Is Web Scraping Legal? What You Can and Can't Do in LATAM

"Is what we want to do actually legal?" is the first right question to ask before taking on any data-extraction project. Web scraping — the automated extraction of data from websites — is legal in Argentina and most of LATAM when you extract public, non-personal data, without bypassing security measures and without harming the site you query. It becomes risky when it involves personal data (regulated by Data Protection Law 25.326 and its regional equivalents), copyright-protected content, or the violation of terms of service you accepted. This guide draws the lines as precisely as possible — with the caveat that it's general orientation, not legal advice for your specific case.

What web scraping is and why your company may already need it

Scraping is using a program to do what a human would do with a browser: visit pages, read data, and copy it into a spreadsheet or database. The difference is scale: where a person reviews 50 prices an hour, a scraper reviews 50,000, every day, with no typos. It's one of the classic tools of programmatic automation.

The most common legitimate uses we implement:

• Competitor price monitoring: knowing every morning how your catalog is positioned against the market.
• Public data aggregation: tenders, official gazettes, regulations, public registries, open government data.
• Market intelligence: real estate listings, job postings, product availability across marketplaces.
• Brand and distributor control: detecting who's selling your product off-price or without authorization.

The legal framework in Argentina: the three layers that matter

There's no "scraping law." What exists are three frameworks that intersect:

1. Personal data — Law 25.326. The most important line. If what you extract identifies people (names, emails, phone numbers, profiles, photos), you're processing personal data and the law applies in full: you need a legal basis, a legitimate and declared purpose, and you must respond to access and deletion requests. "It was public on the internet" does not equal consent — this is the costliest misunderstanding in the field. Building prospecting databases by scraping emails and phone numbers is, flat out, the highest-risk zone.

2. Terms of service. Almost every large site prohibits scraping in its terms. This is a contractual layer: the typical consequence is having your access blocked or facing a civil claim, not a criminal case. The risk is low if you browse public content without an account, and high if you created an account and expressly accepted terms (LinkedIn, Instagram, marketplaces while logged in).

3. Unauthorized access and computer damage. The Criminal Code punishes unlawful access to restricted systems. Scraping public content doesn't fit there; bypassing passwords, paywalls, or technical blocks to reach restricted content can, on top of taking a site down through excessive requests, which creates liability for damages.

How the picture looks across the rest of LATAM

Country	Personal data law	Practical note for scraping
Argentina	Law 25.326 (1853 if its reform advances)	Public personal data stays protected
Brazil	LGPD (Law 13.709)	The strictest and most actively enforced in the region; fines up to 2% of revenue
Mexico	LFPDPPP	Requires a privacy notice for any processing
Colombia	Law 1581 of 2012	Strict purpose principle; the SIC actively sanctions
Chile	Law 21.719 (replaces 19.628)	New regime with an agency and real fines from 2026
Peru	Law 29733	Similar in structure to Argentina

The cross-cutting rule: prices, products, and official data are not personal data, and extracting them is defensible across the entire region; data about people is protected everywhere, whether or not it's published.

Need data from the web but don't want to land in trouble? Book a 30-minute call and we'll review together whether your case is viable and how to do it right.

The red lines: what you must never do

So no grey areas are left, here's what we at Deepyze neither do nor recommend:

• Mass-collecting personal data for prospecting (emails, phone numbers, profiles) without a legal basis. It's the most common violation and the most sanctionable.
• Bypassing logins, paywalls, CAPTCHAs, or blocks to access restricted content. It crosses from the contractual layer into the criminal one.
• Republishing copyright-protected content: extracting descriptions, photos, or articles from another site and publishing them as your own infringes Copyright Law 11.723, scraping or not.
• Degrading the service of the queried site: hundreds of requests per second can take down someone else's server; beyond being unethical, it creates civil liability.
• Disguising the bot as a human user by rotating identities to dodge explicit blocks: if the site blocked you, the message was clear.

Technical best practices of ethical scraping

These practices reduce legal risk and, along the way, make scrapers more stable:

1. Before scraping, look for the API: many sites offer an official route to the same data (Mercado Libre has one, for example). It's more robust and removes the legal debate. We explain the difference in what an API is and how it's used to integrate systems.
2. Respect robots.txt: the file where each site declares what it allows bots to query. It's not law, but it's the good-faith reference a judge and an expert witness will look at first.
3. Rate limiting: space out requests (1 request per second or less is a reasonable floor) and run during the site's low-load hours.
4. Honest identification: a user-agent that says who you are and how to reach you, rather than impersonating a human browser.
5. Caching: don't re-request what hasn't changed; less load for them, less cost for you.
6. Data minimization: extract only the fields your use case needs, and discard any personal data that comes along "for free."

What to check before taking on (or hiring) a scraping project

A short checklist to ground the risk before writing a line of code:

1. Does the data identify people? If the answer is yes, stop and consult: the project needs specific legal analysis, not just good engineering.
2. Is there an official route? An API, an open dataset, a commercial agreement with the source. Check that first; sometimes it costs the same and eliminates the problem at its root.
3. What do the site's robots.txt and terms say? Not to abandon the project at any generic prohibition, but to decide with full information.
4. What's the data worth if the source blocks you tomorrow? Design assuming it can happen: multiple sources, graceful degradation, alerts when the site's structure changes.
5. Who maintains the scraper? Sites redesign their pages without notice; an unmaintained scraper dies, on average, within a few months. Budget for that support from day one.

When you should NOT scrape

• If an official API or open dataset exists with the same data: use them, always. Scraping is plan B, not plan A.
• If the entire business depends on a single site that can block you tomorrow: a business model built on scraping a single hostile source is structurally fragile.
• If the goal is to build contact databases: there are legal paths to generate demand; this isn't one of them.
• If the data barely changes: to review 200 prices once a quarter, a person with a spreadsheet is still the most reasonable option.

Scraping done right, with someone who takes it seriously

The difference between a valuable data project and a legal problem is the design: what gets extracted, from where, at what rate, and with what safeguards. At Deepyze we build ethical, maintainable scrapers — price monitoring, public data aggregation, market intelligence — as part of our AI automation and custom software services, with the APIs and integrations layer so the data flows straight into your systems. A fixed, closed price before we start, a proposal in 24 hours, and a team in your time zone to adjust the scraper when the source changes. Tell us what data your business needs and we'll tell you frankly whether it can be done, how, and what it costs.