Table Of Content
Are AI apps safe to use? How to Secure Gen AI Apps
- March 24, 2025
Summary: Data leaks, where sensitive information is unintentionally exposed, are a major concern, particularly when AI is involved. This article explores whether AI apps are safe, focusing on data loss or leaks due to AI, and provides practical advice for protecting yourself.
Imagine this: Your company’s most sensitive data, customer emails, financial projections, proprietary code, is being devoured by a silent predator. Not a hacker in a hoodie. Not a disgruntled employee. But due to an AI app your employees use in the name of productivity.
In 2023, IBM reported that 42% of enterprises now deploy AI apps daily. Yet the same study revealed that 82% of those companies lack protocols to audit AI for security flaws, a gap attackers are exploiting.
AI isn’t just transforming industries, it’s creating a minefield of unregulated risks. A hospital’s diagnostic AI accidentally exposes 500,000 patient records. A trading algorithm hallucinates, triggering a $300 million market cascade. A customer service bot manipulated into leaking passwords. These are countless examples stating AI apps leaking sensitive data.
This article unpacks the hidden risks of AI apps: are they truly secure? How do they inadvertently leak sensitive data? And—most critically—how can you secure Gen AI apps?
Are AI Apps safe to use?
While most AI companies claim they truly care about the safety of their users’ data, there are incidents where sensitive information is unintentionally exposed due to excess usage of AI. This is especially true with most free or low-cost AI apps as they often lack enterprise-grade security, making them more susceptible to exploitation. While there are some AI tools that claim they offer privacy-focused features like data anonymization or opt-out options while others publicly highlight that they may retain user information to enhance machine learning models.
In most cases, it really isn’t safe for a company to trust AI.
In most cases, it really isn’t safe for a company to trust AI.
Understanding Data Leaks Due to AI
Data leaks due to AI can be categorized into two main types:
- System-Induced Leaks: These occur when AI tools themselves have vulnerabilities or misconfigurations, leading to data exposure. Examples include bugs in AI systems or misconfigured storage access.
- User-Induced Leaks: These happen when users, particularly employees, input sensitive data into AI tools, which may then expose or misuse that data. This is often due to a lack of awareness or policy enforcement.
The investigation found that both types are significant, with user errors being a frequent cause, especially in generative AI tools like ChatGPT. When your employees input data into a Gen AI tool like ChatGPT, it undergoes complex processing.
To truly understand whether an AI is leaking your company’s data, it’s important to learn about the company’s data retention policies. This information can tell you whether the AI stores your data temporarily—or even permanently.
To truly understand whether an AI is leaking your company’s data, it’s important to learn about the company’s data retention policies. This information can tell you whether the AI stores your data temporarily—or even permanently.
Let’s zoom in on ChatGPT once again? Does It save Your Data?
OpenAI, the company behind ChatGPT, has been transparent about its data retention practices, but there’s still plenty to unpack.
By default, OpenAI retains user inputs for 30 days to monitor for misuse and ensure compliance with their terms of service. However, they claim not to use this data to train their models unless explicit permission is granted. For users concerned about sensitive information, OpenAI also offers a “private mode” through its enterprise plans, ensuring that no data is saved or shared beyond the session.
While most of these claims by OpenAI are publicly visible on their official website, most companies still don’t hesitate to take protective measures to prevent unintentional exposure of sensitive data on AI apps. It’s no surprise that Amazon warned employees in January 2023 not to share confidential data with ChatGPT after noticing responses resembling internal data, suggesting potential exposure through training data (Leaked Amazon Documents Warn Employees). In another similar incident, Samsung employees leaked sensitive code and meeting recordings by inputting them into ChatGPT, prompting a company-wide ban in May 2023 (Generative AI data leaks are a serious problem).
Does this mean your company also needs strong protection against these AI apps?
Well, yes in most cases. Especially in today’s AI era where there is an AI tool for almost everything and anything, AI security best practices are essential.
By default, OpenAI retains user inputs for 30 days to monitor for misuse and ensure compliance with their terms of service. However, they claim not to use this data to train their models unless explicit permission is granted. For users concerned about sensitive information, OpenAI also offers a “private mode” through its enterprise plans, ensuring that no data is saved or shared beyond the session.
While most of these claims by OpenAI are publicly visible on their official website, most companies still don’t hesitate to take protective measures to prevent unintentional exposure of sensitive data on AI apps. It’s no surprise that Amazon warned employees in January 2023 not to share confidential data with ChatGPT after noticing responses resembling internal data, suggesting potential exposure through training data (Leaked Amazon Documents Warn Employees). In another similar incident, Samsung employees leaked sensitive code and meeting recordings by inputting them into ChatGPT, prompting a company-wide ban in May 2023 (Generative AI data leaks are a serious problem).
Does this mean your company also needs strong protection against these AI apps?
Well, yes in most cases. Especially in today’s AI era where there is an AI tool for almost everything and anything, AI security best practices are essential.
How to secure AI apps leaking your company's sensitive data?
Worried about safeguarding your information while still reaping the benefits of AI? Here are a few practical tips:
- Read the Fine Print: Before diving into any AI platform, take a moment to review its privacy policy and data usage guidelines. Look for specifics on how your data will be handled and whether opt-out options are available.
- Use Enterprise Solutions: If privacy is a top priority, consider investing in enterprise-grade AI tools. These often come with enhanced security features and stricter data handling protocols.
- Avoid Sharing Sensitive Information: When in doubt, leave it out. Refrain from inputting classified or highly personal content into public-facing AI tools.
- Explore Alternatives: Not all AI tools operate under the same data policies. Research alternatives that align better with your privacy needs.
- Use DLP Solutions: If you want to protect your private data from unauthorized copy-paste or data-upload on AI solutions, use Gen AI DLP Solutions
By following these best practices, you can ensure your employees use AI safely while minimizing the risk of data leaks.
Looking to secure Gen AI Apps?
Kitecyber Data Shield is a DLP solution that secures sensitive data and alerts you whenever it is accessed by an unsecured AI App.
- Fully functional security for data at rest and in motion
- Supports data regulation and compliance
- 24 x 7 Customer Support
- Rich clientele ranging from all industries
The Role of DLP in Protecting Your Company’s Data from AI-based Data Leaks
As AI tools like ChatGPT revolutionize data workflows, robust security is non-negotiable. Data Loss Prevention (DLP), powered by machine learning, monitors and blocks risks like leaks, ransomware, and unauthorized data sharing in real time. It enforces policies to prevent actions like emailing sensitive files or uploading to unsecured platforms, while enabling secure AI adoption.
AI powered DLP Solutions like Kitecyber Data Shield secure AI apps proactively by:
- User Behavior Analytics (UBA): Flags anomalies by tracking usage patterns.
- Automated Audits + Expert Reviews: Detects leaks and ensures compliance.
- Comprehensive Logging: Tracks user activities like copy-paste, data upload, and airdrop transfer.
- Real-Time Alerts: Enables instant response to threats.
- Risk Mitigation: Addresses vulnerabilities before they escalate with efficient remote lock and wipe feature.
DLP isn’t just defense—it’s how businesses harness AI’s power without sacrificing security or trust.
With over a decade of experience steering cybersecurity initiatives, my core competencies lie in network architecture and security, essential in today's digital landscape. At Kitecyber, our mission resonates with my quest to tackle first-order cybersecurity challenges. My commitment to innovation and excellence, coupled with a strategic mindset, empowers our team to safeguard our industry's future against emerging threats.Since co-founding Kitecyber, my focus has been on assembling a team of adept security researchers to address critical vulnerabilities and enhance our network and user security measures. Utilizing my expertise in the Internet Protocol Suite (TCP/IP) and Cybersecurity, we've championed the development of robust solutions to strengthen cyber defenses and operations.
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