What Is Interview Fraud?

The categories hiring teams actually face

It helps to separate interview fraud into categories, because each one is defeated by a different control. This is written for defenders: the point is to recognise what a category looks like from the reviewer's side, not to describe how any of it is carried out.

Categories overlap in practice. A single session can involve an assistant on the same machine and a second person off camera, which is exactly why correlated evidence beats any single signal.

• Identity substitution: a different person sits the interview or assessment than the one hired.
• Proxy assistance: another person supplies answers off camera, through chat, audio, or remote control of the machine.
• Real-time AI assistance: a desktop assistant or overlay produces answers on the candidate's own screen.
• Environment manipulation: virtual machines, screen-capture exclusion, or secondary devices used to hide the assistance layer.
• Credential and history misrepresentation, which sits alongside session fraud rather than inside it.

Why browser-based tools cannot see the assistance

Browser extensions and lockdown browsers observe the page, the tab, and often the webcam. Their visibility ends where the browser process ends, and that is precisely where modern AI assistance lives.

Desktop assistants and answer overlays render above every other window, are frequently excluded from screen capture and screen sharing, and never interact with the assessment tab. Remote-control tools, virtual machines, injected keyboard input, and a second device off camera are equally invisible from inside the browser.

• Native overlay applications draw over the assessment and are often excluded from screen share.
• Remote-access tools allow another person to drive the machine with no browser-visible trace.
• Virtual machines let the assessment run inside a controlled environment with helpers outside it.
• Injected or synthesized keyboard input can enter answers that were never physically typed.
• A second phone, tablet, or monitor off camera leaves nothing at all in the browser.

What device-level detection observes

Reliable detection has to happen at the layer where assistance runs: the operating system. ScreenComply pairs a browser-based API with an optional desktop agent that inspects the environment around the assessment rather than only the page inside it.

The agent enumerates running processes and browser extensions against a maintained list of AI assistants and answer overlays, looks for always-on-top or transparent windows, detects remote access and virtualization, enumerates connected displays from the operating system, verifies that keyboard input originates from local physical hardware, and records focus changes, clipboard events, and typing-cadence patterns.

No detection system catches everything, and ScreenComply does not claim otherwise. The objective is corroborating, timestamped evidence that lets a human reviewer make an informed and defensible decision.

• Process and extension enumeration against a maintained AI-assistant list.
• Overlay, transparency, and always-on-top window detection.
• Remote access, virtual machine, and screen-capture driver detection.
• Display enumeration reported by the operating system, not inferred from gaze alone.
• Input-source integrity, clipboard events, and typing-cadence analysis.

Why this matters commercially and legally

A candidate hired on someone else's performance is expensive in ramp time, re-hiring, and in regulated settings, in audit exposure. At the same time, accusing a candidate without evidence carries its own legal and reputational risk.

The practical answer is documentation. Consistent, timestamped session evidence applied uniformly to every candidate lets a hiring team act on a real finding and, just as importantly, clear a candidate who was flagged by a weak signal.

Turning signals into a report someone can defend

A detection is only useful if it can be explained to a person who was not in the room. Every session produces a structured integrity report: an executive verdict with a graded risk level, a chronological evidence timeline, and the underlying signal detail behind each entry.

Language is deliberately factual rather than accusatory, because the institution or employer makes the decision, not the software. Reports export to PDF and can be shared through a secure link for academic-integrity hearings, HR reviews, and compliance audits, with configurable retention including zero-retention operating modes.