49% of New Yorkers avoid accessing sensitive information like banking accounts and email when on public WiFi.

13% of organizations reported having strong visibility into how AI systems handle sensitive data.

66% of organizations reported catching AI tools over-accessing sensitive information.

95% of publicly disclosed ransomware attacks involved the theft of sensitive information.

Individual breached records surged by more than 186%, revealing sensitive information such as passwords, emails, and credit card details.

There was a 43% increase in data breach data shared on underground forums in 2024.

11% of files uploaded to AI applications include sensitive corporate content.

20% of CISOs are able to identify over 75% of sensitive data across environments.

79% of security teams struggle to classify sensitive data used in AI/ML systems.

Less than half (48%) of organisations express high confidence in controlling sensitive data used for AI/ML training.

39% of Security Engineers report the highest ability to track sensitive data, able to identify over 75% of sensitive data across environments.

14.88% of sensitive data input into GenAI tools was legal and finance data, such as information on Sales Pipeline Data, Investment Portfolio Data, and Mergers and Acquisitions.

6.88% of sensitive data input into GenAI tools was security policies and reports.

45.77% of sensitive data input into GenAI tools was customer data, such as billing information, customer reports, and customer authentication data.

63.8% of ChatGPT users used the free tier, with 53.5% of sensitive prompts entered into it.

8.5% GenAI prompts contain sensitive information.

5.64% of sensitive data input into GenAI tools was sensitive code, like Access Keys and proprietary source code.

26.83% of sensitive data input into GenAI tools was employee data, including payroll data, PII, and employment records.