🤖 AI Security Guide: Are You Using AI Safely? 5 Hidden Risks and How to Avoid Them

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In recent years, AI has quietly become a part of our everyday lives.

When we arrive at work in the morning: We use AI to organize yesterday’s meeting notes.
In the afternoon, when writing emails: We ask AI to polish our wording and make the tone sound more professional.
Before leaving work: We throw a difficult problem at AI and see if it can spark some inspiration.

We use AI to:

✍️ Write emails and improve resumes
📊 Organize meeting notes and create presentations
🧠 Search for information and generate ideas for projects
👨‍💻 Help write code and fix bugs

All of this happens so naturally and effortlessly,
so effortlessly that we hardly ever stop to think about one simple question:

“Wait a minute—did I just give sensitive information to AI?”

Most of the time, what we are looking for is efficiency:

Can I get this done faster?
Can I spend less mental effort on it?
Can I get an answer that “looks good enough”?

That is why many people initially think:

“It’s just a tool. It’s not like I’m downloading a virus. It should be fine, right?”

After all, we are not on a hacker forum,
nor are we downloading some suspicious program.
We are simply pasting a piece of text and asking a question.

But here is the real key—
the risks of AI are often not about “what you intentionally set out to do,”
but rather “what you accidentally ended up doing.”

Because the moment you start using AI, several things have already happened without you necessarily noticing:

You have “entered” data into a system that you do not completely control.
You have allowed an external system to “access” your text, content, or ideas.
You have started relying on AI-generated results to influence your decisions.

And fundamentally, all of these behaviors are related to information security.

So, the real question is not:

“Can we use AI?”

It is:

👉 “In an era when everyone is using AI, are we using it safely enough?”

So, let’s take a closer look at:

the information security risks that AI brings—risks you may not have noticed—and what we can do to avoid them.

🧩 1. What Is “AI Information Security”?

When we talk about information security, the first things that usually come to mind are:

Hackers 🧑‍💻
Ransomware 💥
Stolen accounts 🔓

But AI information security actually covers a much broader scope.

🧠 In simple terms, it comes down to three things

When using AI, remember these three questions:

Input: What data am I feeding into the AI? (Privacy and confidentiality)
Processing: Will the data be retained, analyzed, or even become part of AI training? (Ownership)
Output: Can I completely trust the answer AI gives me? (Authenticity)

If something goes wrong at any one of these stages, it could potentially develop into an information security crisis for an organization or an individual.

🍽️ 2. Why Is “Using AI” Related to Information Security?

🧑‍🍳 A Simple Everyday Analogy

Imagine that you hand an internal company document to a stranger who happens to be very intelligent, and ask them to help you summarize the key points.

You would naturally have some questions in your mind:

🤔 Will they secretly keep a copy of the data?
🤔 Will they share it with someone else?
🤔 Can I be sure that the information they provide is accurate?

AI is much like this:
it is highly capable, but you may not always know exactly how it handles your data behind the scenes.

⚠️ 3. The 5 Most Common AI Security Traps

❌ 1. Pasting “Confidential Information” Directly into AI

Common scenarios include:

Pasting an unpublished contract into AI for editing
Uploading a customer list for analysis
Uploading internal planning documents to a free AI service for summarization

📌 The key risk is:
Once this information is sent, it enters a cloud-based system and may potentially even be used to train future generations of AI models.

Taiwanese technology media outlet TechOrange has pointed out that when many companies adopt AI, unclear boundaries around data usage are one of the most easily overlooked sources of risk.

🔗 “Why Do Companies Need to Rethink Information Security When Adopting AI? An Analysis of 5 Commonly Overlooked Risk Scenarios”
https://techorange.com/2025/04/16/ai-security-highlight/

👻 2. “Shadow AI”: You Are Using It, but Your Company Has No Idea

Shadow AI refers to:

Employees privately using unauthorized or unknown AI tools to handle work-related tasks without the knowledge of the company or approval from the IT department.

For example:

Using a free AI service to modify a quotation
Pasting internal information into an AI-powered translation service
Privately using an unknown generative AI tool

📌 Why is this dangerous?

IT and information security teams have no visibility into its use
The flow of data cannot be properly controlled
It becomes difficult to trace what happened when an incident occurs

An official report from Palo Alto Networks points out that “Shadow AI” has become one of the newest and fastest-growing information security risks facing organizations.

🔗 Palo Alto Networks “2025 State of Generative AI Security Report”
https://www.informationsecurity.com.tw/article/article_detail.aspx?aid=11996

🌀 3. AI Can Be Very Convincing When It “Confidently Makes Things Up” (AI Hallucinations)

AI does not actually “understand” information in the way humans do. Instead, it generates content based on probabilities. As a result, it may:

Look highly professional while actually being wrong (confidently making things up)
Invent non-existent laws, statistics, or research cases
Give you an answer that sounds “reasonable but is actually incorrect”

This phenomenon is known as:

AI Hallucination

The key risk: If an incorrect answer is used directly to make decisions, it could lead to legal liability or damage to an organization’s reputation.

The U.S. National Institute of Standards and Technology (NIST) explicitly points out in its AI risk management documentation that:

“Over-reliance on AI output” is itself a risk.

🔗 NIST – Artificial Intelligence Risk Management Framework (AI RMF)
https://www.nist.gov/itl/ai-risk-management-framework

🎭 4. AI Makes Scams and Fake Information Look More “Real”

AI is making scams increasingly sophisticated.

Hackers can use Deepfake technology to imitate a manager’s voice or appearance, or create highly convincing social engineering emails with almost no obvious flaws.

You may have seen news stories about cases such as:

Imitating a boss’s voice to request a money transfer
Faking a video conference involving senior executives
Highly customized phishing emails with almost no obvious signs of fraud

The key risk: When fraudulent content looks “too real,” our natural instinct to detect something suspicious can fail.

Behind many of these attacks is the use of AI-powered Deepfake technology.

CIO Taiwan has pointed out in its analysis of generative AI risks that AI is already being widely used to strengthen social engineering attacks and improve the precision of scams.

🔗 “A Double-Edged Sword in Cybersecurity: Three Major Risks and Opportunities of Generative AI” | CIO Taiwan
https://www.cio.com.tw/102645/

🔗 5. AI Tools, Plugins, and the Models Themselves Can Also Pose Risks

Many people install AI plugins or Chrome extensions, but the security of these tools can vary considerably.

The AI tools you use are often connected to:

Third-party services
External data sources
Plugins and APIs

The key risk: An insecure plugin could become a backdoor for data leakage.

OWASP, an international nonprofit organization focused on application security, has identified the:

Top 10 risks for AI applications, including prompt injection, data leakage, over-reliance on AI output, and other threats.

🔗 OWASP – Top 10 for Large Language Model Applications
https://owasp.org/www-project-top-10-for-large-language-model-applications/

✅ 4. How Can Ordinary Users Use AI Safely?

The good news is:

👉 You don’t need to be an engineer to get 80% of the protection right.

Start by building the following security mindset:

🛡️ 8 Practical Principles for Everyday AI Users

De-identify Data: If you need AI to polish a document, remove specific names, company names, and monetary amounts.
Treat AI as an Assistant: Use AI as an assistant, not the final decision-maker. Always review its output yourself.
Use Enterprise Versions: If your company provides a paid enterprise AI service, prioritize using it. Enterprise versions typically offer stronger privacy commitments and controls.
Verify the Facts: Whenever AI provides statistics, data, or legal references, always verify the information through a second source.
Watch for Anomalies: If you receive an unusually realistic video or voice message requesting sensitive actions such as a “money transfer” or “authorization,” always verify the request through a separate communication channel.
Follow the Rules: Pay attention to and comply with the AI usage policies established by your organization.
Review Permissions: Before installing an AI plugin, check the developer’s reputation and avoid granting excessive permissions.
Ask Yourself One Final Question: Before clicking the Send button, ask yourself: “If this text appeared as tomorrow’s newspaper headline, could I live with it?”

🌱 5. Conclusion: Information Security Is a “Skill for the AI Era”

AI is like an extremely sharp double-edged sword: 🔪

Use it well, and your productivity can skyrocket.
Use it carelessly, and the risks can be enormous.

Information security is no longer just the responsibility of the IT department. It is a fundamental skill that every AI user needs to develop.

At a time when everyone is pursuing greater productivity and value from AI, only by using AI safely can we truly make it a powerful and reliable partner for the long term.