ChatGPT is not automatically unsafe, but using it can create privacy and security risks—especially when you share sensitive information or connect it to websites, files, email, or other tools. Reduce those risks by limiting what you share and what ChatGPT can access, and by reviewing consequential actions before approving them. No setting or safeguard eliminates every risk.
Is ChatGPT safe to use?
There is no single yes-or-no answer. The risk depends partly on what you put into a conversation and partly on what tools or accounts ChatGPT can reach. In an ordinary chat, you provide the information directly. With connected apps or agent features, the assistant may also be able to read information from signed-in services or take actions, depending on the permissions you grant.
OpenAI describes safeguards such as monitoring, sandboxing, and confirmations for important actions, while warning that safeguards do not remove all risks. Treat ChatGPT as a tool that needs appropriate limits and oversight, not as a guarantee that information will remain private or every action will be safe.
How does ordinary chat differ from connected or agent use?
The key difference is the assistant’s access and authority. A connected assistant may be able to work with information beyond the messages you type, and some workflows can take actions as well as read information. The precise capabilities depend on the feature, connected service, permissions, and account.
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| What to consider | Ordinary chat | Connected apps or agent workflows |
|---|---|---|
| Information available | Messages and files you provide in the chat | May also include information available through enabled apps or signed-in websites, such as email or files |
| Reach | Chat interaction, without an enabled connection to an external service | May reach enabled external services or tools |
| What it can do | Respond to your request using the conversation context | May read information or perform actions, depending on the tool and granted permissions |
| Oversight | Review the answer before relying on it or sharing it | Also inspect proposed actions and confirm consequential steps when prompted |
| Controls to check | Data-use settings and account security | Data-use settings, account security, and the permissions of each connection |
What is a prompt injection?
A prompt injection is malicious instruction hidden in content that an AI assistant is asked to read, rather than simply an unusual instruction typed by the user. It could be placed in a web page, email, or other third-party material. The attacker’s aim may be to redirect the assistant, expose information, or persuade it to take an action the user did not intend. OpenAI calls prompt injection an evolving security challenge.
The risk is more consequential when the assistant can use tools or access connected accounts: malicious content could try to influence what the assistant does with those capabilities. This resembles social engineering, but targets the assistant’s context and tools.
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- Give a narrow, explicit task instead of granting open-ended discretion.
- Limit the assistant to the tools and information the task actually needs.
- Read the details of a proposed consequential action before confirming it.
- Stop the task if the assistant unexpectedly seeks, exposes, or shares information.
Can ChatGPT expose sensitive information?
Information can enter the picture in two different ways: you can type or upload it yourself, or a connected assistant may be able to access it through an enabled app or signed-in website. Keep those paths in mind when deciding what to share and which connections to enable.
OWASP’s guidance on risks in large language model applications identifies sensitive information disclosure as a concern. Personal, financial, health, business, credential, and legal information may be at stake. Instructions telling a model not to reveal information are not a substitute for controlling what the application can access.
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OpenAI has also described a URL-based exfiltration scenario: an attacker may try to make an agent request a URL that contains private information within the URL itself. The company presents URL safeguards as one layer of a broader defense, not as a guarantee against disclosure.
- Do not paste passwords into messages. Avoid sharing private information that is unnecessary for the task.
- Grant access to sensitive accounts or documents only when the task requires it.
- Review data-use settings and connected-app permissions; they address different aspects of use and access.
- Do not continue a task if the assistant appears to be seeking or sharing information unexpectedly.
How can you limit agent permissions and actions?
More functionality and authority can increase the consequences of a mistake or manipulation. OWASP calls this risk excessive agency: an application gives an AI system more capabilities, permissions, or autonomy than it needs. For an individual user, the practical response is to connect fewer services, keep tasks specific, and supervise actions that matter.
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For individual users
- Enable only the connection needed for the current task, and review its permissions.
- Prefer a read-only capability when that is enough; avoid granting the ability to change or send information unnecessarily.
- Check recipients, content, account changes, and other material details before confirming an action.
- Disconnect or disable access you no longer need.
For organizations and developers
These are application-security practices, not settings that every ChatGPT user can configure. OWASP’s guidance supports measures such as:
- Use least-privilege identities and scope tools to the current user and task.
- Separate read and write capabilities where possible.
- Require appropriate human authorization for high-impact actions.
- Log and monitor activity so that unexpected access or actions can be investigated.
- Use technical and operational controls in addition to user training; instructions alone may be bypassed.
How do you protect your ChatGPT account and privacy?
Account security and data-use choices help address different risks. OpenAI says its Advanced Account Security adds stronger sign-in and recovery safeguards. It also says users can control whether their data is used for training and can delete memories, conversations, and account data. OpenAI describes encryption in transit and at rest. These are statements about the company’s controls, not a promise that every account compromise or disclosure is impossible.
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- Review the available account-security and data-use settings and choose options that fit your needs.
- Use stronger sign-in and recovery safeguards where available, and protect the email account used for recovery.
- Delete conversations, memories, or account data when appropriate, understanding that deletion controls do not prevent every possible exposure.
- For a business account, assess administrative, access, and retention controls against your organization’s plan and requirements; features and availability can vary.
What does Lockdown Mode change?
OpenAI describes Lockdown Mode as an optional setting for people with higher security needs or sensitive work. It limits or turns off some capabilities that connect ChatGPT with the web or external services, including live web access, some connectors, and file downloads. This is a security-versus-functionality trade-off: restricting connections can reduce exposure, but also removes capabilities a task might need. Availability may differ by account and rollout.
OpenAI also describes monitoring, sandboxing, and confirmations for important actions. These are layers of protection, not a reason to stop supervising an agent or to connect sensitive accounts casually.
What should organizations know about ChatGPT-related AI risks?
OWASP’s 2026 LLM Top 10, dated August 3, 2026, is a community-developed guide with updated rankings, expanded threat coverage, and mappings to other frameworks. Its 2025 materials discuss risks including prompt injection, sensitive information disclosure, supply-chain vulnerabilities, data and model poisoning, improper output handling, and excessive agency. These are risks for LLM applications broadly; they should not be read as a measurement of ChatGPT incident rates.
Organizations adopting ChatGPT or building AI workflows should evaluate the whole application around the model: what data enters it, which services and tools it can reach, how outputs are handled, and which actions require authorization. Training staff to recognize suspicious content is useful, but it should sit alongside least-privilege access, technical safeguards, monitoring, and appropriate approval processes.
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