Cheaters are a creative bunch, and as exams move online, so do their tactics. Let’s break down some of the most common methods with real-world-style examples—and how to catch them.
Example: Jack is taking an online certification exam. he positions his laptop webcam to show only his face, but just out of view, he got a second monitor displaying a PDF with all the answers. Since the AI proctor only monitors one screen, Jack sails through the test undetected.
Detection: Use software that monitors multiple displays and flags screen mirroring. AI eye-tracking can also help—if a candidate keeps glancing away from the main screen, that’s a red flag.
Example: Jack is great at outsourcing work. He wears a nearly invisible Bluetooth earpiece while his friend (who already passed the exam) feeds him answers in real time. To avoid suspicion, Jake occasionally pretends to think deeply before selecting the right answer.
Detection: Require candidates to show their ears before starting the exam. Random live proctor check-ins can also help, as can audio analysis that picks up whispered conversations.
Example: Priya writes formulas on a transparent tape and sticks it onto her water bottle. During the exam, she casually takes sips while reading her “hydration-enhanced” notes.
Detection: Enforce a clean desk policy and require a full 360-degree room scan before the test begins. AI-powered object recognition could also be trained to detect unusual items in the test environment.
Example: Daniel uses remote-access software like AnyDesk to let his tech-savvy friend control his laptop from another location. While Daniel pretends to be deep in thought, his friend is the one answering all the tough questions.
Detection: Secure browsers can block remote-access programs, and keystroke pattern analysis can help detect when a different person is typing. Sudden changes in typing speed or accuracy are major giveaways.
Example: Emily doesn’t need a friend to help—she’s got ChatGPT. By pasting exam questions into a chatbot and quickly copying the responses, she aces the test while barely lifting a finger.
Detection: Disable copy-paste functionality and monitor test-takers’ activity logs for suspicious behavior, like rapid switching between applications. AI-generated answers also tend to have a distinct pattern that can be flagged.
Example: Mark needs to pass a tough professional licensing exam, so he hires a stand-in who looks like him to take the test. Since the proctor only does a quick ID check, the fraud goes unnoticed.
Detection: Use biometric verification, such as facial recognition and keystroke dynamics. AI can compare live exam footage to ID photos, making it harder to swap test-takers.
AI proctoring is stepping up as the digital watchdog against these crafty cheating methods, using a combination of advanced monitoring techniques to eliminate loopholes.
Example: Alex scribbles key formulas on a piece of paper and tapes it just below his laptop. During the exam, he casually glances down to reference it. Since the webcam is only focused on his face, the notes go unnoticed.
Detection: AI-powered object detection can flag unapproved materials in the testing environment, and a required desk scan before the exam ensures no hidden notes are within reach.
Example: Mia cleverly tilts her webcam slightly upwards so that her monitor is visible but not her hands. While she types, a second person out of the camera’s view whispers answers to her.
Detection: AI proctoring systems track head position and face angles, detecting unnatural movements or attempts to adjust the camera mid-test. If Mia shifts the camera too much, the AI will alert a human reviewer.
Example: Raj places small sticky notes on the edges of his monitor with key terms and formulas. Since they’re just outside the webcam’s view, he can peek at them without suspicion.
Detection: AI-enforced 360-degree room scans before the exam help detect hidden notes. Live AI monitoring also flags excessive head movements that suggest someone is reading from off-screen materials.
Example: Lisa quickly switches to another tab with Google search results whenever a difficult question appears. She then switches back to the exam before the AI proctor notices.
Detection: AI-proctored secure browsers prevent test-takers from opening new tabs, copying/pasting text, or accessing other applications. Any attempt to navigate away is flagged and could lead to immediate disqualification.
Example: Ethan connects a second monitor to his laptop and positions it out of view of the webcam. While his exam runs on one screen, he uses the second screen to look up answers.
Detection: AI-driven screen monitoring detects external displays and prevents the test from running if multiple monitors are connected. A sudden shift in eye movement patterns could also indicate a second screen in use.
Example: Sophia discreetly takes a picture of the exam question with Google Lens and instantly gets a detailed answer. She quickly looks at her phone screen and inputs the response.
Detection: AI-powered test software tracks unusual hand and eye movements. Some proctoring tools also require a mobile phone check before the exam begins and flag any sudden use of external devices.
Example: Tom plugs in a wireless external keyboard, giving control of his laptop to a friend in another room. The friend types answers while Tom pretends to be working.
Detection: AI-based keystroke dynamics analyze typing speed and rhythm. If the system detects a sudden change in typing patterns, it flags the activity for review. Secure testing browsers also block unauthorized peripherals.
Example: Jake places his smart speaker (like Alexa or Google Assistant) nearby. Whenever he encounters a tough question, he subtly whispers, “Hey Google, what’s the capital of…” and listens for the answer.
Detection: AI audio monitoring detects unusual background noises, including robotic voice responses. Some proctoring systems require test-takers to be in a silent room with no background voices present.
While AI isn’t perfect, it’s making cheating significantly harder and riskier. The best AI proctoring systems don’t just rely on automation—they also integrate human review to minimize false flags and ensure fairness. By combining secure test environments, behavioral monitoring, and bio-metric authentication, AI is making exams more cheat-proof than ever before.
That said, the real challenge is staying ahead of the next wave of fraud tactics. Because if history tells us anything, it’s that for every security measure, there’s always a cheater trying to outsmart it. The question is: will AI always be one step ahead?
From hidden devices to AI-generated responses, exam cheating is evolving fast—but so are the methods to detect it. The key is a combination of AI surveillance, human oversight, and smarter exam design. If assessments don’t adapt, cheaters will always find a way to stay ahead.
Have you encountered any of these tricks before? Or maybe even seen a new one in action?