The recruitment landscape has shifted rapidly. Interviews, once regarded as the most reliable stage for candidate verification, are now vulnerable to sophisticated manipulation powered by generative AI. Traditional human evaluation cannot always detect when a candidate is being coached by an AI model or presenting a resume that does not reflect genuine experience.

This challenge is not hypothetical. A 2025 hiring-security study reported that 59 percent of managers have suspected a candidate of using AI tools during interviews, and more than 35 percent encountered cases where someone other than the applicant attended a remote interview. As generative AI grows more accessible, live interview fraud is becoming mainstream.

CrossClassify introduces Live Interview Analysis, an advanced solution that validates resume information against the answers given during the interview, and simultaneously compares behavioral patterns and device fingerprinting signals to detect external assistance or fabricated claims. This gives hiring teams confidence based on data rather than instinct and allows decisions to be made with clarity and defensible evidence.

Modern fraud does not stop at the resume. Agentic AI tools can assist candidates in real time, generating high quality answers with tone and structure that appear natural to human evaluators. In several documented cases, candidates who passed resume screening later showed scripted or AI-generated responses in interviews, even pausing unnaturally to wait for AI output before answering.

Recently, a case reported in industry media involved a deepfake job seeker whose video froze when asked to touch their face, exposing that the person on screen was not the real applicant. Other reports describe organised groups offering "proxy interview services" where a more skilled person or an AI agent attends the interview on behalf of the applicant.

CrossClassify closes this vulnerability by validating interview responses against resume information while monitoring device behaviour to confirm that the interviewee is the true applicant. Inconsistencies between written claims and verbal answers, unusual input behaviour, or signs of proxy participation are surfaced immediately. Verification becomes continuous, active, and measurable.

CrossClassify embeds a verification layer directly into the interview process. It evaluates whether a candidate's answers align with their documented experience, measures reasonability of skill claims, and observes device context to detect external automation. When suspicious patterns appear, the interviewer is notified instantly with supporting evidence and a live fraud score.

The interview is no longer a blind trust environment. It becomes an authenticated truth stage.

The system captures micro-interaction patterns such as typing rhythm, hesitation intervals, mouse movement flow, cursor precision, and response timing. These signals reveal whether answers originate organically from the candidate or are being generated or relayed by an external assistant. Organic human behaviour is naturally irregular and dynamic, while AI supported input tends to follow patterned, consistent timing and mechanical rhythm. This behavioural contrast enables CrossClassify to distinguish genuine interview responses from automated, scripted, or AI-assisted behaviour with high reliability.

Every spoken sentence in the interview is transcribed and matched against the candidate's resume in real time. Through this alignment, the system can detect when an applicant makes claims that do not appear anywhere in their documented employment history, or when verbal skill assertions are unsupported by past experience. It also uncovers contradictions, abrupt shifts, or overstated achievements that indicate fabricated or AI-generated content. As a result, the interview becomes a real time fact verification process instead of a controlled performance, and authenticity is measured through evidence rather than presentation.

CrossClassify references millions of verified career paths to evaluate credibility. It flags unrealistic job progression, unlikely skill pairings, and experience levels that do not align with typical growth timelines.

Device fingerprinting identifies hardware signature, network provenance, behaviour history, and multi-account use. Attempts to mask identity, reuse devices, or route access through VPN chains are flagged instantly.

Interview decisions can now rely on identity anchored, device-verified participation.

Live Interview Analysis does more than compare answers to resumes. It also detects non-human participants and identity obfuscation attempts. Using link analysis, behavioural biometrics, and real time device fingerprint monitoring, CrossClassify identifies bots, deepfake audio or video, remote controlled interview sessions, and impersonation events.

This confirms that the individual answering questions is the authentic applicant, not an AI pipeline or proxy operation behind the camera. Interview integrity is preserved even under advanced adversarial conditions.

• A real time authenticity score with continuous recalculation


• Alerts when verbal answers conflict with resume data


• Indicators of AI assistance, proxy involvement, or device manipulation


• A full integrity and evidence report after the call

CrossClassify stops fraud before it enters the system. Multi-account behaviour, disguised identities, and device farm registrations are detected and blocked. The result is a clean applicant pool before screening or interviews begin.

The system detects and prevents account takeovers and session hijacking. By monitoring live behavioral patterns and device fingerprints, CrossClassify can identify when an unauthorized user attempts to access an applicant or employer account, preventing malicious actors from exploiting the recruitment platform.

Career path analysis, skill relationship modelling, and trajectory review expose fabricated resumes and AI generated profiles. Recruiters reach the interview stage with pre-verified CVs, reducing wasted interview time.

Interview integrity cannot be assumed. It must be verified.

CrossClassify validates spoken answers against resume data, detects real-time AI interference, confirms device authenticity, and protects interviews from automation and impersonation.