Detect the tools. Protect the results.
CounterAI™ cheating detection built for what comes next
CounterAI™ helps identify AI-assisted cheating through behavior-based detection, contextual review, and human-verified evidence, so your program can respond defensibly while staying ahead of evolving threats.
Our approach to AI cheating detection
Detect AI misuse without chasing every new tool
AI cheating is not static. Tools evolve and adapt quickly, which makes tool-by-tool detection difficult to sustain. CounterAI™ focuses on how AI misuse shows up during an assessment: unusual behavior, evasion attempts, interaction patterns, and risk signals that are evaluated in context.
Detects behavior patterns associated with AI assistance
Blocks or interrupts unauthorized use of AI assisted apps that may compromise the integrity of your assessments when risk is identified
Evaluates flagged activity with human review before outcomes are confirmed
Why Behavior detection matters
AI-assisted cheating changes quickly. New apps, extensions, copilots, and renamed tools can appear faster than detection lists can be updated. A sustainable approach looks beyond the tool itself and identifies how someone is attempting to evade oversight.
CounterAI™ is designed to recognize patterns of AI misuse, probing, and external assistance, helping your program stay ahead of new threats without depending on a constantly changing catalog of tools.
Built on security doctrine
A holistic security approach to AI cheating detection
CounterAI™ operates within Integrity Advocate’s broader security-based proctoring framework, where multiple controls work together to prevent, detect, evaluate, and respond to risk. That means AI cheating signals are considered alongside behavioral, environmental, and situational context.
Deterrence
Visible oversight discourages misuse before it starts.
Situational awareness
Behavioral baselining helps separate normal activity from meaningful risk.
Counter-surveillance
Evasion behaviors are detected, even when tools are renamed or disguised.
Proportional response
Actions are matched to risk, helping avoid unnecessary escalation.
Evidence-based outcomes
Decisions are documented, explainable, and ready for review.
Download the Security Based Proctoring Ebook
Learn how CounterAI™ fits into a broader integrity framework.
OUR HUMAN APPROACH
AI can flag risk. Human review applies the context
Automated detection can identify suspicious patterns, but it cannot fully understand intent, context, or the surrounding assessment environment on its own. Integrity Advocate adds trained human review to every CounterAI™ flag, helping ensure decisions are based on corroborated evidence rather than isolated signals.
A real person confirms what happened, applies program rules, and documents the decision, giving test takers a fair process and your organization a defensible record.
ADVANCED SECURITY OPTIONS
Layered protection for higher-risk assessments
CounterAI™ works alongside additional security controls that reduce opportunity, capture context, and help reviewers understand what happened during the assessment.
Onscreen content protection
Blocks risky on-screen actions, like copying, printing, and shortcuts that could enable cheating or content theft, keeping test content secure throughout the exam.
Room scan
Before the exam begins, test-takers pan their camera to show their workspace, confirming there are no unauthorized materials while minimizing extra personal data captured.
Second camera
An optional second camera provides a wider view of the testing space for high-stakes exams, adding another layer of oversight without disrupting the test-taker’s experience.
HOW WE COMPARE
Three approaches to AI cheating detection, only one is built for context
Tool lists and lockdown browsers can help, but they often miss the bigger picture. Integrity Advocate combines behavioral detection, layered controls, human review, and audit-ready evidence.
END-TO-END WORKFLOW
From AI risk signal to human-verified outcome
Every flagged event follows a connected review process that combines detection, context, evidence, and human judgment; creating a secure, time-stamped record your program can rely on for appeals, audits or compliance reporting.
Identity verified first
The assessment begins with identity verification, helping confirm the right person is in the session.
Session proctored and monitored
Monitoring establishes context across behavior, attention, navigation, environment, and interaction patterns.
AI and risk detection in real time
CounterAI™ identifies signals of unauthorized AI assistance, evasion, or suspicious interaction patterns.
Audit-ready, human-verified record
A trained reviewer evaluates the evidence, confirms the outcome, and creates an audit-ready record.
TRUSTED BY PROGRAMS WORLDWIDE
Programs worldwide rely on Integrity Advocate for outcomes that are fair, trustworthy, and defensible
Over 10 million sessions proctored, zero breaches in 12+ years, 98% client retention, and the #1 spot on G2 for ease of use.
WHAT OUR CLIENTS SAY
“The technology and artificial intelligence—I don't want to say changes daily, but I'd be joking if I didn't say it wasn't. And the Integrity Advocate team is responsive, is good at teaching us the ropes about what to look for, is constantly updating their system.”
AI cheating detection you can actually stand behind.
Every flag reviewed by a real person. No installs. Zero breaches in 12 years. See how Integrity Advocate works and what it means for your program.
10M+
Total sessions proctored
65+
Languages supported
98%
Client retention rate
Resources on AI cheating detection
Explore our latest educational resources and industry insights on AI-assisted cheating and assessment security.
What Defensible Assessment Looks Like in 2026
April 7, 2026
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3
min read
AI tools have changed what cheating looks like, and most proctoring systems were built for a different problem. This post covers why an automated flag alone can't defend an outcome, and what a defensible assessment record requires in 2026.
Integrity vs. Surveillance: Is Your Proctoring Tool Monitoring Learners or Surveilling Them?
July 2, 2024
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4
min read
There is a meaningful difference between monitoring and surveillance in online proctoring, and most programs have not thought carefully about which one they are actually doing. Monitoring confirms identity, verifies participation, and produces a defensible result. Surveillance collects everything it can, flags anything it does not recognize, and leaves programs to sort out the noise. This post draws that distinction clearly, explains what privacy-first proctoring actually looks like in practice, and makes the case for why human review is the only thing that makes an assessment result genuinely defensible when it is challenged.
Most Proctoring Tools React to Cheating. This Approach Prevents It.
July 9, 2026
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2
min read
Most proctoring platforms are built to detect cheating after it happens. Integrity Advocate's security-based framework is designed to prevent it through deterrence, proportional response, and human-reviewed evidence, with Counter-AI as one component of a broader system built to adapt as threats evolve. This post introduces the framework and links to the full white paper.
Preguntas frecuentes
Encuentra respuestas a las preguntas más frecuentes de nuestros clientes.
AI cheating detection identifies signs that a test taker may be using unauthorized AI tools or external assistance during an assessment. Integrity Advocate’s CounterAI™ looks beyond tool names by evaluating behavioral and interaction signals in context.
CounterAI™ is designed to identify AI misuse patterns, not only known tool names. That helps protect programs as tools are renamed, embedded into browsers, added through extensions, or replaced by new technologies.
Depending on the risk level, the session may be blocked, interrupted, flagged, or reviewed. Integrity Advocate uses a proportional approach, meaning actions are based on corroborated risk signals rather than a single isolated indicator.
Every flagged session is reviewed by a trained professional. Reviewers evaluate the evidence, session context, and program rules before confirming an outcome.
CounterAI follows Integrity Advocate's privacy-by-design standards. We collect only what's necessary, evidence is redacted if sensitive content is detected, and data handling meets GDPR, FERPA, and PIPEDA requirements.