Digital privacy has become one of the major battlegrounds in contemporary technology. Amid artificial intelligence, big data, and personalized advertising, a barely visible industry for most users gathers enormous amounts of personal information: data brokers.
Their activity isn’t new, but by 2025, they have reached a level of sophistication and importance that places them at the center of debates on cybersecurity, international regulation, and the data economy.
A secretive but billion-dollar sector
Data brokers are companies that collect, process, and sell personal data from sources such as public records, commercial transactions, browsing histories, social networks, or mobile apps.
It’s estimated that over 4,000 data intermediaries operate in the U.S., with major players—like Acxiom, CoreLogic, or Experian—making billions of dollars annually through the mass buying and selling of information. In Europe, the number is lower due to the GDPR framework, but the same global players remain present.
What’s concerning is the breadth of profiles they generate: from addresses, phone numbers, and emails to mobility patterns, credit histories, political affiliations, consumption habits, or even health risk predictions based on aggregated data.
From commercial segmentation to security risks
In theory, this industry’s goals are “legitimate”: optimizing advertising campaigns, predicting consumer trends, or reducing financial fraud. However, in practice, uses can lead to discrimination, political manipulation, or exposure to cyberattacks.
A clear example: people search websites—BeenVerified, Spokeo, Whitepages, among others—allow any user to access highly sensitive information. For malicious actors, these serve as perfect catalogs for phishing, harassment, or identity theft.
Additionally, many data broker databases end up leaked on the dark web. This means the same sets of data can feed both advertising segmentation algorithms and targeted malware campaigns.
Collection techniques: beyond the obvious
Data brokers don’t rely solely on public sources. Their collection arsenal includes:
SDKs in mobile apps: libraries that capture geolocation, usage habits, and metadata.
Loyalty programs: each discount is paid for with an additional flow of data.
Cookies and fingerprinting: advanced web tracking techniques.
Predictive models based on AI: capable of inferring data users never shared directly (e.g., likelihood of contracting a disease).
With the rise of generative AI, another front opens: data brokers that feed their models with scraped personal information from the internet, without explicit consent.
Legal frameworks: Europe vs. the U.S.
The European General Data Protection Regulation (GDPR) offers a robust framework: explicit consent, the right to be forgotten, data portability, and strong penalties. However, enforcement against large data brokers is limited, as many operate outside of Europe.
In the U.S., the landscape is much more fragmented. States like California, with the California Consumer Privacy Act (CCPA), have implemented rules requiring data brokers to register and allow opt-outs. Starting in 2026, a list of permanent exclusions—”delete lists”—will take effect, representing a significant shift.
The problem is, without a federal law at the national level, much of the industry continues to operate with minimal oversight.
Opt-out and data removal services
For advanced users and sysadmins, the issue isn’t just philosophical but practical: how to limit data exposure?
There are three approaches:
Manual opt-out: Access lists like the “Big Ass Data Broker Opt-Out List” or services from IntelTechniques, which compile hundreds of links to request manual removals. Labor-intensive, but effective long-term.
Automated services: companies like Optery, DeleteMe, OneRep, or Incogni automate the process, periodically monitoring and removing reappearing data. Paid options considered the most realistic for managing sensitive digital identities.
Deletion vs. suppression: deletion removes data from the public database, while suppression prevents its redistribution and resale. The latter is often more sustainable, preventing data from reappearing elsewhere.
Implications for cybersecurity
Security professionals face three immediate challenges with the data broker industry:
Expanded attack surface: each external database with employee or customer info is a potential vector for spear-phishing and Business Email Compromise (BEC) scams.
AI-based attacks: language models can personalize social engineering campaigns using info from data brokers.
Invisible internal leaks: even if an organization secures its own systems, third-party providers could expose related information.
Managing suppliers and third-party risks becomes essential.
Mitigation strategies
Experts recommend a layered defense approach combining:
Regular data exposure audits using threat intelligence tools.
Use of email aliases and virtual numbers for risky registrations.
Corporate privacy policies instructing employees on safe practices.
Hiring data suppression services for critical roles (executives, privileged personnel).
Integration with SIEMs and DLP systems to correlate attack attempts with external leaks.
The business behind it: who buys this data?
The market isn’t limited to advertisers. Major buyers include:
Financial institutions: for credit risk assessments.
Insurers: to set pricing based on personal data.
Political parties and electoral consultants: for microtargeting.
Adtech and martech companies: that combine data from multiple sources to maximize campaign effectiveness.
Malicious actors: purchasing leaked or exposed databases for fraud.
The fine line between legitimate use and abuse is increasingly hard to draw.
Moving toward regulation—or fragmentation
The dilemma is evident: personal data is the raw material of the digital economy. Overregulation can stifle innovation and favor less-restricted competitors; under-regulation fosters distrust, exposure, and risks.
Europe leads with GDPR, but its enforcement against U.S. giants remains limited. The U.S. features a patchwork of state laws like CCPA, fostering fragmentation. China enforces state sovereignty over data, with strict control of both citizens’ and corporate data.
The global scenario is one of fragmented regimes, requiring companies and users to navigate multiple overlapping frameworks.
FAQ
What differentiates a data broker from a social network or search engine? While both collect data, data brokers don’t offer services directly to users. Their business model is solely based on reselling collected information.
What risks does this pose to a company? Data exposure of employees, increased targeted attacks (phishing, BEC), corporate identity theft, and reputational damage.
How can I find out if my data is in the hands of data brokers? Search your name on people search sites, use services like Have I Been Pwned for breaches, or employ digital footprint monitoring tools.
Does AI worsen the problem? Yes. Generative AI enables massive data exploitation and personalization of attacks, increasing both the value and risk of these data sets.
via: Redes Sociales