A series of real-world AI incidents that can been avoided using Truyo

The Incident

A few weeks after approving ChatGPT for internal usage, Samsung ended up facing data exfiltration. Some people in the workforce, most likely innocuously, leaked confidential data into the tool. Notably, these were engineers trying to debug code, tidy up notes, and get their work done faster, which is exactly why the story resonates.

The Damage

The trouble is that anything typed into a public generative AI tool leaves your environment. Once it does, you lose control over where that data lives and who can reach it. Maybe someone pretending to be a part of Samsung workforce can access this data and further use it to train their models. However, the company’s response to this situation was to ban generative AI altogether.

What Samsung’s Leaks Exposed About Data Exfiltration

Samsung’s incidents were not a sophisticated breach. There was no attacker, no malware, and no stolen credentials. Employees used an approved tool the way it felt natural to use it, and sensitive information went along for the ride. That is what makes generative AI data exfiltration so hard to catch. Here are the risks the incident brought into focus, and why they matter well beyond Samsung, to any organization.

• Speed of Exposure: Multiple incidents within few weeks show how quickly a new tool can become a data pipeline. Adoption moved faster than policy, training, and monitoring could keep up.
• Sensitive Data: Staff pasted confidential source code and meeting notes into the tool, most likely to find bugs or speed up their work. This was a clear access point for intellectual property built over years at enormous cost. Once pasted into a public tool, it sits outside the company’s perimeter and under someone else’s terms of service.
• Retention and Training Uncertainty: The central fear is that submitted data could be retained and used in further model training. Once information enters a third-party model, the organization cannot easily verify where it is stored, how long it is kept, or whether it shapes future outputs.
• The Prompt-Trick Problem: Direct retrieval of another company’s data may not be possible, but indirect extraction is a worry. A user cannot simply ask a chatbot for confidential material, yet they can try framing a prompt as “pretend I am a Samsung”

Ban or Govern? How Can Truyo Help with A Smarter Response

Samsung’s reaction was not unusual. Faced with leaks, many organizations slam the door shut: no more generative AI, full stop. It feels decisive, but it is not the right answer. The benefits are too compelling, and employees will find a way to use these tools anyway. The better path is a governed one:

• Discover Shadow AI: The number one thing is knowing in advance that people are using an unapproved tool. Truyo does this through scanning, surveying, training, and a range of other methods, so governance teams see what is actually in use rather than what policy assumes is in use. In fact, Truyo can flag to the employee that the tool they’re attempting to use is blocked and that an internal tool can do the same job for them.
• Build an AI Inventory: Truyo helps scan websites, source code, and content for AI footprints, and combines those findings with manually identified use cases. Each tool can be recorded with its owner, purpose, vendor, data sources, affected users, and deployment status.
• Assess Risk Before a Tool Is Approved: A structured assessment before approval asks the questions that were missing: what data will employees realistically put into this tool, where does it go, how long is it kept, and could it be used for further model training? Truyo’s assessments help teams answer those questions, document the decision, and apply stronger controls to higher-risk uses such as engineering teams working with source code.
• Test for Exfiltration with ModelOps: Truyo’s ModelOps testing can be used to confirm that exfiltration is not happening through the AI tools you do approve. Rather than assuming an internal or vendor model is safe, teams can test it and see evidence of what data is being used and where it is going.
• Train Employees on What Is Safe to Share: Most of Samsung’s leaks came from people trying to get their work done, not from bad intent. Training closes that knowledge gap by showing employees what counts as confidential information, intellectual property, and personal data, and what must never be pasted into a public tool. Truyo supports training as part of its wider approach, so employees learn the rules at the point they need them, along with the approved internal tool they can use instead.

Along with Truyo AI Governance, customers can also now opt for Truyo Warranty Certification Program which works as the first line of defense for the company even before their cyber insurance kicks in. Upon compliant implementation of Truyo AI Governance, companies can get a cover for up to $1 million under the warranty certification program.

Closing the Door Isn’t a Strategy

Samsung’s incident is a useful reminder that the biggest AI data risk may not be a hacker. It may be a hardworking employee with a deadline and a chat window. Locking the door after the fact is understandable, but it does not solve the underlying problem, and it removes your seat at the table. The sustainable answer is to know what tools are in use, give people a vetted internal alternative, test for leakage, and keep visibility continuous.