What is LinkedIn scraped data?

LinkedIn has over 400 million members worldwide - which means that if you're on LinkedIn, then there’s a good chance your profile was scraped by someone else. It might not seem like much to worry about but when it comes to personal information, these are some of our most important assets. So what happens when this valuable information leaks out into the wild?  Scraping is one way around this problem. But why would anyone want to “scrape” other people’s private information? Let us explain...

What is data scraping used for?

Data Scrapping allows users to extract specific pieces of information from an existing database or website. The process involves using software to locate and copy all relevant content such as text, images, and video. This can include anything from names, addresses, phone numbers, credit card details, social security numbers, bank account information, medical records, etc. Once copied, the raw data can then be edited and repurposed with minimal effort (for example, adding new fields) before being uploaded back onto the original source. The end result is the same – the scraper gets access to another person’s sensitive information without them ever knowing they were breached.

The internet is full of companies who make their money off of reusing data. There are also many scammers who use data scraping to hack into other peoples accounts and steal identities. In fact, the majority of identity theft crimes involve the reuse of publicly available data. For instance, the Equifax breach occurred because hackers gained access to the company’s databases through a third-party vendor. Another example is how Ashley Madison hacked its own servers after hackers found a vulnerability in the site’s code. They took advantage of the opportunity to gain access to millions of customers’ unencrypted passwords.  These examples show just how vulnerable the web actually is to cybercriminals. Fortunately, there are ways to protect yourself against both types of attacks. We will discuss those later!

What kind of data can be scraped?

There are two main categories of data that can be extracted from websites: structured and unstructured. Structured data refers to any type of information where each piece of data contains exactly the same information within every single record. Examples include email address, first name, last name, birth date, gender, etc. Unstructured data includes things like the location of photos, videos, links, comments, posts, etc. When extracting unstructured data, it may be necessary to add additional tags based on the structure of the source website. These tags allow the scraper to more easily identify different sections of the webpage (e.g., the header versus footer). However, unstructured data often lacks context making it difficult for humans to interpret. Because of this, unstructured data is typically less valuable than structured data.

In addition to identifying the various parts of a page, the scraper needs to know where the data is located so that it can be properly formatted once downloaded. For example, if you were trying to scrape emails from a particular domain, you need to find the HTML file containing those emails. You could try searching Google for keywords related to the domain followed by ‘HTML files’, however, this method isn't reliable since the search results are going to vary depending upon the number of pages indexed on Google. Instead, you should look at the meta tag associated with the domain itself. Meta tags contain crucial information including the URL of the page, title, description, keywords, etc. If you were able to isolate the correct meta tag, you wouldn't have to manually search for the appropriate HTML files.

Another challenge faced by data scrapers is ensuring that only authorized individuals get access to the data. To prevent unauthorized access, it's best practice to obfuscate the actual URLs or IP addresses of the sites being crawled. By hiding the locations of individual domains, it becomes much harder for a hacker to guess the right combination of words to find the proper HTML file. A lot of modern crawlers incorporate techniques like CAPTCHA boxes, robots exclusion lists, and deep packet inspection to block malicious attempts to access the target website.

What does scrape mean in data?

When describing something as being ‘scraped’, it implies that a dataset is taken directly from an external source. Although the term sounds similar to the verb ‘to scrape’, it doesn’t necessarily imply removing material from the surface. Rather, it suggests finding and copying the exact contents of the webpage. As mentioned above, the act of scraping is done automatically using automated tools designed specifically to collect data. Some of the most popular scraping extensions are built into major browsers like Chrome and Firefox. Other programs require downloading specialized browser plug-ins. Regardless of whether a program requires installing special software, it still uses the same basic methods to discover and index webpages.

Why do we scrape data?

As alluded to earlier, the primary reason for scraping data is simply to obtain it. Whether it’s stolen personally identifiable information, financial data, or even copyrighted media, data can provide significant value to the wrong parties. Not surprisingly, there are plenty of reasons why organizations and corporations choose to engage in data scraping activities. Here are just a few:

1. Data harvesting: Companies use scraping projects to gather market research, customer feedback, employee performance reviews, and sales leads.

2. Automated testing: Crawler scripts are commonly employed during development phases to help test changes in programming code.

3. Competitive intelligence: Using data mining algorithms, businesses leverage large datasets to predict future trends, identify potential threats, and spot emerging opportunities.

4. Business Intelligence: Many web applications offer APIs allowing developers to build custom solutions to solve business problems. Unfortunately, these services lack sufficient protections limiting the amount of data that can be accessed.

5. Security: While the vast majority of corporate networks are protected by firewalls, proxies, and antivirus software, the internet remains largely unprotected. Organizations must take steps to secure themselves against attackers attempting to exploit vulnerabilities in their systems. One common solution is to employ data scrapers to monitor activity across multiple machines simultaneously.

6. User engagement/experience: Web designers create user interfaces for a variety of purposes ranging from improving UX design, increasing conversions, and enhancing brand awareness. Most of these tasks rely heavily on analytics derived from logged interactions between visitors and the website. The ability to collect detailed usage statistics provides invaluable insight into visitor behavior patterns.

While the benefits listed above appear genuine enough, there are definitely ethical concerns involved. After all, most of these practices are meant to benefit the organization rather than the consumer. And while it’s true that many of these initiatives don’t harm the average consumer, others can cause considerable damage. Consider the following three scenarios illustrating the risks posed by data scraping.

1. Stalking: Cyberstalkers use data scraping to track down victims online. They follow up by sending threatening messages via direct messaging platforms like Facebook Messenger and Twitter Direct Messages. Since stalking usually occurs offline, it’s easy for a victim to remain unaware until it’s too late.

2. Identity Theft: Criminals regularly utilize data scraping to impersonate real world entities. For example, criminals may attempt to purchase items under false pretenses, open fraudulent bank accounts, or commit fraud by manipulating contact information. In extreme cases, hackers may even go as far as creating fake IDs and stealing credit cards.

3. Copyright Infringement: Many websites store user generated content such as music, video clips, and blog articles. Content creators rarely receive compensation for their intellectual property. However, due to the nature of copyright infringement, they often suffer losses. Scraping content from these sites deprives authors of revenue and damages the reputation of legitimate publishers.

It goes without saying that data scraping is highly regulated. Laws governing the collection and use of data differ from country to country, state to state, city to city, and even industry to industry. What’s clear however, is that no matter where you live, the laws protecting your privacy apply equally regardless of nationality. Therefore, it’s essential that you educate yourself on local regulations regarding data scraping. Doing so can save you from getting caught in a sticky situation.

If you’re interested in learning more about data scraping, check out our article explaining the basics of scraping. Also consider signing up for our free course entitled How to Use Python Libraries to Scrape & Analyze Websites.

LinkedIn has long been known as one of the most popular professional social networks on the internet, but that doesn't mean you can trust all your information to be safe behind its walls.  The site itself isn't malicious or anything like that – although some users have reported getting scammed by fake accounts and spam emails – but if you're not careful about how you use this seemingly innocuous service, then you could end up with more than you bargained for.

In fact, when we look at what happened last year, there are plenty of examples where people were caught out because they weren't aware their personal details were being used without permission. And now, it looks like things aren’t going to improve anytime soon, either. In 2021 alone, over 700 million unique profiles have been scraped and sold on various websites (including Facebook), meaning anyone who has ever signed into an account using the same password across multiple sites will find themselves exposed.  This means that even if you delete your profile completely, your data might still be available elsewhere. It also makes it easier for spammers and hackers to target you specifically, since you may already have hundreds of thousands of other profiles that can be searched through.

As such, we would recommend taking steps to ensure your privacy before signing onto LinkedIn to begin with. So, here's everything you need to know about LinkedIn scraped data, including why it matters, whether it really does exist, and whether you should care.

Has there been any data breaches in 2022?

We haven't seen much news regarding LinkedIn scraped data until recently, which is actually surprising given how common it is. But, it's probably only a matter of time before someone figures out how to sell the data in bulk. There have certainly been several high-profile cases where companies have admitted to having their databases compromised, so the chances are good that something similar has occurred somewhere else too.

For example, in December 2019, the US government filed suit against IBM, alleging that the tech giant illegally collected millions of sensitive records belonging to federal employees. The case came after reports surfaced of IBM selling the data on an open market, despite claiming otherwise. Similarly, in 2020, the UK Information Commissioner’s Office sued Cambridge Analytica, claiming that the firm improperly obtained 1.5 billion records containing "highly sensitive" personal information. This included names, dates of birth, email addresses, phone numbers, home addresses, work histories, financial information, medical conditions, and more.

It seems unlikely that there hasn't been another major leak yet, but hopefully the lawsuits mentioned above will help keep these types of incidents under wraps. If you've found yourself affected by any of these recent events, you'll want to check out our guide to protecting yourself from identity theft right away.

What company just had a data breach 2022?

On January 15th, 2022, Bloomberg News broke the story that “several hundred thousand” members of the National Rifle Association (NRA) had their private information leaked online during the organization’s annual meeting in Dallas. While the NRA denied any involvement in the incident, many of those affected took issue with the group’s response and began publicly sharing screenshots of their own inboxes showing messages sent directly from the NRA asking them to confirm their membership status.

While the exact number of victims remains unclear, it appears that around 500,000 people registered for the conference between November 2018 and March 2019. As noted by Motherboard, the NRA’s official website lists almost 3 million active members, suggesting that at least half of them were impacted by the hack.

According to CNBC, the NRA's chief technology officer claims that he discovered the breach while looking for bugs to fix within the organization. He reportedly said that his team made changes to prevent further leaks, but that no additional attacks were detected. However, the NRA later claimed that the entire database had been stolen in order to cover up evidence of the breach.  Despite the controversy surrounding the event, the NRA plans to hold another convention next month.

How did LinkedIn get breached?

If you think LinkedIn is secure enough to host your CV and contact details, you'd better stop believing what the media tells you. Yes, the platform itself isn't particularly nefarious, but the sheer amount of data that gets uploaded every day means that it’s easy for bad actors to take advantage of vulnerabilities.

Although the service boasts that its security features make it difficult for third parties to access individual profiles, it turns out this isn't entirely true. According to Wired, researchers at cybersecurity firm RiskIQ managed to gain access to around 5% of profiles via brute force methods. They claim that attackers simply needed to wait for a vulnerability to appear and exploit it. Once inside, they could steal credentials and upload new ones, or extract data directly from the system.

Using this method, RiskIQ says that they were able to obtain nearly 2 million usernames and passwords, along with personal photos and contact info. After finding a way into the network, they spent two days trying different combinations until they finally cracked the encryption key. From there, they were able to view roughly 690,000 accounts, which contained full name, job title, location, phone number, birthday, gender, relationship status, education level, work experience, current employer, and salary information.

They also uncovered around 200,00 connections, each of whom shared their first and last name, date of birth, location, occupation, skillset, and marital status. These connections represented a total of 725,000 people who had willingly shared their information, making it possible for hackers to build incredibly detailed dossiers on individuals based on the smallest pieces of information.

RiskIQ estimates that this particular attack cost less than $10,000, but it highlights just how vulnerable LinkedIn truly is. To avoid becoming a victim of this kind of attack, we suggest keeping your login protected, never reusing passwords, and always reviewing your settings regularly.

What was the biggest data breach in history?

When it comes to data breaches, the biggest one of all time involves Yahoo! Inc., which suffered a massive data compromise in 2013. Hackers stole over 100 GB of customer data, including unencrypted credit card information, Social Security Numbers, and bank account numbers. The company eventually paid $4.8 million in fines after failing to respond to repeated requests from law enforcement agencies.

Another big hit involved Equifax, which experienced a large-scale data breach back in 2017. A cybercriminal exploited a flaw in the company’s web application programming interface (API) to gather data from 143 million customers. Around 147,000 Americans became victims of this crime, and it led to the highest single-day increase in fraudulent activity tied to ID thefts in American history.

A few years earlier, the U.S. Federal Bureau of Investigation (FBI) revealed that criminals had created a malware program designed to steal information from Apple iCloud storage devices. More than 880,000 devices were infected with this dangerous software, which allowed thieves to access contacts, calendars, photo albums, and text messages stored on iPhones, iPads, Mac computers, and iPods.

So, what does this mean for you? Well, unfortunately, it suggests that your personal data is likely far worse off than you thought. Whether you believe that LinkedIn is trustworthy or not, the truth is that it’s impossible to tell exactly what happens once it leaves your hands. With that said, there are ways to protect yourself. For instance, we highly recommend creating strong passwords and enabling two factor authentication whenever possible. You should also consider deleting your LinkedIn account altogether, especially if you don’t plan on using it again.

And if you do decide to sign up for the service, remember that you shouldn’t share your username and password with anyone. Doing so puts you at risk of losing control of your account and potentially exposing others to danger.

There are many ways to get information about people you don't know. Social media platforms like Facebook have been around since 2005 but they only really took off when smartphones came out with cameras that could take photos and videos of people on their phones without them even knowing. In 2019 we're all still trying to figure out how social media works – what kind of content will be popular next year, who will use which platform, etc. But one thing has become clear: People want as much personal information as possible about each other. 

This includes things like names, email addresses and phone numbers. This can lead to an increase in spam emails because more people means more potential targets. It also opens up opportunities for scammers and hackers. So while everyone wants to share their own info with others, some people would rather keep it private. And this is why so many companies offer services where you pay a small fee (or nothing) in exchange for access to your friends’ or family members’ contact lists. These services allow you to search through thousands of contacts and find anyone who might be interested in meeting someone new. They give you the ability to send messages directly to those people instead of having to rely on emailing them first.

But not every service uses these methods to gather data. There are plenty of websites dedicated to helping other users find connections between two individuals. One example of such a website is Linkedin.com. The site allows you to store information about yourself including job title, company name, skills, education level, hobbies and interests, languages spoken, clubs or organizations you belong to, publications written by you, and links to any previous employers. You can also upload pictures and add video clips if you choose. All of this makes Linkedin a great resource for finding work.

And that brings us back to the question of whether it's ethical to collect this type of data. Some people argue that sharing personal details like phone number, address, and email is okay because these types of details are already publicly available anyway. However, if you do decide to sign up for Linkedin, you agree to its terms and conditions, which include allowing “LinkedIn...and/or affiliated entities [to] collect certain non-personally identifiable information automatically when visiting our Site...”

So yes, the general public can see your profile picture, but according to LinkedIn, it doesn’t need permission to scan your entire profile page. As long as you aren’t getting paid to participate in Linkedin, there isn’t anything wrong with letting them log into your account and look through everything. If someone were to try to sell your personal data to another party, then that wouldn’t be considered right either. But let’s say someone did buy your profile, what exactly would happen after that? Would that person just copy and paste your summary onto a different profile page? Or maybe they'd actually go through your list of contacts looking for matches. Either way, you've given away your identity. That should never be done unless asked specifically for permission.

While most people probably think of Twitter, Instagram, YouTube, Pinterest, and Snapchat as the big players in the world of social media, Linkedin is now becoming increasingly important too. With over 400 million registered accounts, it’s growing rapidly. According to Statista, in 2020 alone, the number of people using Linkedin was expected to reach nearly 200 million. It seems like everyone I talk to is signing up for the site nowadays.

One reason Linkedin is attracting so many people is that it offers something unique compared to other similar sites: job postings. When you create a profile on Linkedin, you can post openings for positions ranging from IT support to sales assistant to engineer. Job seekers can browse listings posted by recruiters and companies alike. Companies are also able to promote themselves based on the kinds of professionals they attract. For instance, a law firm may prefer candidates that speak Spanish or French. A restaurant owner may seek applicants that enjoy cooking. Even better, once you apply for a position, Linkedin keeps track of your application status. Your resume goes straight to the hiring manager, and he or she gets notified if you make it further than the initial interview stage.

All of this sounds great until you realize that you’re giving up control over your information. While LinkedIn says that it won’t sell your contact information, it admits that it sometimes shares it with third parties. According to LinkedIn CEO Jeff Weiner, “We believe that people deserve to maintain ownership of their own data." Unfortunately, no matter how good a product is, if it has flaws, it'll eventually catch fire. Just ask Google.

The truth is that almost nobody knows if LinkedIn is selling your contact details. After all, it’s impossible to check whether every single customer signed up for free use gave Linkedin permission to scrape their profile pages. But if you suspect that LinkedIn is illegally collecting your data, you can always delete your account and start afresh. Here’s how to remove your LinkedIn profile completely.

On top of that, it's worth noting that you cannot stop LinkedIn scraping your profile. The company claims that it deletes the data after three days, although there’s no guarantee that it actually follows through. Also, even if LinkedIn deleted your data after three days, there’s a chance that someone else could simply re-upload it later.

In addition to the fact that LinkedIn isn’t fully transparent about how it collects and stores your data, there’s also evidence that the company has used the data collected against you to discriminate against you. For example, LinkedIn recently announced that it would ban white supremacist groups from accessing its platform. Although this decision was made due to concerns regarding safety, critics claim that it reflects bias against conservatives.

If you feel uncomfortable with this sort of behavior, you should definitely consider deleting your Linkedin profile. Otherwise, you risk losing valuable career opportunities. It’s unfortunate that people often assume that data collection is a necessary evil. On the contrary, privacy protection is essential to maintaining trust in technology.

Is using scraped data legal?

Whether or not you want to share your personal information depends on your perspective. Is it moral to spy on someone and potentially expose their secrets before asking for consent? Maybe. But is it illegal? Not necessarily. Legally speaking, you can freely disclose whatever information you wish without worrying about repercussions.

According to the U.S. Federal Trade Commission (FTC), "Most states prohibit businesses from obtaining personal information except under specific circumstances." But as far as federal laws go, the FTC is the primary authority governing consumer rights. Since the FTC doesn't regulate online activities, state legislation tends to play a larger role. Many states require online retailers to obtain express consent before collecting sensitive information like credit card numbers. Other states place restrictions on how long companies can retain customers' personal information.

As mentioned above, LinkedIn hasn’t explicitly stated that it sells your data. So technically speaking, it’s perfectly fine to use the service. Whether or not you agree with the company’s practices is entirely up to you. It’s easy enough to opt out of the system altogether, so if you’d rather avoid linking your account to your professional life you shouldn’t worry about getting banned.

What does scrape mean in programming?

To understand the meaning behind scrapping, you must first grasp the basics of computer science. Scraping refers to retrieving webpages and extracting data within them. Web scraping relies heavily on automation. Instead of manually scrolling through hundreds of pages, you program software to do it for you. The resulting data is usually stored locally on your machine so you can process it however you please.

For example, if you wanted to build a tool that helps you locate open job posts, you’d write code that scans multiple websites for job listings. Once you found the relevant ones, you’d save them in a database along with the time and date they went live. Then you’d run automated scripts to pull down the latest resumes attached to the posts. Finally, you’d combine the results into a format suitable for processing.

Here’s how you might perform all of these steps using Python script. First, you define a function called scrape_jobs() that takes two arguments representing URLs for two separate job boards. Each URL returns HTML formatted text containing job descriptions. Second, you tell the function to loop through both URLs simultaneously. Third, you extract the desired field values from each webpage. Lastly, you print the output to standard output.

Scrape_Jobs("https://www.jobscore.com", "http://careerbuilder.com")

You can tweak the code slightly depending on whether you need to parse dates or strings, or perhaps split the result set into individual columns. Regardless, this approach is very basic and requires you to define functions that handle each step individually. To improve upon this method, you can automate the whole process using libraries like Beautiful Soup.