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Candidate cheating covers any attempt by an applicant to gain an unfair advantage during an interview or assessment, from a quiet second monitor with answers open to a full proxy test taker completing the exercise on someone else’s behalf. It is not a new problem, but the tools available to candidates who want to cheat have changed considerably in a short time. Generative AI now lets a candidate have a live model whispering suggested answers in one ear while they talk to a recruiter in the other, a dynamic serious enough that Gartner’s own candidate survey found 6% of respondents admitting to some form of interview fraud already, with the firm projecting the fake and misrepresented candidate problem to keep growing through 2028 (Gartner, July 2025).
This guide covers the most common ways candidates cheat today, the AI driven tactics that have emerged most recently, the signs worth watching for, and the layered approach that catches most of it before an offer goes out.
The core behavior, wanting an unfair edge, has not changed. What has changed is how cheap and how convincing the tools for it have become. A candidate no longer needs a coached friend on a second phone, a browser tab with an AI assistant can generate a plausible, contextually relevant answer to almost any interview or coding question in seconds, and it can do so quietly enough that a distracted interviewer may never notice the telltale pause.
This is exactly the shift that has pushed leading academic research on exam integrity to focus specifically on multimodal detection, analyzing eye movement, head posture, and typing patterns together rather than any single signal, since a single behavioral cue is no longer enough on its own to catch AI assisted cheating reliably (systematic review, Discover Education).
Proctor the sessions that matter. AI proctoring monitors video, audio, and browser activity throughout an assessment or interview, catching a second voice, an unauthorized tab, or a suspicious pause pattern without requiring a recruiter to watch every second personally. Glider’s own breakdown of how candidates cheat in hiring assessments covers the specific tactics proctoring is built to catch in more depth, and Auto Proctoring: How It Works to Ensure Candidate Genuineness explains the automated detection layer itself.
Confirm identity, more than once. Proctoring answers “is this person cheating,” identity verification answers the equally important “is this even the right person,” and Glider’s ID Verify is built to reconfirm that at multiple points in the funnel rather than only once at the start.
Design assessments that are harder to cheat on by nature. Open ended, applied problems that ask a candidate to reason through a scenario out loud are considerably harder to fully outsource to an AI tool than a static multiple choice test, which is part of why structured, adaptive skill assessments and scored live interviews hold up better than a resume review alone.
Bring the signals together. A proctoring flag, an identity mismatch, and an assessment score are each partial evidence on their own, viewing them together in one Candidate 360 profile makes the full pattern far easier to see than checking each system separately.
Candidate cheating has not become more common because people have become less honest, it has become easier because the tools to do it convincingly are now sitting in a free browser tab. The response is not to abandon remote hiring, it is to build a process, proctored assessments, verified identity, and applied skills testing, that assumes some candidates will try, and is designed to catch it calmly and consistently when they do.
Candidate cheating includes proxy test taking, having someone else feed answers during a live interview or assessment, using unauthorized resources like search engines or AI tools during a timed test, and misrepresenting credentials or experience to pass an earlier stage of the process.
Common methods include a second monitor or device displaying answers, screen sharing with another person, unauthorized browser tabs open to search engines or AI chat tools, and having someone else complete the assessment entirely on the candidate’s behalf.
Some candidates run a generative AI tool alongside a live interview or coding assessment and read or paraphrase its suggested responses in real time, a tactic that produces unnaturally polished or generic sounding answers paired with telltale pauses.
Warning signs include long pauses before smooth answers, eyes repeatedly shifting to one part of the screen, generic sounding responses to personal questions, and a noticeable gap between assessment scores and live explanation ability, and AI proctoring can flag many of these signals automatically.
AI proctoring significantly reduces the opportunity for cheating by monitoring video, audio, and browser activity throughout a session and flagging suspicious patterns for human review, though it works best combined with identity verification and well designed, applied assessments rather than as a standalone solution.
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