Concept image showing an AI-powered resume screening system identifying a hidden prompt injection attack designed to manipulate hiring decisions.

1% of resumes contain hidden prompts to trick AI hiring tools

Published: 17:35, July 25, 2026

A study carried out by academic and industry researchers analyzed the resumes (CVs) of 200,000 individuals from a range of sectors. They found that 1% contained hidden instructions designed to manipulate AI hiring systems.

In other words, the instructions were designed to undermine the AI’s ability to do its job properly or make it do things that the programmers had not intended.

The researchers found that in a sample of 200,000 resumes across several different sectors, one percent contained hidden instruction designed to exploit or manipulate AI systems.

In today’s competitive job market, some applicants are discreetly trying to be one step ahead of current AI hiring tools. These AI systems filter applicants, so that HR personnel can rapidly receive a shortlist of candidates for face-to-face interviews. The researchers explain that this trend is spreading rapidly.

The findings of the study will be presented at the USENIX Security Symposium in August, 2026. The study and findings can be read at arXiv, an open-access research repository where scientists and academics share their research papers. Researchers from Duke University, UNC-Chapel Hill, Arizona State University, UC Berkeley, and hireEZ carried out the study.

Lead author Mohan Zhang, from the University of North Carolina at Chapel Hill, and colleagues examined 200,000 real resumes that had been submitted to hireEZ, the industry research collaborator. The authors say that theirs is the first detailed study of prompt injection in an AI system that is used extensively in the real world.

It may simply consist of invisible keywords that humans can’t detect because they blend into the text background. 

Study co-author Neil Gong, an associate professor of electrical and computer engineering at Duke University, said:

“Even a few years ago, these attacks would have been completely effective and AI screeners wouldn’t have questioned it. What surprised us was not just that people are trying it, but how quickly the tactic is spreading.”

The team, which includes hireEZ and researchers at Arizona State University, the University of California, Berkeley, and the University of North Carolina at Chapel Hill (UNC), found that 1% of randomly selected, de-identified resumes contained prompt injection. Those resumes spanned July 2019 to December 2025 and covered a wide range of sectors.

While the 1% rate held relatively stable across industries, the researchers noted that it appears to have increased considerably since the release of ChatGPT in 2022, as the numbers rose sevenfold between July 2024 and November 2025.

“Prompt injection attacks have matured a lot in the past few years,” said Tianlong Chen, who previously served as chief AI scientist at hireEZ while this data was collected and is now an assistant professor of computer science at UNC. “There are TikTok and YouTube videos teaching people how to do it and free templates to generate hidden prompts. The trend is growing fast, so we felt it was important to partner with cybersecurity experts to study the problem.”

The research collaboration was not meant to verify people’s resume information. It was part of an effort to create systems for the job recruitment industry as a whole to counter this growing trend. After all, being able to spot which resumes have prompt injection is the first step toward dealing with their potential consequences.

Chen noted they do not ascribe malicious intent from the resumes they analyzed; some applicants may have unknowingly used templates with already hidden text. They also intentionally did not test whether the embedded instructions succeeded in manipulating hiring outcomes, citing ethical concerns. But the volume alone points to a growing risk as AI becomes more deeply embedded in hiring and society writ large.

Prompt injection is a cybersecurity vulnerability that affects more than just AI hiring practices. It is a risk for agentic AI, which are systems that can perform multi-step tasks, retrieve information on the internet and store memory. As these systems draw input from more sources, they also become more susceptible to hidden malicious instructions or incorrect data in that input.

“Agentic AI can pull together information from multiple sources into a single prompt,” Gong said. “If any part comes from an untrusted source, an attacker can manipulate the whole prompt and steer the system away from the original goal.”

Chen said any AI system making a “go” or “no-go” decision is at risk. While all of hireEZ’s final screening decisions are made by a human, examples in other industries range from paper-review systems for academic conferences or electronic exams to high-stakes domains such as visa applications, autonomous vehicles and flight planning.

“Any scenario where AI is used to score, filter or decide could potentially face similar attacks,” Chen said.

To counter this, researchers like Gong and Chen are developing several defensive strategies rather than relying on one safeguard. Possible solutions include training AI models to be more robust, monitoring inputs at runtime and using detection tools to identify where a malicious prompt is hiding.

“It’s not just academic researchers who see the real risk with prompt injection; industry is aware of the significant security threats too,” Gong said. “Our goal is to build a comprehensive set of defenses that can protect both users and the systems they rely on, not just in hiring, but anywhere agentic AI is used.”

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