Companies across every industry are now facing a new kind of fraud: fake job applications powered by AI.

Using off-the-shelf AI tools, anyone can now create extremely realistic fake resumes, professional headshots, online portfolios, and LinkedIn profiles in seconds. Combined together, it looks like an ideal candidate for your open roles.

AI is fueling a surge in fake job applicants

We experienced this firsthand just last week. A candidate passed our screening process and even aced a few interviews to get to the final stage of our interview process. But something felt off to our Head of People, so she suggested meeting the candidate in person. That's when the candidate immediately declined and deleted their LinkedIn profile.

We're not alone in this. Gartner predicts that about 1 in 4 job applicants will be fake by 2028, but based on internal data and recent chats with customers, these numbers are very conservative and companies are already seeing hundreds of fake job applicants on a weekly basis. With the pace of innovation in AI, these numbers will only continue to grow.

This is becoming a critical challenge for every hiring team, and traditional screening methods aren't enough anymore.

Why are fraudsters targeting job applications?

Most large companies have systems in place to detect financial fraud and cybersecurity attacks, so attacking hiring processes can give fraudsters an easier way in.

If a fraudster gets hired, they can steal your data and IP, defraud your business and customers, or engage in salary arbitrage by falsely claiming to live in high-cost areas while actually residing somewhere much cheaper.

But the most concerning threats come from organized groups targeting courier and delivery roles to steal valuable goods, and nation-state actors attempting to infiltrate software engineering roles for IP theft and system exploitation.

It's not just traditional fraudsters either. People in the "overemployed" movement are using these same tactics to land multiple remote jobs simultaneously, maximizing their earning potential while deceiving employers about their availability and commitment.

The barrier to entry is shockingly low. In a recent demo we gave to the Merchant Risk Council, we were able to create an entirely automated scam system in 20 minutes, including a fully functional spoofed website of a major retailer. This used to take weeks just to create a bad copy of a website, and now these same AI tools are being applied to job applications.

How to detect a fake job application

While these scams are getting more sophisticated, there are still red flags that can help you spot fake candidates during your hiring process.

1. Watch for resume inconsistencies. Real candidates often have small discrepancies as they update profiles at different times, but fake profiles tend to be either perfectly consistent (because they were created all at once) or have mismatches between employment dates, job titles, and resume gaps.
2. Look for AI-generated content. Resumes created by AI usually have a formulaic structure, overuse certain phrases like "results-driven" or "detail-oriented," and contain an unusual number of em dashes (—). Tools like QuillBot can tell you the likelihood that a resume or cover letter has been written by AI. But be careful not to automatically disqualify these candidates, as many legitimate job seekers use AI tools to improve their resumes, which is different from having everything fabricated.
3. Pay attention during video interviews. Poor video quality isn't always a red flag, but unnatural lighting, lip-syncing issues, or candidates who avoid turning their head can be signs of potential deepfake use. However, these tools are getting a lot harder to detect. Some recent demos show how you can now wave a hand in front of your face, change lighting, and make quick movements without any glitching.
4. Notice behavioral red flags. Be cautious with candidates who are unusually eager to start immediately, accept offers without any negotiation, or act suspiciously when you suggest meeting in person or changing interview formats. Genuine candidates typically have questions about the role, company culture, or growth opportunities.

While these tactics can help, you should know skilled fraudsters can still get around manual detection methods. To spot large scale AI attacks, you’ll want to tie in fraud detection techniques like using device signals to detect injection attacks that spoof webcam footage during live calls, analyzing keyboard and mouse patterns to identify automated or scripted responses, monitoring IP geolocation and VPN usage to verify claimed locations, and tracking browser fingerprinting anomalies that suggest the use of fraud tools or virtual machines.

How Sardine helps detect fake job applicants

After our close call, our engineering and people teams got together during a hackathon to solve this. They built a way to bring our fraud detection right into your existing HR tools.

While hiring managers focus on qualifications and culture fit, we can detect what's happening behind the scenes. Is someone actually in San Francisco like they claim, or are they behind a VPN in another country? Is someone else controlling their screen during the interview? What does their device tell us about the tools they're using?

These signals would have immediately flagged our fake candidate. They spent all that time creating the perfect fake profile, but they couldn't fake the technical fingerprints. We integrate directly with platforms like Ashby, Greenhouse, and Lever, so you get real-time alerts without changing how you work. No friction for real candidates, just protection from the fakes.

One fake hire who gains access to your systems could cost millions in stolen IP, compromised customer data, or regulatory fines. But with the right detection in place, you'll never have to wonder if your next great hire is actually a sophisticated fraudster sitting in another country.

If you’d like to learn more about protecting your hiring process, reach out to us at sardine.ai/contact.