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Data Of 700 Million LinkedIn Users Is For Sale On The Dark Web

Who would pay for this information, you wonder? Spammers, phishers, and other cybercriminals are definitely the target audience here.

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data of 700 million linkedin users is on sale for $5000 on the dark web

The security team at LinkedIn doesn’t get much rest lately. In April, 500 million of its user’s data was exposed by hackers, and the same data collection technique was apparently used by a dark web user called TomLiner, who is currently selling 700 million LinkedIn user records (92% of all LinkedIn users) in a convenient bundle for just $5,000.

The data collection technique in question is called scraping, which is the act of extracting useful information from a website. Since any public website can be scraped using readily available tools, it wouldn’t be correct to call this incident a breach, as LinkedIn quickly pointed out.

“While we’re still investigating this issue, our initial analysis indicates that the dataset includes information scraped from LinkedIn as well as information obtained from other sources,” said Leonna Spilman, Corporate Communications Manager at LinkedIn. “This was not a LinkedIn data breach, and our investigation has determined that no private LinkedIn member data was exposed.”

So, what data has been exposed? Fortunately, no passwords or dates of birth. Here’s what a sample of one million records published by the scrapper contains:

  • Email addresses
  • Full names
  • Phone numbers
  • Physical addresses
  • Geolocation records
  • LinkedIn username and profile URL
  • Personal and professional experience/background
  • Genders
  • Other social media accounts and usernames

Who would pay $5,000 for this information, you wonder? Spammers, phishers, and other cybercriminals are definitely the target audience here.

Also Read: Is Your Phone Hacked? How To Find Out & Protect Yourself

Having all this information in one place makes it much easier for them to create detailed profiles of their potential victims and launch sophisticated targeted attacks against them. Sure, they could simply scape it by themselves using LinkedIn’s own API (application program interface) just like the seller did, but cybercrime can be so profitable that their time is often more valuable.

If you have a LinkedIn account, then you should assume that your personal information is included in the dataset and act accordingly. More specifically, you should enable multi-factor authentication (MFA) and avoid replying to email messages from unknown senders, let alone opening any attachments they may contain.

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ESET Bets On Specialized Security AI At 0.5% The Training Cost

ESET says NeoCortex can estimate an attacker’s next move, with a kill switch and human oversight built in to keep it from going rogue.

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eset bets on specialized security ai at 0.5% the training cost

A sign-in anomaly, a suspicious process launch and an unusual connection may look harmless alone. Together, they can describe an intrusion that is hard for security to teams to piece together.

To solve that problem, ESET announced ESET NeoCortex on November 4, 2026: a specialized foundational AI model for cybersecurity. It powers ESET LiveCortex, available within the ESET PROTECT Platform, which connects fragmented security signals and turns them into actionable incidents.

Filtering is the main selling point, with LiveCortex processing billions of raw telemetry events daily, and just 0.00111% of them contributing to incidents presented to customers. The aim is less alert fatigue and more analyst time spent on threats that matter.

NeoCortex is built on world-model architecture, learning how digital environments behave and how events relate. ESET says that lets it reconstruct missing incident context, recognize similar past cases and estimate an attacker’s likely next step – what the company calls “minus-one-day defense,” a chance to intervene before the next stage unfolds. ESET points to Black October, the week leading up to October 25, 2026, when critical security issues affecting PHP, Linux, GitLab and other key systems demanded rapid, prioritized responses, as the kind of moment where that context matters.

ESET’s internal research also suggests a specialized model like NeoCortex can be trained at up to 200 times lower cost than a large general reasoning model, while delivering more accurate, defense-focused results. The company credits optimized training, a focus on cybersecurity vocabulary, lower computing requirements and privately owned hardware.

Also Read: Dubai Says Its Deepfake Detector Needs Just 7 Seconds Of Video

“AI is accelerating both cyberattacks and cyberdefenses. With ESET NeoCortex, we are applying our AI investment to develop specialized foundational cybersecurity intelligence that remains under our control and strengthens, rather than replaces, human expertise,” said Juraj Malcho, Chief Technology Officer at ESET.

As part of the design, NeoCortex forms part of a layered architecture combining specialized models, deterministic controls, correlation logic, validation, auditability and expert human oversight. Safeguards include restricted sandboxes, read-only tools, continuous monitoring, defined usage and token limits, a kill switch and human oversight of critical response decisions. The model is also developed and self-hosted on ESET’s own infrastructure, which the company says reduces exposure to shifts among third-party AI providers, including commercial and geopolitical ones.

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