Is CourseCheetah Detected? Honest Answer

What "detected" actually means

Most students searching this question are worried about one of three things: Canvas itself flagging the extension, an instructor reviewing the quiz log and seeing something unusual, or webcam-based proctoring catching some visible behavior.

CourseCheetah is designed around the fact that detection in all three is behavioral, not technical. There's no scanner that detects the extension itself. There's no fingerprint that says "this student is using AI." What gets flagged is the visible activity that comes with most cheating methods.

Does Canvas detect CourseCheetah directly?

No. Canvas doesn't run an extension scanner. The platform records what happens inside its own page — what questions you viewed, when you answered, when you switched tabs. That's the entire surveillance surface. CourseCheetah operates inside that page (it's a content script that runs in the Canvas tab) and doesn't trigger any of the events Canvas writes to the quiz log.

Does the Canvas quiz log show anything unusual?

No. The quiz log records "stopped viewing the quiz" every time browser focus leaves the quiz tab. Tab switches, alt-tabs, window switches — all logged. Because CourseCheetah keeps you on the same Canvas page (the answer appears on the question itself), no focus loss happens, no event fires.

An instructor pulling your quiz log sees what an instructor would expect: started the quiz, viewed each question in order, answered each one, submitted. No anomalies.

Does it work under webcam proctoring?

Generally, yes. Webcam-based monitoring flags students for visible behavior — looking down at a phone, gaze drifting to a second monitor, talking out loud, unusual mouse motion. CourseCheetah produces none of those. The answer is on the question; your eyes stay on the question; your mouse moves like a normal student's.

Caveats worth being honest about:

• Time-on-question patterns matter. Even with the answer in front of you, finishing a 30-question hard exam in 90 seconds will look suspicious. Pace yourself to ~10–15 minutes regardless.
• Some screen-recording proctoring tools record everything. If your school uses screen recording with manual instructor review of every session, an instructor scrubbing your video could see CourseCheetah's UI. This is an unusual review depth and most institutions don't do it.
• Locked-browser exam tools block Chrome extensions. If your school uses a locked-browser tool for an exam, Chrome extensions don't run inside its window. CourseCheetah requires regular Chrome to function, so those sessions are an exception.

The mechanism: Privacy Guard

The reason there's nothing for Canvas to log isn't magic — it's a feature called Privacy Guard. When enabled, six browser-level protections sit between Canvas and the events it would normally write to the quiz log:

• Visibility API Override — blocks Canvas's tab-leave detection at the browser API level.
• Focus Event Intercept — prevents focus-loss and blur tracking from firing.
• Page Hide Suppression — suppresses the page-hide events Canvas listens for.
• Mouse Leave Protection — blocks mouse-exit detection.
• iframe Communication Shield — secures cross-frame messages so iframed quiz content can't leak signals.
• Activity Heartbeat Spoof — simulates the continuous activity Canvas expects from a focused student.

Together these don't "hide" your activity after the fact — they intercept the events before Canvas can write them. The log on your professor's screen looks identical to a focused student's because, from Canvas's perspective, you were a focused student.

Has anyone been caught using it?

Honestly: caught for what? CourseCheetah doesn't leave a behavioral trail to catch. The cases where students get flagged for using any AI tool are usually behavioral: tab switches in the quiz log, time mismatches, webcam anomalies. CourseCheetah neutralizes all three. We have not seen credible reports of detection through the extension itself.

The honest framing: CourseCheetah dramatically reduces detection risk by removing the behaviors that produce the signals. It doesn't make you invisible to a school's academic integrity office if your final exam essay reads like ChatGPT and you submitted it 3 minutes after the quiz opened. Pace yourself, edit submissions, behave like a focused student.

Compared to other approaches

Detection risk by method, ordered worst-to-best:

1. Tab-switch to ChatGPT — log records every switch, easy to flag.
2. Phone notes — clean log but webcam catches head movement.
3. Second monitor — gaze drift on camera; some proctors block at startup.
4. Tab-cloak extensions — clean log but you still have to look somewhere for the answer.
5. CourseCheetah — clean log, eyes on screen, no audio, no second device.

The bottom line

CourseCheetah is hard to detect because there's nothing for the standard Canvas + proctoring stack to detect. The extension lives inside the Canvas page, generates the answer locally to you, and surfaces it where you're already looking. None of the standard detection vectors fire.

That's not the same as "you can do anything and never be caught." Pace your answers, edit before submitting, behave normally on camera. Combined with those basics, the detection risk is as low as anything in this category gets.