As it core, web scraping is based on a simple process: You retrieve data from a target website with the goal of doing something meaningful with the data. Regardless of your experience in the industry, this process should immediately make you ask a question to yourself:” I’m retrieving and using someone else’s data, so am I violating copyright or something while scraping?”.
In this article, we’ll discuss what copyright in the context of web scraping is, when it occurs, and how to avoid it.
Let’s dive into it!
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What is Copyright Violation in the Context of Scraping?
Generally speaking, a copyright violation occurs when you reproduce, display, distribute, or create derivative works from someone else’s creative work without their permission (or without a valid legal exception). In the context of web scraping, the “creative work” involves (but is not limited to) the following:
Articles.
Images.
Audio and video.
Code (under particular conditions).
In other words, if you scrape and reproduce an article (even a small part of it) on your website without the author’s permission, you can be infringing copyright. Whether it is actually infringement depends on context (how much content you copied, how you used it, and which jurisdiction applies), but “a small part of a whole article” is not a safe harbor.
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How Can Copyright Violations Occur While Scraping?
To avoid copyright infringements, you should know the common cases to take care of. Below is a list of common situations where copyright can be violated while scraping data from websites:
Copying content: Technically speaking, scraping is copying. When you download a webpage’s HTML to your disk, you’ve made a copy. If that HTML contains creative expression, you have created a copy of copyrighted material. That does not automatically mean you are infringing, but this is the exact action copyright law regulates. And if you store, reuse, or republish that expression without permission (or a solid exception), you’re in infringement territory. Note that courts don’t need the copied content to be 1:1 identical. For them, “substantial similarity” can be enough.
Copying images and media: Images are typically strongly protected. Scraping image URLs and hotlinking can still be risky, even if you report the source URLs while republishing the images. And, of course, downloading and rehosting is even more direct copying.
Copying “creative fields” that look like “data”: Product descriptions, editorial blurbs, “about” sections, hotel/restaurant descriptions, FAQs, and similar content is often copyrighted text. While editorial blurbs and similar text are obviously copyrighted content, the others are not so obvious. The point to always take care of is in relation to “creative work”. A product description can be creative work when it contains original language, structure, or marketing copy. But not every description is protected. For example, a purely functional description text may have weak or no copyright protection, depending on the jurisdiction and the originality of the content itself.
Scraping for training LLMs: Scraping web pages to get data for training LLMs is surely part of the evolving career of web scraping professionals. However, scraping data to train Large Language Models can trigger reproduction/derivative-work arguments in courts. This is still an evolving legal area, so you should not assume “transformative” automatically saves you from legal troubles, especially at scale. The issue between studio Ghibli and OpenAI on copyright violations due to LLMs’ training is one among the open ones, but keep in mind: allegations, investigations, and lawsuits are not the same thing as a final court ruling.
How to Avoid Copyright Violations While Scraping
Having legal issues is probably the worst nightmare for professional scrapers. So, how can you be sure you are not violating copyright while scraping? Below is a list of guidelines to take into consideration:
Scrape facts, not expression: Copyright protects expression, not facts. Scraping the price of a stock, the temperature in London, or a flight arrival time doesn’t infringe any copyright because these are facts. No one owns the fact that today it is 20 degrees in London. On the other hand, scraping a journalist’s analysis about why the price of a stock moved in a certain direction, or a photographer’s image of London, is a creative expression.
Transform, don’t replicate: When repurposing content (on your website or anywhere else), transform it. This is a general rule of thumb, but if you are in the US, one of your best defenses is “Fair Use”. But to claim this, your use must be transformative. For example, scraping Amazon reviews and posting them on your own e-commerce site is replicating, not transforming. Even summarizing reviews cannot be considered transformative in some cases, and even when it is, it’s not a guaranteed shield.
Don’t store raw pages by default: As said before, storing the HTML of entire pages means creating copies. To solve this, you can follow two paths:
Parse in-memory.
Extract only the necessary content, not whole pages.
Treat images as a separate “danger zone”: Images are a type of content that, during the whole Internet era, had the majority of copyright issues so far. The safest options are:
Using the website’s official APIs when scraping images, if available.
Scraping images under a Creative Commons license with compliance.
Asking and getting direct licensing from the owner.
So far so good, but let’s be honest: When you are taken by your daily job tasks, it’s easy to lose your compass. To avoid it, the best thing to do is to create standardized (and documented) processes and procedures so that you always operate under a guardrail. This section provides you with a couple of ideas you can implement as standardized processes to be sure you don’t violate any copyright while scraping.
Procedure #1 to Avoid Copyright Violations While Scraping: Develop a Copyright Risk Check
Most copyright problems in scraping are self-inflicted. This happens because developers often scrape “everything on the page,” save it “for later,” and only then do they ask: “Wait, can we ship this?”.
Before you add a field (or a selector) to your scraper, ask yourself the following questions:
“Is this a fact, or is this someone’s writing?”: Prices, dates, SKUs, addresses, and opening hours are facts. A paragraph of an article is someone’s writing. Remember to treat those differently.
“If I publish this, would it compete with the source?”: If your application lets users consume the content without clicking the original, you’re not “aggregating.” You’re substituting.
“Am I copying just what I need, or am I copying the entire page?”: If the answer to this question is: “We only store it for debugging”, then you are building a copy.
“How much am I taking?”: A single excerpt is one thing. Thousands of excerpts across a site start looking like a dataset designed to recreate the whole content.
“What am I going to do with it later?”: Internal analysis is one risk profile. A public API that returns the scraped text is a completely different risk profile.
“Is my plan defensible if someone sends a legal notice?”: If your only defense is “but the content is publicly available”, you don’t have a defense. As said before, public availability is different than ownership-
If answers to these questions feel shaky, the fix is usually boring: don’t collect it, collect less, or get permission.
Procedure #2 to Avoid Copyright Violations While Scraping: Build Your Scraper So It’s Hard to Do Something Dumb
If you want to stay out of trouble, don’t rely on “policy.” Rely on defaults and standards.
Here’s what I mean: The safest scraper is the one that can’t casually vacuum up article bodies, image files, and review text unless you deliberately build it that way.
Below is a process that works safely:
Fetch the page.
Extract only what you came for.
Store facts + metadata (source URL, timestamp).
Throw the rest away.
When you really do need to keep anything close to “content” (ie, media), treat it as a special case: short retention, locked-down access, and a reason written down somewhere if needed. Not “maybe we’ll need it later”: You must have a valid reason.
If you want a mental model, you can think of it like so: You’re not building a web scraper. You’re building a pipeline. And pipelines need guardrails.
Examples: What “Safe-ish” Looks Like vs What Can Surely Get You in Trouble
Let’s be practical now and see some examples of what is generally safe and what is not. Of course: The following examples are not court outcomes. They’re the kind of setups that tend to be boring (safe-ish) or spicy (trouble-ish):
Price tracker (safe-ish): You scrape SKU + price + availability + timestamp and show a price history chart. You don’t copy product descriptions or images. This is the classic “facts + original output” use case.
Product catalog clone (risky): You scrape titles, descriptions, bullet points, images, and reviews, then you show them on your site. That’s not “data.” That’s content. You’re rebuilding their user experience.
News aggregation (high risk): If you store headlines + links and add your own tags/filters, you’re closer to indexing. If you store full articles and users can read all the content as is without leaving your site, then you’re highly risking getting a trip to the nearest court.
Review analytics (mixed): Using reviews internally to compute “top complaints this month” is one thing. Republishing reviews precisely as they are is another.
Business directory (often safer, until you start copying the fluff): Name, address, phone, opening hours: These are usually factual. “About us” sections and photos, on the other hand, are where you cross over into copyrighted expression.
So notice the pattern: The moment your product starts looking like a substitute for the source, your legal risk goes up fast.
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The Traps That Have Nothing to Do with Copyright (But Still Hurt)
Copyright is only one way scraping can go wrong. Plenty of scraping disputes are won on issues that are simpler to prove than infringement. Below are the big ones you should treat as “no trespassing” signs:
Circumvention (DMCA Section 1201): If the site uses a login wall, CAPTCHA, paywall, anti-bot challenges, or IP blocking to stop you, and you write code to bypass those measures, you are potentially violating anti-circumvention laws. This is not “copyright infringement” in the traditional sense, but the practical takeaway is simple: If you have to defeat a technical barrier to get the data, you’re walking into a high-risk territory fast.
Disregarding robots.txt: The robots.txt isn’t the law, but ignoring it has its implications. In disputes, it can be used as evidence that you knew you were unwelcome and kept going anyway. It can also be relevant to arguments about authorization and “bad faith,” even if it doesn’t create copyright liability by itself.
Terms of service (contract risk): If the ToS explicitly forbids scraping (and most do), and you scrape anyway, you may be liable for breach of contract. This is often easier for the content owner to win than a copyright claim because the argument is straightforward: You agreed (explicitly or implicitly) to a contract, then you violated the agreement.
Do not scrape behind a login: Once you log in, you have affirmatively agreed to a contract. Breaking that contract to scrape is a fast track to a lawsuit. If your plan requires authenticated access, treat it as a licensing/permission problem, not an engineering challenge.
Conclusion
In this article, we’ve discussed how copyright infringements can occur while scraping and how to avoid them. As said, it’s not always easy to understand when you are actually infringing copyright, as it depends on the governing laws which, often, are local ones. Still, the main ideas proposed can help you be conservative and stay pretty safe while scraping web pages.
So, let us know: Did you find those practices useful? Do you apply other frameworks to be sure you’re not violating copyrighted content? Let us know in the comments!tat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.”
