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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Never paste secrets or sensitive records into an AI chatbot unless your organization has explicitly approved that service and processing. Keep out passwords, one-time codes, payment-card data, government identifiers, health and financial records, confidential business material, proprietary code, security-incident details, and anyone else’s private messages or documents. Remove direct identifiers and unnecessary details, use a synthetic example or summary, and choose an approved tool with documented retention, access and contractual safeguards.
Why ordinary chat input can become a data-protection problem
An AI chatbot is an external processing service, even when it feels like a private conversation. Text, files, images and connected data may be retained, reviewed, logged, transferred between systems or used according to the service’s settings and contract. The exact treatment differs by product, account type, region and administrator configuration, so a public consumer chatbot should not automatically be treated like an internal, access-controlled system.
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The risk is not limited to a dramatic data breach. A prompt can put information in the wrong legal jurisdiction, expose it to a vendor or reviewer, violate a customer promise, break a sector rule, or create a permanent record that is difficult to delete. A seemingly harmless combination of facts can also identify a person after a name has been removed.
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NIST’s guidance on personally identifiable information (PII) defines the goal plainly: “PII should be protected from inappropriate access, use, and disclosure.” That standard applies to the information you type yourself and to information about customers, patients, colleagues, family members or other people.
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Credentials and transaction secrets: never enter them
Passwords and authentication codes
Do not paste passwords, passphrases, PINs, one-time authentication codes, recovery codes, private keys, API keys, access tokens, session cookies or backup codes. These values can grant access immediately; asking a chatbot to “check” or “improve” one does not make disclosure safe.
OpenAI warns that passwords shared separately in a chat or document are not covered by secure sign-in protections. A login form’s protection does not extend to a password copied into a conversation. If you need help with an authentication error, provide the error message and a redacted description of the account, never the secret itself.
Payment and banking data
Keep primary account numbers, card numbers, expiration dates, CVV or CVC codes, card PINs, bank-login details, wire instructions and any data that could complete a transaction out of chat. OpenAI’s financial-data guidance specifically says: “Do not use ChatGPT inputs (such as conversations, files, and GPTs) to enter, upload, or share cardholder data as defined by Payment Card Industry Data Security Standard (PCI DSS).”
For a billing question, use the merchant’s authenticated support channel and describe the problem without reproducing the account number. Mask all but the last few digits if an approved support process genuinely requires identification.
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Personal data and records that require an approved workflow
Government identifiers and identity documents
Do not upload passport or driver-license scans, national identification numbers, tax identifiers, immigration records, voting records or a combination of details that uniquely identifies someone. A full name alone may be low risk in one context, but a name plus birth date, address, employer, family information or government number can create a high-impact identity record.
Health and medical information
Patient charts, diagnoses, prescriptions, laboratory results, insurance numbers, therapy notes, appointment histories and medical images belong in a service specifically approved for that use. Removing the patient’s name is not enough if dates, rare conditions, locations, clinician names or unusual events make the person recognizable.
If you need help understanding a general medical concept, ask about the condition in abstract terms or use a fictional case. A chatbot cannot replace a clinician, and a general-purpose service may not provide the confidentiality, retention limits or legal basis required for real patient data.
Financial and customer records
Do not paste tax returns, payroll files, credit reports, loan applications, account statements, customer lists, purchase histories or support tickets containing personal details unless the organization has approved that exact processing. The same rule applies to spreadsheets: hidden columns, comments, formulas and metadata can contain more personal information than the visible table.
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The Federal Trade Commission has noted that model-as-a-service companies may receive confidential internal documents and personal, health and financial data. That observation is a warning about the category of service, not a guarantee that every provider handles data identically. Check the specific product’s terms and your organization’s authorization.
Confidential business information is still sensitive data
Legal, commercial and strategic material
Keep confidential contracts, legal advice, merger or acquisition plans, trade secrets, pricing strategies, unreleased financial results, investor information, board materials and negotiation positions out of an unapproved chatbot. Attorney-client or other professional confidentiality can be weakened when material is sent to a third-party service that has not been authorized by the relevant policy or agreement.
Source code and technical secrets
Do not paste proprietary source code, private repositories, signing certificates, deployment files, infrastructure diagrams, database exports, internal URLs or configuration files containing secrets. Even code without an obvious password can reveal algorithms, vulnerabilities, customer integrations or licensing obligations.
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Security incidents and vulnerability details
Incident timelines, forensic logs, indicators of compromise, exploit steps, unpatched vulnerability details and internal response plans should remain in the organization’s incident system or an explicitly approved security assistant. A public chatbot can become an additional disclosure point while an incident is still active.
Private communications, photos and documents
Private emails, direct messages, meeting transcripts, family correspondence, photos, recordings and documents can expose people who never consented to the upload. Do not assume that because you received a file you have permission to submit it to a separate AI service. Ask whether the task can be completed from a short, redacted summary.
Before sharing, remove names, email addresses, phone numbers, faces, signatures, account numbers, exact dates, precise locations and unique quotations that are not necessary. Preserve only the context needed to answer the question.
Why “de-identified” does not always mean anonymous
De-identification is a risk reduction step, not a guarantee. A person may be re-identified through a combination of role, small-town location, dates, rare medical event, employer, family relationship or sequence of incidents. A document can also contain identifiers in headers, revision history, embedded images, spreadsheet metadata or tracked changes.
- Replace names with neutral labels such as
Customer Aand change exact dates to a month or relative period when precision is unnecessary. - Generalize locations, job titles and ages; remove rare combinations of facts.
- Delete comments, hidden sheets, file metadata and unused attachments before upload.
- Prefer a synthetic example that preserves the structure of the problem without representing a real person or transaction.
Do not claim that information is anonymous unless you have a documented method and a risk assessment supporting that conclusion.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Connected agents add another exposure path
A chatbot that can read email, cloud files, calendars, ticket systems or databases can expose more than the text in your prompt. Malicious instructions hidden in a webpage, document or email can trigger prompt injection: the agent may follow instructions embedded in third-party content rather than your intended task.
OpenAI’s prompt-injection guidance gives a practical control: “Where possible, limit an agent’s access to only the data it needs to complete a task.” Use least-privilege permissions, separate sensitive repositories, disable unnecessary connectors and require a human review before an agent sends messages, changes records, approves payments or publishes content.
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“Enterprise” is not a magic privacy label, and a consumer product is not automatically unsafe for every low-risk question. Decide from documented controls and the sensitivity of the material. Compare these axes before using real data:
| Control | Questions to answer |
|---|---|
| Retention and deletion | How long are prompts and files kept? Can an administrator or user delete them, and are backups covered? |
| Model-improvement use | May inputs be used to improve models? Is the setting off by default, configurable, and enforceable by contract? |
| Human and vendor access | Who can review content for support, safety, abuse prevention or operations? |
| Security controls | Are data encrypted in transit and at rest? Are access logs, strong authentication and role-based permissions available? |
| Confidentiality terms | Does the agreement cover your data, subcontractors, incident notification and permitted processing? |
| Geographic processing | Where are prompts stored and processed, and do transfers meet your legal and contractual requirements? |
| Auditability | Can your organization review activity, export logs and investigate an incident? |
| Authorization | Has your privacy, security, legal or sector-specific owner approved this use case? |
The Information Commissioner’s Office describes a risk-based approach to AI governance and notes that its AI guidance is under review. Treat that as a reason to check current organizational and regional requirements, not as permission to upload sensitive records by default.
A safer workflow for getting useful AI help
- Classify the material. Identify whether it contains credentials, payment data, PII, health or financial records, confidential business information, security details or information about someone else.
- Identify the destination. Determine what leaves your control, which provider receives it, how it may be retained or accessed, and whether the account is organization-approved.
- Minimize the input. Keep only the fields, pages, code lines and time period required for the task. Remove direct identifiers, secrets, exact locations and unnecessary dates.
- Use a synthetic or redacted substitute. Replace real names, amounts, account numbers, URLs and customer scenarios with fictional values that preserve the problem’s structure.
- Apply access limits. For an agent, grant only the repositories and actions needed. Disable broad search, write access and automatic sending when they are unnecessary.
- Review the output and action. Check generated text for hidden disclosure, incorrect assumptions and instructions that came from untrusted content before copying it into a system or approving an action.
Examples: risky prompt versus safer prompt
| Risky input | Safer alternative |
|---|---|
| “Here is my password and the login error.” | “A login returns error code 403 after password reset. What non-secret checks should I perform?” |
| A pasted credit-card number and disputed charge. | “A card transaction was declined yesterday; what information should I gather for the issuer?” |
| A patient’s full chart and request for a summary. | “Summarize this fictional case: adult patient, chronic condition, medication list omitted.” |
| A customer export with names, emails and purchases. | Use an approved internal tool, or provide aggregate counts with identifiers removed. |
| A private repository and production configuration. | Share a minimal, fictional code sample and the sanitized error message. |
If you already pasted sensitive data
Act according to the sensitivity and your organization’s incident procedure; do not wait for proof of misuse. Stop further sharing, record what was submitted and when, and notify the privacy or security team if the data belongs to an employer, customer or patient.
- For exposed passwords, API keys, tokens, recovery codes or private keys, revoke or rotate them immediately and check related access logs.
- For payment data, contact the card issuer or financial institution through its official fraud channel.
- For personal or regulated records, follow breach-assessment, notification and retention procedures applicable to your organization and region.
- Delete the conversation or file where the service permits it, but do not treat deletion as proof that copies, backups or logs no longer exist.
A quick decision test before you press Send
- Would disclosure harm a person, customer, employer or investigation?
- Does the input contain a secret, identifier, regulated record or trade secret?
- Do I have explicit permission to send this exact information to this exact service?
- Can I solve the problem with a summary, aggregate, redaction or synthetic example?
- Is the tool’s retention, training use, access, location and deletion behavior documented?
- If an agent is connected, does it have more data or authority than this task requires?
If any answer is uncertain, do not paste the original material. Use the minimum necessary information in an approved workflow instead.
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