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Cheating Detection & Fraud Prevention

Hard to fake, easy to trust

Detect sophisticated cheating and AI misuse using telemetry, pattern analysis, and full-service proctoring.

Get assessment results you can trust

Ensure trustworthy assessment results as cheating methods evolve faster than traditional detection can track.

Safeguard integrity

See whether learning programs led to skill improvement and use the results to evaluate training impact and ROI.

Improve hire quality

Reduce the risk of advancing candidates whose scores don’t reflect how they’ll perform on the job.

Modernize defenses

Stay protected as new cheating tactics and tools emerge, keeping assessment results reliable.

Speed up workflows

Offload investigation and verification work so your team isn’t stuck manually reviewing suspicious results.

Multiple safeguards, one clear signal

Use multiple layers of defense to spot suspicious results and preserve assessment integrity.

Identify potential integrity issues by evaluating whether an assessment reflects an individual’s own work.

  • Analyze multiple fraud signals, including solution similarity, telemetry, and copy-paste activity.
  • Identify patterns that may indicate AI-assisted behavior, which are often missed by basic plagiarism checks.
  • Receive a score that reflects overall trust level, with a clear breakdown of issues requiring review.

Reduce the impact of leaked assessment content using CodeSignal’s proprietary monitoring technology.

  • Automatically monitor public sites like Stack Overflow and LeetCode for leaked CodeSignal questions.
  • Easily detect exposed content to enable rapid question replacement and preserve assessment validity.
  • Enforce copyright protection through built-in monitoring and DMCA takedown workflows.

Verify assessment results using full-service proctoring that combines automated analysis with human review.

  • Record video, audio, and screen activity for the entire assessment session so nothing important is missed.
  • Evaluate sessions using multi-agent analysis, with human reviewers validating flagged activity and final decisions.
  • Receive proctoring results within one hour, compared to the typical 24 to 48 hour turnaround for manual review.

Minimize answer sharing by rotating question variations across candidates while keeping assessments fair and consistent.

  • Rotate thousands of question variations so candidates don’t receive identical assessments.
  • Maintain consistent difficulty and scoring across variations to protect assessment integrity.
  • Limit the impact of leaked or memorized content, especially in high-volume and entry-level hiring funnels.

Confirm candidate identity with a short verification step built into the start of the assessment or interview.

  • Prompt candidates to complete identity verification in minutes using a valid, government-issued photo ID.
  • Verify identity during remote evaluations by matching the candidate’s name and photo ID to the person on camera.
  • Include verification status and relevant context alongside assessment results for hiring teams.

Add optional safeguards to assessments for roles or situations that require closer oversight.

  • Disable copy and paste functionality to prevent question sharing and the use of answers from outside sources.
  • Use IP tracking and location signals to add context when reviewing potential integrity concerns.
  • Configure controls selectively so higher-risk roles receive added protection without impacting all candidates.
years

of cheating and fraud detection expertise

M+

skill evaluations completed on CodeSignal

hour

turnaround time for CodeSignal proctoring results

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Technical Assessments

Measure technical capability using role-specific tasks that reveal current proficiency and learning opportunities.

AI Skills Assessments

See how candidates work with AI tools in realistic scenarios, from foundational knowledge to applied use.

Business Assessments

Assess business skills through hands-on exercises that identify strengths and development areas.

Frequently asked
questions

How does CodeSignal detect cheating in assessments?

CodeSignal uses multiple detection layers including Suspicion Scores that analyze fraud signals like solution similarity and copy-paste activity, LeakSweep technology that monitors for leaked questions, AI proctoring with video and screen recording, identity verification, and dynamic question rotation to prevent answer sharing.

A Suspicion Score evaluates whether an assessment reflects a candidate’s own work by analyzing multiple fraud signals including solution similarity, telemetry data, and copy-paste activity. The score identifies patterns that may indicate AI-assisted behavior and provides a clear breakdown of integrity issues requiring human review.

AI proctoring records video, audio, and screen activity for the entire assessment session. Sessions are evaluated using multi-agent analysis, with human reviewers validating flagged activity and making final decisions. AI proctoring results are delivered within one hour, compared to typical 24-48 hour manual review turnarounds.

LeakSweep is CodeSignal’s proprietary monitoring technology that automatically scans public sites like Stack Overflow and LeetCode for leaked assessment questions. When exposed content is detected, teams can rapidly replace questions and use built-in DMCA takedown workflows to protect copyright and preserve assessment validity.

Yes. CodeSignal’s Suspicion Score identifies patterns that indicate AI-assisted behavior, which are often missed by basic plagiarism checks. The system analyzes telemetry data, solution patterns, and behavioral signals to detect when candidates use AI tools inappropriately during assessments.

CodeSignal includes identity verification that prompts candidates to complete verification in minutes using a valid government-issued photo ID. For remote evaluations, the system matches the candidate’s name and photo ID to the person on camera, with verification status included alongside assessment results for hiring teams.