Case Library / Agentic AI Attacks (AI-Powered Social Engineering) / Deepfake Candidate Interview Fraud at Vidoc Security Lab (Polish-Founded/US-HQ, 2024-2025)

Deepfake Candidate Interview Fraud at Vidoc Security Lab (Polish-Founded/US-HQ, 2024-2025)

Vidoc Security Lab, a Polish-founded, US-headquartered cybersecurity startup, caught two separate job candidates using real-time AI deepfake video filters to disguise their identity during technical interviews for a Poland-based remote role, and suspected, based on matching vocal accents and one persona's oddly over-rehearsed answers, that both fake personas were run by the same operator.

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Reviewed by the Social Engineering Examples team.

What Happened

Vidoc Security Lab, a Polish-founded, US-headquartered remote-first startup building AI-assisted code security tools, was targeted twice within about two months (roughly December 2024 and 2025-02-04) by job applicants who used real-time deepfake/AI face-filter technology to disguise their real identity during video interviews for an open, Poland-based remote backend engineer role. In the first case, a candidate using the name "Makary Krol" and claiming a Polish background passed resume screening, an HR call, and a full technical coding interview (finishing faster and more completely than any prior candidate) before cofounder Klaudia Kloc grew suspicious in the final non-technical interview: he could not speak any Polish despite the claimed background, and his personal details didn't hold up. In the second case, a candidate using the name "Bratislav Rakočević" and claiming a Serbian background had spent weeks building rapport with the cofounders via LinkedIn before a role opened. During the live technical interview, cofounder Dawid Moczadło noticed the on-camera face looked artificial and didn't match the candidate's LinkedIn photo, and that answers sounded like scripted, ChatGPT-style bullet points. Moczadło recorded the call and asked the candidate to place a hand in front of his face, a liveness test real-time deepfake filters typically cannot render, which the candidate refused, exposing the fraud on camera. Post-incident analysis showed the synthetic face resembled Polish politician Sławomir Mentzen, and Vidoc noted both personas shared a similar strong accent despite differing claimed nationalities, leading the company to suspect a single operator (or coordinated group) was behind both attempts, and possibly similar attempts at many other companies. Vidoc publicized both incidents (blog postmortem, 2025-03-27) and the story was independently reported in depth by The Pragmatic Engineer newsletter (2025-03-11, based on a direct interview with cofounder Dawid Moczadło) and by The Register and other outlets.

How the Attack Worked

Both fraud attempts followed Vidoc's normal remote hiring funnel: resume/CV screening, a 15-30 minute HR/operations screening call, a hiring-manager or technical coding interview, and a final non-technical interview. In case 1 ("Makary Krol," claiming a Polish background and a Warsaw University of Technology degree), the candidate had a polished, convincing CV and LinkedIn profile, spoke broken English with a strong accent flagged internally as unusual but not disqualifying, and became the first candidate in the hiring process to complete the entire timed 2-hour coding interview (including follow-up questions) with time to spare. He passed resume screening, the HR call, and the technical/hiring-manager interview. Suspicion only crystallized in the final, non-technical interview with cofounder Klaudia Kloc, when he was unable to speak any Polish despite claiming to have grown up and studied in Poland, and gave inconsistent answers about his background, timezone, and former employers. The interview was ended and no offer was made; this session was not recorded, so Vidoc had only notes, not video proof. In case 2 ("Bratislav Rakočević," claiming a Serbian background), the candidate had built rapport over weeks via unsolicited, polite LinkedIn messages before a role opened, and had a LinkedIn profile with real mutual connections at companies he claimed to have worked for. He first tried to skip video ("camera not working") before joining on camera for the technical interview with cofounder Dawid Moczadło. Dawid immediately noticed the on-screen face looked artificial and mismatched the LinkedIn photo, the speech pattern resembled read-aloud, ChatGPT-style bullet points, and there was audio-video lag consistent with a real-time face-swap/deepfake filter. Dawid deliberately kept the candidate talking, started recording, and then asked the candidate to place a hand in front of his face, a simple liveness test most real-time deepfake filters cannot render correctly. The candidate refused, exposing the ruse, and Dawid ended the call. Later frame analysis showed the synthetic face closely resembled Polish politician Sławomir Mentzen. Vidoc's postmortem noted both personas shared a similarly strong, Asian-sounding vocal accent despite claiming different nationalities (Polish vs. Serbian), and that the second persona's answers felt over-rehearsed, as if the operator had already been through Vidoc's specific interview sequence before; this was the basis for the company's suspicion that one operator (or coordinated group) ran both personas, and possibly many more against other employers.

The Lure & the Tell

Lure: two well-groomed fake personas, "Makary Krol" (claimed Polish, Warsaw University of Technology grad) and "Bratislav Rakočević" (claimed Serbian), each backed by a convincing CV, an active LinkedIn profile with real mutual connections, and strong-to-exceptional live coding performance, including being the fastest candidate ever to finish Vidoc's full 2-hour timed coding interview. The second persona had spent weeks building LinkedIn rapport with the cofounders before any role was even open. Tell: in case 1, the candidate claiming Polish nationality/education could not speak a word of Polish, and his biographical answers (timezone, past employers, schooling) didn't hold together under casual conversational questioning in the non-technical final round. In case 2, the interviewer noticed an artificial-looking face mismatched to the LinkedIn photo, ChatGPT-style scripted answers, and audio/video lag; when directly asked to place a hand in front of his face, a simple test that breaks real-time face-swap filters, the candidate refused, immediately exposing the deception. Vidoc also flagged the second persona's oddly overconfident, seemingly pre-rehearsed answers as if he'd already been through this exact interview flow, feeding the suspicion both personas were run by the same operator.

Outcome

Neither impostor was hired or paid. The first candidate ("Makary Krol") was quietly rejected after the final interview raised unresolvable doubts, but the encounter was not recorded, leaving Vidoc with only notes. The second candidate ("Bratislav Rakočević") was caught on a recorded call after refusing a hand-over-face liveness test; cofounder Dawid Moczadło ended the interview and later published the recording publicly. Vidoc added a mandatory in-person (or strictly ID-verified, filter-free) final interview round to its hiring process, published a free ebook titled "Deepfake Fraud Prevention: 17 Practical Strategies to Detect Fake IT Workers" (title confirmed directly on Vidoc's own blog post) on detecting fake IT workers, and went public with both incidents via a company blog postmortem (2025-03-27) and a Pragmatic Engineer newsletter deep-dive (2025-03-11) based on an interview with Moczadło. Vidoc reported being contacted afterward by dozens of other startups and larger tech firms describing similar experiences, some only discovering the deception after already hiring the person, suggesting a widespread, possibly coordinated campaign rather than an isolated incident.

Why It Matters

This is one of the earliest and most thoroughly documented first-party case studies of real-time deepfake video filters being used offensively against a company's own hiring process, rather than against a bank or help-desk. It demonstrates that a candidate can pass CV screening, an HR screen, and even a rigorous, timed technical coding assessment while wearing an AI-generated face, meaning technical competence alone is not proof of identity, and that standard video-interview trust assumptions (a face on screen, an accent, a claimed home country) can all be faked concurrently. It also surfaces the broader pattern, echoed by dozens of companies who contacted Vidoc afterward and independently reported in the West in connection with fraudulent North Korean overseas IT-worker schemes, that fully remote hiring pipelines at software companies are being probed at scale by fraudulent-identity operators, with security/access-sensitive employers (like a code-security startup) especially high-value targets if a fake hire succeeds.

Defenses

Vidoc's and Pragmatic Engineer's recommended/adopted mitigations: (1) require candidates to disable all video filters/backgrounds and verify this visually at interview start; (2) record all interviews, including early screening calls, to preserve evidence and allow frame-by-frame review; (3) use an active "liveness" challenge mid-interview, e.g., asking the candidate to place a hand in front of part of their face, which breaks most real-time face-swap filters because the algorithm cannot render the occlusion correctly; (4) cross-check claimed nationality/background against basic cultural and language fluency (e.g., ask a claimed native speaker to answer in that language); (5) verify timezone, previous-employer, and biographical details for internal consistency; (6) add a mandatory in-person (or at minimum, live unfiltered, ID-verified) final round before extending any offer, which Vidoc adopted after these incidents; (7) require formal ID/notarized identity verification prior to onboarding, especially for full-remote hires; (8) treat unusually fast/flawless completion of timed technical assessments combined with weak conversational depth as a correlated red flag rather than assessing coding and communication independently. Vidoc later published a free ebook titled "Deepfake Fraud Prevention: 17 Practical Strategies to Detect Fake IT Workers," confirmed directly on the company's own blog post, based on this experience.

Sources
  • Fake Engineer - Advanced Deepfake Fraud and How to Detect It. Vidoc Security Lab (company blog) Primary. First-party company postmortem, published 2025-03-27, written by the cofounders describing both incidents directly. Verified live and content-matched: confirms both incidents, the hand-in-front-of-face liveness test, the Sławomir Mentzen face match, and the exact ebook title 'Deepfake Fraud Prevention - 17 practical Strategies to Detect Fake IT Workers.'
  • AI fakers exposed in tech dev recruitment: postmortem. The Pragmatic Engineer (Gergely Orosz) Primary. Deep-dive published 2025-03-11 based on a direct interview with Vidoc cofounder Dawid Moczadło; includes the hiring funnel data and step-by-step recruitment timeline. Verified live and content-matched: confirms 'Makary Krol' name, Warsaw University of Technology claim, 500-application funnel, and the $600K 2023 / seed-round-in-2024 funding narrative.
  • WTF, developer used AI to alter his appearance during a technical interview with me. LinkedIn / Dawid Moczadło Primary. Original public post (dated 2025-02-04) with the recorded video of the second incident. Verified live and content-matched: post date and content (ChatGPT-style answers, AI-altered appearance) confirmed.
  • Story of how an AI-generated Polish politician came to our coding interview. LinkedIn / Klaudia Kloc Primary. Cofounder's own account corroborating the incident and the Sławomir Mentzen face-match detail. Verified live and content-matched (post dated 2025-02-27).
  • I'm a security expert and I almost fell for this IT job scam. The Register Secondary. Independent reporting corroborating and contextualizing the incident, including the suspected North Korean IT-worker scheme linkage and the DOJ's cited $88M DPRK IT-worker scam figure. Verified live and content-matched; confirms Vidoc's San Francisco HQ (not Palo Alto).
  • How to Tell If Your Job Candidate is an AI Deepfake. Inc. Secondary. Secondary coverage summarizing detection lessons drawn from this case, including a direct quote from Moczadło. Verified live and content-matched.
  • Vidoc Security Lab secures $2.4M investment from Top Silicon Valley VCs. AIN.ua Secondary. Corroborates the seed round as $2.4M, announced October 2024 (not $2.5M/August 2024 as recalled in the Pragmatic Engineer interview), from Pebblebed, Firestreak Ventures, XFactor Ventures, and 500 Emerging Europe; also confirms Polish founders. Verified live and content-matched.
  • Cytowski & Partners and Kondracki Celej Advise on Vidoc Security Labs' USD 2.4 Million Seed Financing Round. CEE Legal Matters Secondary. Legal-deal reporting corroborating the $2.4M figure and describing Vidoc as Gdańsk-based (legal entity) working with Palo Alto-based lead investor Pebblebed. Verified live and content-matched; this source is the origin of the corrected finding that Palo Alto refers to the investor, not to Vidoc itself.
Attack Chain & Defense
The sequence the attacker ran
How it could have been stopped
1
Reconnaissance and target selection: the operator(s) likely used OSINT sources such as LinkedIn, company blogs, and funding-announcement coverage (Vidoc's $2.4M raise was publicly reported in October 2024) to identify Vidoc as an early-stage, security-focused, fully remote employer actively hiring for a Poland-based backend role, consistent with reporting that these schemes target companies with valuable IP and permissive remote-hiring processes.
Countering Stage 1: public hiring and funding announcements are hard to suppress without harming legitimate recruiting and PR, so the realistic control is not hiding this exposure but hardening the interview process a well-researched applicant will eventually reach.
2
Persona and asset fabrication: the operator(s) built fabricated candidate identities, including a polished CV, an active LinkedIn profile with real mutual connections, and a real-time deepfake/face-swap video filter, likely assembled using commercially available or open-source face-swap tools plus AI-assisted writing for CVs and application materials matched to the job requirements.
Countering Stage 2: vet claimed credentials and employment history against independent, hard-to-fake signals, for example contacting claimed former employers directly, since a convincing profile and mutual connections are not proof of a real underlying identity.
3
Unsolicited rapport-building (second persona specifically): per Vidoc's account, this persona spent weeks sending polite, unsolicited LinkedIn messages to the cofounders before any role was open, pre-establishing familiarity that made the later application feel less like a cold approach.
Countering Stage 3: treat unsolicited pre-role networking from unknown accounts as a neutral signal rather than a trust signal, and apply the same verification steps to warm leads as to cold applicants regardless of prior rapport.
4
Application and initial screening: fabricated CVs were submitted through Vidoc's normal job posting, and both personas passed a 15-30 minute HR/operations phone screen, exploiting the fact that early-stage screens are typically audio-only or low-friction and not designed to catch identity fraud.
Countering Stage 4: add a lightweight identity-consistency check at the first live conversation, such as easily-verified biographical or cultural questions tied to the claimed background, rather than treating early screens as pure skills gates.
5
Technical assessment: both personas performed strongly in live, timed coding interviews, in one case finishing faster and more completely than any prior candidate, using genuine or AI-assisted technical skill to build interviewer confidence ahead of the higher-scrutiny final round.
Countering Stage 5: score technical performance and communication/identity signals independently rather than letting a strong coding result offset unresolved identity doubts, and treat unusually flawless completion paired with weak conversational depth as a correlated red flag.
6
Real-time video concealment: candidates joined video interviews using a real-time deepfake/face-swap filter, in one case first attempting to avoid camera use entirely by claiming a broken camera or connection before eventually joining with the filter active.
Countering Stage 6: require candidates to disable all video filters and virtual backgrounds and visually confirm this at the start of every video interview, and treat camera-avoidance excuses at the video stage as a reason to slow down rather than proceed.
7
Live deception under questioning: candidates gave scripted, ChatGPT-style bullet-point answers, and Vidoc's postmortem noted a similarly strong accent across two differently-claimed nationalities plus audio-video lag consistent with real-time face-swap processing.
Countering Stage 7: record all interviews, including early screening calls, so unusual speech patterns, accents, and audio-video lag can be reviewed frame-by-frame rather than relying on an interviewer's in-the-moment impression alone.
8
Detection via liveness challenge: Vidoc's cofounders directly asked candidates to place a hand in front of their face, a simple occlusion test that most real-time deepfake filters cannot render correctly; both personas failed or refused this test, exposing the fraud before any hire was made.
Countering Stage 8: build an active liveness challenge, such as a hand-over-face or unexpected lighting/angle change, into every final-round video interview as a standard, non-negotiable step rather than an ad hoc response to suspicion.
9
Intended objective (not achieved): had either persona passed undetected, the goal was consistent with fraudulent employment, meaning securing an offer and onboarding to draw a salary under a false identity, with the added risk at a security company of gaining codebase/production access that could enable IP theft, backdoor insertion, or, per suspected DPRK-style overseas IT-worker schemes cited in reporting, sanctions-evasion revenue.
Countering Stage 9: gate final onboarding on formal, ID-verified, in-person or live-unfiltered confirmation of identity before extending any offer or provisioning codebase/production access, which Vidoc adopted as a mandatory step after these incidents.
Quick Facts
Victim
Vidoc Security Lab, a San Francisco-headquartered, Polish-founded, remote-first, AI-assisted code-security startup (also operating a Polish legal entity, VIDOC SECURITY LAB SP. Z O.O., registered in Gdańsk) cofounded by Dawid Moczadło and Klaudia Kloc (formerly ethical hackers/bug-bounty researchers), which had raised a $600K pre-seed/seed round in 2023 and a further $2.4M seed round in October 2024 (from Pebblebed, Firestreak Ventures, XFactor Ventures, and 500 Emerging Europe) and was hiring backend engineers for a Poland-based remote role at the time of both incidents.
Location
San Francisco, USA (Vidoc Security Lab's company HQ, confirmed by the company's own LinkedIn page and multiple company-data sites; a Palo Alto address belongs to lead investor Pebblebed, not to Vidoc itself) and Gdańsk, Poland (its Polish legal entity, VIDOC SECURITY LAB SP. Z O.O.; the company was Polish-founded by Dawid Moczadło and Klaudia Kloc). The open backend-engineer role being hired for was a Poland-based remote position. Fake candidates claimed to be located in Poland and Serbia respectively.
Date
First incident: approx. December 2024 (exact date not published in primary sources). Second incident: 2025-02-04 (per Dawid Moczadło's LinkedIn post). Vidoc Security Lab's own postmortem blog post published 2025-03-27; The Pragmatic Engineer newsletter deep-dive published 2025-03-11 (based on interview with cofounder before the blog post went up).
Impact
No confirmed direct financial loss: neither fake candidate was extended an offer or paid a salary, and no funds were transferred. Costs were operational and opportunity costs: recruiter and cofounder interview time, disrupted hiring funnel for a role sourced from roughly 500 applications, and the reputational and security risk that would have materialized had either impostor been hired into a codebase-access engineering role at a security company. No dollar figure has been published by any source.
Status
Confirmed
Case Type
Real-World Incident
Sector
Cross-Sector / Multiple Industries, Cybersecurity Industry, Technology & Software
Threat Actor
Unaffiliated Individual
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