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Data security is challenging for every business, but if you’re in finan...
Refreshed and updated January 7th, 2026.
In a dramatically short period, AI has gone from creeping into the enterprise to storming down the boardroom doors with full force. From Microsoft Copilot to Google Gemini to OpenAI’s ChatGPT, generative AI tools have embedded themselves into day-to-day workflows faster than security teams can down their first morning coffee.
We’ve spoken about the risks associated with Copilot and Gemini, but ChatGPT deserves its own spotlight. That’s because it’s the most widely used and the least governed by many organizations.
In this guide, we’ll explore why ChatGPT poses a real threat to enterprise data security if left unchecked.
Why ChatGPT Is Still a Risk Even Without Native Access to Your Files
Unlike Copilot, ChatGPT doesn’t have built-in access to your corporate emails, documents, or Teams chats. Which certainly sounds safer, until you realize how often sensitive data is pasted directly into ChatGPT by well-meaning employees just trying to get their work done.
And therein lies the problem, as they say. ChatGPT’s security risk isn’t really about what it can access, it’s more about what users share, how data is processed, and what guardrails (if any) are in place to stop mistakes from becoming incidents.
Let’s break it down.
Six Security Risks That Make ChatGPT a Threat in 2025
1. Employees don’t think twice about pasting sensitive data
People copy and paste internal data into ChatGPT every day, including customer emails, product roadmaps, and even contract language. That data is then processed and can be retained and used to train future models. Despite OpenAI’s opt-out options, usage habits haven’t changed, and enterprises rarely have visibility into how AI tools are being used at the edge.
2. Attackers weaponize ChatGPT for malware and phishing
Are you a hacker who needs polymorphic malware or a convincing phishing campaign? ChatGPT has got what you need. But wait, there’s more! While OpenAI has added filters to prevent abuse, threat actors continue to jailbreak the system. In one example, they’re disguising prompts as academic questions or penetration tests to generate harmful code or social engineering scripts.
3. Better phishing campaigns to trick employees
What used to be an easy-to-spot email scam now looks like a professional message from your CFO. ChatGPT allows attackers to localize, personalize, and perfect their outreach, especially in spear-phishing and business email compromise attacks.
4. How to be a cybercriminal 101
Every AI prompt is a free lesson. Aspiring hackers use ChatGPT to study exploits, write Python scripts for scanning vulnerabilities, and test basic obfuscation techniques. It makes cyberattacks easier, and cybercriminals stronger.
5. More vulnerable API integrations, more attack surface problems
When companies integrate ChatGPT into internal workflows via APIs, they open a new vector for attacks. Many of these APIs are new, rushed to market, and inconsistently secured, giving adversaries a path into core business systems.
6. No guardrails on how output is used
ChatGPT might generate insecure code or inaccurate analysis, and because it sounds confident, users are more likely to trust it. There’s no sandbox, no enforcement, no review process unless you build one yourself. That turns every output into a potential liability.
How Is ChatGPT Different Than Copilot?
While both tools use OpenAI’s models, their enterprise usage and risk posture are wildly different:
| Feature | Microsoft Copilot | ChatGPT |
| Integration | Embedded in Microsoft 365 apps | Standalone or via API |
| Security | Governed by Microsoft’s compliance framework | Requires custom safeguards |
| Data Access | Directly accesses company files | No native access—but users share data manually |
| Custom Controls | Built-in enterprise IT management | Must be built from scratch |
The takeaway here is that Copilot is governed, but ChatGPT is a wild card unless you lock it down.
Five Ways to Remediate ChatGPT Security Risks
ChatGPT wasn’t exactly built for enterprise use. It doesn’t follow your security policies, respect your compliance boundaries, or ask permission before processing sensitive data. But that doesn’t mean your only option is to block it entirely.
Security teams that win in 2025 aren’t the ones playing whack-a-mole with AI tools and avoiding AI governance; they’re the ones who set up invisible protections that let employees move fast without accidentally blowing holes in their security posture.
Here’s how to rein in the chaos and stay in control, even when ChatGPT isn’t.
1. Control access and integrations
Restrict access to ChatGPT through SSO and enforce a zero-trust model across endpoints. If you’ve deployed ChatGPT via API, use API gateways with OAuth 2.0 and apply encryption in transit to protect data.
2. Monitor AI use and flag sensitive data
Don’t assume employees will know what’s okay to share. Use data security tools to monitor AI-generated and user-submitted content for sensitive data. Bonus points if the tools can do it without relying on rules, regex, or manual classifiers.
3. Deploy smart DLP that understands context
Traditional DLP breaks when data doesn’t match the patterns it expects. Look for tools that label data based on meaning, not format—so even if someone pastes a contract summary or source code into ChatGPT, it gets flagged before it leaves the perimeter.
4. Educate employees, frequently and engagingly
Your AI policy shouldn’t live in a shared document that no one ever reads. Train users on what’s safe to share, how ChatGPT works, and the risks of hallucinations or code reuse. Reinforce with real-world examples and internal phishing simulations.
5. Plan for the worst
Don’t have an AI incident response plan? Time to get on that. If sensitive data is shared with ChatGPT, what’s your remediation process? Who gets notified? What steps do you take to assess impact? Simulate the scenario now, and don’t wait until it happens.
Let Concentric AI Do the Heavy Lifting
ChatGPT isn’t going anywhere (although it does go down from time to time). And banning it outright doesn’t work, because users will find a workaround.
What you need is visibility, control, and the right automation to keep sensitive data from leaking in the first place.
With Concentric AI, organizations get a GenAI taming tool that:
- Discovers and classifies sensitive data, even in shared docs, Slack threads, and API payloads
- Applies sensitivity labels automatically—no end-user action required
- Monitors usage patterns and flags risky behaviors in real time
- Detects AI-generated content containing sensitive info before it leaves your environment
No agents. No rules. No maintenance overhead. Just smart, autonomous data protection that thinks the way your users do—and stops the risks they don’t see coming.
Book a demo and see how Concentric AI keeps your generative AI adoption secure, scalable, and under control.