Entry-level hiring most vulnerable as assessment fraud and cheating attempts more than doubled in 2025, highlighting how sophisticated monitoring protects hiring integrity by identifying and deterring violations
SAN FRANCISCO, Feb. 25, 2026 /PRNewswire/ — CodeSignal, the leading AI-native skills platform, today released new research revealing a sharp increase in cheating and fraud over the past year. In 2025, cheating and fraud attempt rates for proctored assessments more than doubled, rising from 16 percent in 2024 to 35 percent. This trend was driven by an uptick in plagiarism, proxy test-taking, and unauthorized AI use, reflecting a broader cultural shift as candidates increasingly integrate advanced tools into their daily lives, underscoring the importance of robust fraud prevention infrastructure.
The surge is overwhelmingly concentrated in early-career hiring. Entry-level assessment cheating and fraud attempt rates nearly tripled year-over-year, jumping from 15 percent to 40 percent, making junior roles the most vulnerable segment of the modern hiring funnel.
“Fraud in hiring isn’t new, but it is always evolving with the times,” said Tigran Sloyan, CEO and Co-Founder of CodeSignal. “With 80 percent of Gen Z reportedly using AI in their daily lives, these tools are becoming a standard part of how people function. Access to AI also makes unauthorized assistance harder to detect and raises the stakes for maintaining fair and reliable skill evaluation. At CodeSignal, we continuously adapt our prevention methods to protect interview integrity even as the technology candidates use becomes more sophisticated.”
Key Behavioral Findings
CodeSignal’s detection system analyzes sessions using digital, AI, and human-led proctoring. Among assessments that were flagged in 2025, researchers identified several recurring behavioral signals:
- 35 percent involved frequent off-screen referencing during the session.
- 23 percent showed unusually linear typing patterns where complex solutions were produced with minimal pauses or debugging.
- 15 percent demonstrated elevated similarity to known answers or leaked content.
Importantly, these signals reflect fraud and cheating attempts that were detected and flagged, not successful circumvention of assessment standards.
Global and Operational Trends
The research further highlights how geographic location and active monitoring impact the frequency of attempted misuse:
- Regional Disparity: Cheating and fraud attempt rates reached 48 percent in Asia-Pacific compared to 27 percent in North America.
- Deterrence Factor: Unproctored assessments showed score increases more than 4X larger than proctored ones.
- Risk Concentration: Violations remain heavily concentrated at the entry-level rather than being distributed evenly across experience tiers.
A Decade of Fraud Prevention Infrastructure
Refined over 10 years and across millions of assessments, CodeSignal’s proprietary Suspicion Score, full-session proctoring, and leak-resistant assessment design approach effectively identify four primary categories of violations: copy-paste plagiarism, proxy test-taking, unauthorized AI use, and identity fraud.
“By applying AI proctoring to detect behavioral and technical signals like off-screen referencing, typing dynamics, and solution similarity, we’re able to identify a wide range of potential integrity issues during assessments,” Sloyan added. “This gives organizations a consistent way to evaluate risk across candidates.”
The full research findings are available at: https://codesignal.com/blog/prevent-and-detect-cheating-in-recruiting/
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