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Giant User Theft and Bot Attacks Target on Job Seekers

 

Job seekers are viable targets for social manipulation efforts because applicants are emotionally weak and eager to provide any information to help them win the job. Cybercriminals are finding it easier to find the next victim now the "Great Resignation" is in full armor. 

A job posting portal with a location in six countries was the sufferer in this instance. The goal of the attack was to collect job seeker information from the website. 

Since February 1, experts have seen a 232 percent increase in phishing email attacks imitating LinkedIn, seeking to deceive job seekers into handing up private credentials. The emails contained subject lines including "Searching for a suitable candidate online," "You mentioned in 4 searches this week," and even "You have 1 new message," as per the Egress team. 

The OWASP Foundation classifies web scraping as an operational threat (OAT-011), which is defined as gathering accessible data or processing output from an application. While web scraping walks a delicate line among reporting and data privacy violations, it is still one of the most common automated hacks affecting businesses today, according to Imperva.

Imperva didn't name the company, but it said it received 400 million bot requests from 400,000 network Interfaces over four days in an attempt to harvest all of its job seekers' information. Similar strategies can be employed in "scalping" attacks, which are aimed to purchase in-demand, limited-edition products in order to resell them at a greater price later. Imperva neutralized one such operation on a retailer's website around Black Friday week, which had nine million bot queries in only 15 minutes — 2500 percent above its normal traffic rate.

Several people are accustomed to receiving regular authentic LinkedIn communications – and may unintentionally click without double-checking. Individual users are still responsible for being aware of the data they provide socially and how it can be used to deceive users into clicking a malicious link.
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