violation that is on par with hacking or denial of service attacks and carries up to a 15-year sentence for each charge.
In 2016, Congress passed its first legislation specifically to target bad bots — the Better Online Ticket Sales (BOTS) Act, which bans the use of software that circumvents security measures on ticket seller websites. Automated ticket scalping bots use several techniques to do their dirty work including web scraping that incorporates advanced business logic to identify scalping opportunities, input purchase details into shopping carts, and even resell inventory on secondary markets.
To counteract this type of activity, the BOTS Act:
Prohibits the circumvention of a security measure used to enforce ticket purchasing limits for an event with an attendance capacity of greater than 200 persons.
Prohibits the sale of an event ticket obtained through such a circumvention violation if the seller participated in, had the ability to control, or should have known about it.
Treats violations as unfair or deceptive acts under the Federal Trade Commission Act. The bill provides authority to the FTC and states to enforce against such violations.
In other words, if you’re a venue, organization or ticketing software platform, it is still on you to defend against this fraudulent activity during your major onsales.
The UK seems to have followed the US with its Digital Economy Act 2017 which achieved Royal Assent in April. The Act seeks to protect consumers in a number of ways in an increasingly digital society, including by “cracking down on ticket touts by making it a criminal offence for those that misuse bot technology to sweep up tickets and sell them at inflated prices in the secondary market. ”
In the summer of 2017, LinkedIn sued hiQ Labs, a San Francisco-based startup. hiQ was scraping publicly available LinkedIn profiles to offer clients, according to its website, “a crystal ball that helps you determine skills gaps or turnover risks months ahead of time. ”
You might find it unsettling to think that your public LinkedIn profile could be used against you by your employer.
Yet a judge on Aug. 14, 2017 decided this is okay. Judge Edward Chen of the U. S. District Court in San Francisco agreed with hiQ’s claim in a lawsuit that Microsoft-owned LinkedIn violated antitrust laws when it blocked the startup from accessing such data. He ordered LinkedIn to remove the barriers within 24 hours. LinkedIn has filed to appeal.
The ruling contradicts previous decisions clamping down on web scraping. And it opens a Pandora’s box of questions about social media user privacy and the right of businesses to protect themselves from data hijacking.
There’s also the matter of fairness. LinkedIn spent years creating something of real value. Why should it have to hand it over to the likes of hiQ — paying for the servers and bandwidth to host all that bot traffic on top of their own human users, just so hiQ can ride LinkedIn’s coattails?
I am in the business of blocking bots. Chen’s ruling has sent a chill through those of us in the cybersecurity industry devoted to fighting web-scraping bots.
I think there is a legitimate need for some companies to be able to prevent unwanted web scrapers from accessing their site.
In October of 2017, and as reported by Bloomberg, Ticketmaster sued Prestige Entertainment, claiming it used computer programs to illegally buy as many as 40 percent of the available seats for performances of “Hamilton” in New York and the majority of the tickets Ticketmaster had available for the Mayweather v. Pacquiao fight in Las Vegas two years ago.
Prestige continued to use the illegal bots even after it paid a $3. 35 million to settle New York Attorney General Eric Schneiderman’s probe into the ticket resale industry.
Under that deal, Prestige promised to abstain from using bots, Ticketmaster said in the complaint. Ticketmaster asked for unspecified compensatory and punitive damages and a court order to stop Prestige from using bots.
Are the existing laws too antiquated to deal with the problem? Should new legislation be introduced to provide more clarity? Most sites don’t have any web scraping protections in place. Do the companies have some burden to prevent web scraping?
As the courts try to further decide the legality of scraping, companies are still having their data stolen and the business logic of their websites abused. Instead of looking to the law to eventually solve this technology problem, it’s time to start solving it with anti-bot and anti-scraping technology today.
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What is Screen Scraping and How Does it Work? - SearchDataCenter

What is Screen Scraping and How Does it Work? – SearchDataCenter

Screen scraping is the act of copying information that shows on a digital display so it can be used for another purpose. Visual data can be collected as raw text from on-screen elements such as a text or images that appear on the desktop, in an application or on a website. Screen scraping can be performed automatically with a scraping program or manually with an individual extracting data.
Screen scraping has a variety of uses, both ethical and unethical. Brief examples of both include either an app for banking, for gathering data from multiple accounts for a user, or for stealing data from applications. A developer might be tempted to steal code from another application to make the process of development faster and easier for themselves.
What is it used for?
Screen scrapers have been applied in a broad number of fields for a variety of use cases. Some potential uses include:
banking applications and financial transactions;
saving meaningful data for later use;
to perform actions a user would on a website;
to translate data from a legacy application to a modern application;
for data aggregators such as price comparison websites;
to track user profiles to see online activities; and
to steal data.
One of the largest use cases has been in banking. Lenders may want to use screen scraping to gather a customer’s financial data. Financial-based applications may use screen scraping to access multiple accounts from a user, aggregating all the information in one place. Users would need to explicitly trust the application, however, as they are trusting that organization with their accounts, customer data and passwords. Screen scraping can also be used for mortgage provider applications.
An organization might also want to use screen scraping to translate between legacy application programs and new user interfaces (UIs) so that the logic and data associated with the legacy programs can continue to be used. This option is rarely used and is only seen as an option when other methods are impractical.
If an individual can gain access to the underlying code in an application, the user could use screen scraping to steal the code and use it in their own application. This would save the individual time and effort or allow them to learn how a feature in an application works without permission.
A portion of the time, screen scraping will involve a third-party system. For example, screen scraping would allow a third-party organization to access data on financial transactions in a budgeting app.
Screen scraping has changed its main use cases over time. A recent example of this comes from 2019 when screen scraping began to be phased out of one of its larger use cases, banking. This was done to ease security concerns surrounding the practice. Budgeting apps now must use a single, open banking technology.
How does screen scraping work?
Screen scraping can be accomplished in several ways, depending on what the process is being used for. For example, through Java, an individual can copy and paste source code from one application into their own if they have a pathway of direct access to it.
In general, screen scraping allows a user to extract screen display data from a specific UI element or documents. Different methods can be used to obtain all the text on a page, unformatted, or all the text on a page, formatted, with exact positioning. Screen scrapers can be based around applications such as Selenium or PhantomJS, which allows users to obtain information from HTML in a browser. Unix tools, such as Shell scripts, can also be used as a simple screen scraper.
In banking, a third-party will request users share their login information so they can access financial transaction data by logging into digital portals for the customers. A budgeting app can then retrieve the incoming and outgoing transactions across accounts.
Regarding the use of transferring data from a legacy program, a data scraping program must take the data coming from the legacy program that is formatted for the screen of an older type of terminal such as an IBM 3270 display and reformat it for Windows 10 or someone using a web browser. The program must also reformat user input from the newer user interfaces (such as a Windows graphical user interface or a web browser) so that the request can be handled by the legacy application as if it came from the user of the older device and user interface.
How to prevent screen scraping
Unfortunately, there is no one definitive way to prevent screen scraping from happening. However, there are ways to help deter it from happening. An organization can detect screen scraping through a few given signatures or use behaviors. For example, if a nonstandard user agent is detected, if JavaScript fails to run client-side or several page request sequences are made, it may be a sign of screen scraping.
To help deter screen scaping, an organization can:
use one-time passwords, because screen scrapers will not be able to see a password until it is used;
use web application firewalls, which can help detect signature- or behavior-based actions;
set a cookie value to be checked by the webserver in JavaScript;
make sure endpoints or APIs aren’t exposed;
run fraud detection software to catch screen scraping potentially while it is happening; and/or
set content to be shown as an image, which won’t stop screen scraping from happening but will stop programs that can’t translate images.
All these methods can help deter screen scraping, but it won’t stop it completely. In addition, organizations must make sure that their actions won’t make the end-user experience worse. For example, setting a website’s content to appear as an image may make it difficult for individuals to find the page, because it will affect how search engines find the page to begin with.
Screen scraping tools
If individuals don’t want to screen scrape manually, there are several tools that can help automate the process, such as:
UiPath
Jacada
FMiner
Macro Scheduler
ScreenScraper Studio
Existek
These tools include automation features such as automated user interfaces, macro recorders and editors. They work with Windows or web applications. Some tools have specific features over others and focus on specific platforms.
Screen scraping vs. web scraping
While screen scraping is the process of extracting data shown on a screen, web scraping extracts data from the web. The two concepts share many similarities to the point where it can be said that web scraping is like a specific type of screen scraping. The main differences lie in where the data is being taken from and what is it being used for.
Web scraping is used to extract data exclusively from the web — unlike screen scraping, which can also scrape data from a user’s desktop or applications. This form of data extraction can be used to compare prices for goods on an e-commerce shop, for web indexing and data mining.
The process accesses the web through HTTP over a web browser and can either be done manually or automatically through a bot or web crawler.
Difference between screen scraping and data scraping
Data scraping is a variant of screen scraping that is used to copy data from documents and web applications. Data scraping is a technique where structured, human-readable data is extracted. This method is mostly used for exchanging data with a legacy system and making it readable by modern applications.
Screen scraping and open banking
Open banking is the concept of sharing secured financial information to be used by third-party developers for the creation of banking applications. This concept is based on the sharing of APIs, which allows an application to use the same API to aggregate information from different accounts into one place. This is what allows a banking app to let users look at their multiple accounts from different banks in one place.
In the past, some banking apps would gather information using screen scraping. This process would require a user to share their bank logon credentials to the third-party app. The application would then log on to the user’s accounts on his or her behalf and screen scrape the needed data to show in-app.
By contrast, open banking now uses shared APIs, meaning the exact data needed is copied without requiring the user to share logon credentials. The concept was introduced in 2018 and is now becoming a standard over the use of screen scraping.
This was last updated in February 2020
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Frequently Asked Questions about website screen scraping

Is it legal to screen scrape a website?

Web scraping and crawling aren’t illegal by themselves. After all, you could scrape or crawl your own website, without a hitch. … Big companies use web scrapers for their own gain but also don’t want others to use bots against them.

What is a screen scraping website?

Screen scraping is the act of copying information that shows on a digital display so it can be used for another purpose. Visual data can be collected as raw text from on-screen elements such as a text or images that appear on the desktop, in an application or on a website.

Why would you scrape a website?

Web scraping is integral to the process because it allows quick and efficient extraction of data in the form of news from different sources. Such data can then be processed in order to glean insights as required. As a result, it also makes it possible to keep track of the brand and reputation of a company.

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