Applicant Identity Verification

$1,500.00

Deep-investigative review of your applicant pipeline. I personally verify the identity, employment history, and risk profile of candidates you flag for closer examination β€” catching what your ATS, your background check vendor, and your ID verification tools cannot.

What corporations are struggling with:

β€’ North Korean IT workers infiltrating Western engineering teams under stolen identities

β€’ Proxy interview fraud β€” one person passes the technical screen, a different person shows up on day one

β€’ AI-generated resumes, cover letters, and interview answers that defeat traditional screening

β€’ Identity theft applicants using real people’s credentials, photos, and employment history

β€’ Money mule recruitment into AP, treasury, and executive-support roles β€” BEC fraud from inside the building

β€’ Voice-cloning and deepfake video interviews that pass live video screens

What I’ll do per candidate:

β€’ LinkedIn profile authenticity verification β€” using the same methodology that produced 54,210 fraudulent-job takedowns and 7,000+ fake-profile removals

β€’ Cross-platform identity consistency check across LinkedIn, GitHub, X, public records, prior employer footprints

β€’ Employment history validation β€” confirming the candidate worked where they claim, in the role they claim, during the dates they claim

β€’ Photo and document forensic review for AI generation, image reuse, and known fraud-pattern markers

β€’ Pattern matching against documented fraud-operator typologies (Talentify network, Panzer network, North Korean IT worker indicators, money-mule recruitment patterns)

β€’ Risk scorecard with confidence interval and specific red flags identified

Deep-investigative review of your applicant pipeline. I personally verify the identity, employment history, and risk profile of candidates you flag for closer examination β€” catching what your ATS, your background check vendor, and your ID verification tools cannot.

What corporations are struggling with:

β€’        North Korean IT workers infiltrating Western engineering teams under stolen identities

β€’        Proxy interview fraud β€” one person passes the technical screen, a different person shows up on day one

β€’        AI-generated resumes, cover letters, and interview answers that defeat traditional screening

β€’        Identity theft applicants using real people’s credentials, photos, and employment history

β€’        Money mule recruitment into AP, treasury, and executive-support roles β€” BEC fraud from inside the building

β€’        Voice-cloning and deepfake video interviews that pass live video screens

What I’ll do per candidate:

β€’        LinkedIn profile authenticity verification β€” using the same methodology that produced 54,210 fraudulent-job takedowns and 7,000+ fake-profile removals

β€’        Cross-platform identity consistency check across LinkedIn, GitHub, X, public records, prior employer footprints

β€’        Employment history validation β€” confirming the candidate worked where they claim, in the role they claim, during the dates they claim

β€’        Photo and document forensic review for AI generation, image reuse, and known fraud-pattern markers

β€’        Pattern matching against documented fraud-operator typologies (Talentify network, Panzer network, North Korean IT worker indicators, money-mule recruitment patterns)

β€’        Risk scorecard with confidence interval and specific red flags identified

Deliverables per candidate:

β€’        Investigation report (PDF) with executive summary and detailed findings

β€’        Risk score: Low β†’ Medium β†’ High β†’ Critical, with the specific evidence behind each tier

β€’        Clear recommendation: Proceed / Proceed with additional verification / Decline

β€’        Screenshots and evidence archive supporting every flag raised

β€’        24–48 hour turnaround on standard cases; rush available

 

Pricing:

  • Single candidate (standard): $1,500

  • Bundle of 5 candidates: $6,000 ($1,200 each)

  • Bundle of 10 candidates: $10,000 ($1,000 each)

  • Bundle of 25 candidates: $20,000 ($800 each) β€” enterprise rate

  • Rush 24-hour turnaround: $3,000 per candidate

  • Executive / C-suite candidate review: $3,500 per candidate

What makes this different:

β€’        Human pattern recognition. ATS systems, background-check vendors (HireRight, Checkr), and ID verification tools (Persona, Jumio, Onfido) catch what is catchable by automation. They miss what is designed to defeat automation. I catch what they miss.

β€’        Built on real fraud-operator pattern data. 54,210 takedowns of upstream fake-employer fraud means I know exactly what the downstream fake-candidate fraud looks like β€” the same operators run both sides.

β€’        Direct deliverable. No portal, no dashboard, no integration project. You send the candidates. I send the report. You make the decision.

 

Deep-investigative review of your applicant pipeline. I personally verify the identity, employment history, and risk profile of candidates you flag for closer examination β€” catching what your ATS, your background check vendor, and your ID verification tools cannot.

What corporations are struggling with:

β€’ North Korean IT workers infiltrating Western engineering teams under stolen identities

β€’ Proxy interview fraud β€” one person passes the technical screen, a different person shows up on day one

β€’ AI-generated resumes, cover letters, and interview answers that defeat traditional screening

β€’ Identity theft applicants using real people’s credentials, photos, and employment history

β€’ Money mule recruitment into AP, treasury, and executive-support roles β€” BEC fraud from inside the building

β€’ Voice-cloning and deepfake video interviews that pass live video screens

What I’ll do per candidate:

β€’ LinkedIn profile authenticity verification β€” using the same methodology that produced 54,210 fraudulent-job takedowns and 7,000+ fake-profile removals

β€’ Cross-platform identity consistency check across LinkedIn, GitHub, X, public records, prior employer footprints

β€’ Employment history validation β€” confirming the candidate worked where they claim, in the role they claim, during the dates they claim

β€’ Photo and document forensic review for AI generation, image reuse, and known fraud-pattern markers

β€’ Pattern matching against documented fraud-operator typologies (Talentify network, Panzer network, North Korean IT worker indicators, money-mule recruitment patterns)

β€’ Risk scorecard with confidence interval and specific red flags identified

Deep-investigative review of your applicant pipeline. I personally verify the identity, employment history, and risk profile of candidates you flag for closer examination β€” catching what your ATS, your background check vendor, and your ID verification tools cannot.

What corporations are struggling with:

β€’        North Korean IT workers infiltrating Western engineering teams under stolen identities

β€’        Proxy interview fraud β€” one person passes the technical screen, a different person shows up on day one

β€’        AI-generated resumes, cover letters, and interview answers that defeat traditional screening

β€’        Identity theft applicants using real people’s credentials, photos, and employment history

β€’        Money mule recruitment into AP, treasury, and executive-support roles β€” BEC fraud from inside the building

β€’        Voice-cloning and deepfake video interviews that pass live video screens

What I’ll do per candidate:

β€’        LinkedIn profile authenticity verification β€” using the same methodology that produced 54,210 fraudulent-job takedowns and 7,000+ fake-profile removals

β€’        Cross-platform identity consistency check across LinkedIn, GitHub, X, public records, prior employer footprints

β€’        Employment history validation β€” confirming the candidate worked where they claim, in the role they claim, during the dates they claim

β€’        Photo and document forensic review for AI generation, image reuse, and known fraud-pattern markers

β€’        Pattern matching against documented fraud-operator typologies (Talentify network, Panzer network, North Korean IT worker indicators, money-mule recruitment patterns)

β€’        Risk scorecard with confidence interval and specific red flags identified

Deliverables per candidate:

β€’        Investigation report (PDF) with executive summary and detailed findings

β€’        Risk score: Low β†’ Medium β†’ High β†’ Critical, with the specific evidence behind each tier

β€’        Clear recommendation: Proceed / Proceed with additional verification / Decline

β€’        Screenshots and evidence archive supporting every flag raised

β€’        24–48 hour turnaround on standard cases; rush available

 

Pricing:

  • Single candidate (standard): $1,500

  • Bundle of 5 candidates: $6,000 ($1,200 each)

  • Bundle of 10 candidates: $10,000 ($1,000 each)

  • Bundle of 25 candidates: $20,000 ($800 each) β€” enterprise rate

  • Rush 24-hour turnaround: $3,000 per candidate

  • Executive / C-suite candidate review: $3,500 per candidate

What makes this different:

β€’        Human pattern recognition. ATS systems, background-check vendors (HireRight, Checkr), and ID verification tools (Persona, Jumio, Onfido) catch what is catchable by automation. They miss what is designed to defeat automation. I catch what they miss.

β€’        Built on real fraud-operator pattern data. 54,210 takedowns of upstream fake-employer fraud means I know exactly what the downstream fake-candidate fraud looks like β€” the same operators run both sides.

β€’        Direct deliverable. No portal, no dashboard, no integration project. You send the candidates. I send the report. You make the decision.