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CodeSignal's Findings on Growing Assessment Fraud

In a significant revelation, CodeSignal, a leading AI-native skills platform, has uncovered an alarming rise in assessment-related cheating and fraud in 2025. According to their latest research, the rate of fraudulent activity in proctored assessments surged from 16% in the previous year to a staggering 35% in 2025. This increase is indicative of a broader cultural trend where candidates are increasingly employing sophisticated tools, including advanced technology like AI, to gain unfair advantages in assessments.

Key Trends in Cheating and Fraud

The research conducted by CodeSignal showcases a specific focus on early-career positions. The data indicates a nearly tripling of cheating attempts for entry-level assessments, escalating from 15% in 2024 to a remarkable 40% in 2025. This vulnerability highlights the need for robust protective measures specifically tailored for junior roles in the modern hiring process. Tigran Sloyan, CEO and Co-Founder of CodeSignal, emphasized that while fraud in hiring is not a new issue, the methods candidates utilize are continually evolving, creating a pressing need for organizations to enhance their monitoring systems.

Behavioral Insights from Detected Cheating Attempts

CodeSignal's advanced detection systems leverage a combination of digital analysis, AI, and human-led proctoring to monitor assessment sessions effectively. Notably, among the flagged assessments in 2025, several behavioral indicators were observed:

• - 35% of sessions involved frequent off-screen referencing.
• - 23% demonstrated unusually consistent typing patterns with minimal pauses.
• - 15% exhibited similarities to known solutions or leaked answers.

These signals reflect attempts at fraud during assessments, showcasing the importance of continuous monitoring strategies.

Geographic and Operational Trends

The research also sheds light on the geographic variations in cheating behaviors and highlights the impact of monitoring conditions on the effectiveness of detection methods. For instance, the Asia-Pacific region recorded the highest attempt rate at 48%, while North America had a significantly lower rate of 27%. Additionally, unproctored assessments showed score increases that were over four times higher than those in proctored conditions.

Year-Long Developments in Fraud Prevention

With a decade of experience in developing fraud prevention infrastructures, CodeSignal has refined its systems to identify key violation types, including copy-paste plagiarism, proxy test-taking, unauthorized AI use, and identity fraud. This ongoing refinement aims to understand and mitigate cheating risks effectively. Sloyan indicated that leveraging AI to monitor various behavioral signals, such as off-screen referencing and typing dynamics, allows organizations to maintain consistent evaluation criteria across candidates.

Conclusion

As the prevalence of fraud in assessments continues to rise, organizations must be vigilant in employing advanced monitoring techniques. CodeSignal's insights stress the necessity for adaptive strategies in protecting hiring integrity and ensuring fair skill evaluations. For a more in-depth analysis, the full research findings can be accessed on CodeSignal's official blog. As organizations navigate this complex landscape, integrating sophisticated tools and fostering a culture of integrity in assessments will be paramount to ensuring the quality of hires and the efficacy of their evaluation processes.