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Use the report or feedback control attached to the unsafe answer whenever one is available. Explain exactly what the chatbot did, preserve enough surrounding conversation to make the problem reproducible, and inspect the data that will be sent before you submit. A legal-content complaint, a security vulnerability, and an ordinary bad answer usually have different reporting routes.
What counts as an unsafe chatbot response?
An unsafe response is more than an answer you dislike. It can provide dangerous instructions, encourage illegal activity, expose private information, make a high-stakes claim without appropriate caution, produce hateful or abusive material, or fail to refuse a request that should have been refused. A response can also be unsafe because of the context it uses: for example, it may quote a private file, email, image, or connected-app record that you did not expect to be included.
Accuracy matters as well. A confident medical, legal, financial, security, or emergency answer can create harm even when the wording is polite. Report the behavior that creates the risk, not just the conclusion you disagree with. If the issue is a policy violation, local-law concern, or security weakness, use the specialist route described by the provider instead of treating it as ordinary quality feedback.
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Report the specific answer first
Response-level controls give the provider the clearest target. They normally preserve the answer and at least some conversation context, so the review team can see what led to the output. Labels and locations can change by product surface, account type, device, and country; use the current label shown in your app.
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ChatGPT
- Find the message that contains the unsafe answer.
- Select the thumbs-down control beneath that message.
- Choose Select an issue, then select Safety or Legal concern.
- Follow the prompts and describe the behavior in your own words. Include the smallest amount of surrounding conversation needed to explain the risk.
OpenAI also documents separate ways to report shared links, GPT conversations, GPTs, advertisements, and forum posts. Choose the route for the item itself rather than assuming that message feedback covers every surface. A content-reporting webform is available for cases that do not fit the in-product control. OpenAI says reports and other signals can be reviewed by its Model Quality team, which may apply filters or other mitigations; the documentation does not promise a particular action for every report.
Claude
Claude provides an in-product report button for shared content and a separate reporting form. Use the safety-report route for a troubling answer or for a safety mechanism that is causing a user-experience problem. Anthropic asks for enough detail to replicate the issue, so include the relevant prompt sequence, the resulting answer, and the conditions under which it occurred.
Policy or local-law concerns use a separate content-report route. Universal jailbreaks and security vulnerabilities have their own disclosure guidance; those channels are intended for vulnerability reporting, including the security-research cases described in Anthropic’s guidance, not for routine feedback about one unpleasant answer.
Gemini
- Under the answer, choose Good response or Bad response.
- For a harmful or offensive result, choose the Offensive / Unsafe reason when it is offered.
- Add a concise explanation and submit the feedback.
For a problem that is not tied to one answer, use Settings & help → Send feedback. A legal concern has a separate Report legal issue option. In Gemini for Workspace, use Report abuse next to the response or under More options. General answer feedback uses the separate good/bad suggestion flow.
Choose the right route for the problem
| Situation | Best starting route | What to emphasize |
|---|---|---|
| One answer gives dangerous, abusive, or seriously misleading content | Response-level safety feedback | The exact output, the preceding prompt, and why the behavior is unsafe |
| A shared page, public conversation, GPT, advertisement, or forum post is problematic | The reporting control for that item | The item’s location and the specific content to review |
| A suspected violation of law or a rights-related complaint | The provider’s legal or content-report form | The jurisdiction, relevant content, and the legal issue, without unrelated personal data |
| A reproducible security flaw or universal jailbreak | The provider’s vulnerability or responsible-disclosure route | Reproduction steps, impact, affected product or version, and safe disclosure details |
| A general product problem with no single answer | General feedback or support form | When it occurs, how often, and which feature is affected |
Do not send a vulnerability report through a public forum or attach exploit material to a routine thumbs-down unless the provider specifically asks for it. Conversely, do not label a single inaccurate answer as a security vulnerability unless you can explain a security impact.
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What to include so the provider can reproduce it
A bare thumbs-down records dissatisfaction but may not explain the failure. A reproducible report lets an investigator distinguish a one-off generation from a repeatable safety gap.
Identify the product surface
- Chatbot name and the surface used: web app, mobile app, API-backed feature, shared link, or Workspace integration.
- Account or workspace context when relevant, such as a managed organizational account.
- The feature involved, including a custom GPT, shared conversation, connected app, file upload, or image input.
- The approximate date and time, your time zone, and the device or app version if it is visible.
Preserve the causal sequence
- Quote the prompt that immediately preceded the unsafe answer.
- Keep earlier turns that changed the meaning of the request, such as role instructions, uploaded documents, or a prior refusal.
- State whether you repeated the request and whether the same behavior occurred again.
- Describe any settings, tools, browsing mode, connectors, or permissions that were enabled.
Do not rewrite the answer to make it sound worse or better. If the output is long, quote the dangerous passage and enough surrounding text to show its context. A screenshot can help when formatting, an image, or a user-interface control is part of the problem, but it should not expose unrelated private information.
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Explain the safety failure
Use plain, specific language: “The answer supplied step-by-step instructions for harming a person,” “It stated a medical emergency was harmless without asking about symptoms,” or “It revealed text from a connected document that was not relevant to my request.” Say what a safer response would have done, such as refusing, asking a clarifying question, adding an appropriate limitation, or omitting unrelated private content.
Describe impact without exaggerating
State who could be affected and how: immediate physical risk, privacy exposure, fraud risk, harassment, unsafe professional advice, or a misleading public share. Separate observed harm from a potential consequence. If no one was harmed, say that the risk was prospective. Accurate reports are easier to assess than claims that cannot be verified.
Inspect what will be attached before submitting
The text you type into a feedback box may not be the entire report. Google says Gemini feedback can include the associated conversation, including prompts and responses, and may also include uploaded files, images, and personal content from connected apps. In Gemini for Workspace, an abuse report can include the prompts, context documents, emails, and Gemini response used to generate the answer.
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Before sending, look for names, addresses, account numbers, health information, confidential work documents, customer records, passwords, API keys, private images, or other data that is not necessary to investigate the issue. Remove unrelated material when the interface allows it. If the reporting flow automatically includes context that you cannot edit, decide whether that disclosure is appropriate for your circumstances and use a support or legal channel when you need to explain the concern without sending the full content.
Do not paste secrets into a report to prove that a model exposed them. Describe the type of secret, redact most characters, and preserve only a harmless identifier if the provider needs to locate the event. Keep an unredacted copy only in a secure place that you control, subject to your organization’s retention rules.
How to write a high-quality report
The following format works in an in-product form, a support ticket, or a specialist disclosure channel. Adapt it to the fields the provider presents.
Product and feature: [name and surface]
Time and time zone: [approximate date and time]
Prompt sequence: [relevant prompts in order]
Unsafe output: [short quote or description]
Why it is unsafe: [specific risk or policy concern]
Reproduction: [steps, settings, files, and whether it repeated]
Expected safer behavior: [refusal, warning, clarification, or redaction]
Data attached: [conversation, file, image, or none]Keep the first sentence useful to a triage reviewer. For example: “On the mobile app, after I uploaded a lease and asked for a summary, the answer reproduced a neighbor’s unrelated personal details from the file.” Then provide the sequence and evidence. Avoid insults, speculation about the provider’s motives, and a long account of unrelated frustrations.
Improving safety while you use a chatbot
Reporting helps a provider find failures, but you can reduce exposure during the same session. These practices do not make a chatbot reliable by themselves; they create clearer boundaries and make unsafe behavior easier to detect.
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Limit the information you share
- Remove names, contact details, account numbers, credentials, exact locations, and other identifiers before uploading text.
- Upload only the pages or fields needed for the task instead of an entire mailbox, customer export, or case file.
- Disconnect integrations that are not required for the request and review which files or apps are in scope.
- Use synthetic examples when testing a workflow or a safety boundary.
Ask for bounded, checkable work
- State the intended use and the limits: for example, “Summarize these symptoms and list questions for a clinician; do not diagnose or recommend a treatment.”
- Ask the model to identify uncertainty, missing information, and assumptions.
- Request citations or quotations from the material you supplied when the task is summarization.
- Break high-stakes work into smaller steps so you can inspect each output before acting on it.
Verify before acting
Independently check medical, legal, financial, safety, identity, and security claims with a qualified professional or an authoritative source. Treat generated code, commands, and configuration changes as untrusted until reviewed in a safe environment. Never let a confident tone substitute for evidence.
Test refusal and privacy boundaries carefully
If you are evaluating a system, use benign test cases that demonstrate the boundary without requesting real-world harm. Record whether the model refuses, redirects, asks for clarification, or leaks information. Stop testing if the output begins to provide actionable dangerous instructions, and report the result through the appropriate channel rather than escalating the request repeatedly.
When the issue is urgent
If a response suggests an immediate threat to someone’s safety, do not wait for a platform review. Contact local emergency services or an appropriate crisis or safeguarding organization, and warn the person at risk when doing so is safe. Preserve relevant evidence without redistributing dangerous instructions. The chatbot report is still valuable, but it is not an emergency-response service.
For workplace, school, or regulated environments, follow the organization’s incident process as well as the provider’s form. A security, privacy, or compliance officer may need to contain access, preserve logs, notify affected people, or assess reporting duties.
What happens after you submit?
Providers combine user reports with automated detection and other review signals. OpenAI says it uses automated tools to detect potentially harmful prompts, completions, and uploads and that trained experts review reports alongside those systems. Its transparency guidance says any moderation or enforcement decision depends on circumstances such as legal requirements, severity, and prior or repeat violations.
That means a report is an input to a review process, not a promise of removal, an account action, a model change, or a response by a particular date. Keep the confirmation number or case correspondence if one is provided. If the issue continues, submit a concise follow-up that references the earlier report and supplies new evidence instead of filing many identical reports.
Common reporting mistakes
- Using the wrong channel: send legal complaints and vulnerability disclosures through their specialist routes.
- Providing no context: include the prompt and the turn that triggered the answer, not just a screenshot of the final sentence.
- Oversharing: remove unrelated private data and inspect automatic attachments.
- Editing the evidence: preserve the original wording and identify any redactions.
- Overstating the result: distinguish an observed output from a feared consequence.
- Assuming a label is universal: interface names differ by app, account, locale, and date; choose the closest current category.
- Expecting instant repair: a report may inform filtering, investigation, or future model work, but no particular outcome is guaranteed.
A quick pre-submission checklist
- Did you select the control attached to the specific unsafe answer or item?
- Is the issue categorized accurately as safety, legal, abuse, privacy, or security?
- Did you include the relevant prompt sequence and feature settings?
- Can another reviewer understand the risk without guessing?
- Did you state whether the behavior reproduced?
- Did you check files, images, connected apps, documents, and emails that may be attached?
- Did you remove secrets and unrelated personal information?
- Are urgent real-world risks being handled through an emergency or organizational process?
Frequently Asked Questions
Can I report a chatbot answer without sending the whole conversation?
Sometimes. The controls differ by provider and feature, and some feedback flows automatically include associated prompts, responses, files, images, or connected-app content. Review the submission preview or form information; if you cannot limit the attachment, use the provider’s support or legal route to discuss the disclosure.
Should I report an inaccurate answer as a security vulnerability?
Usually not. An isolated wrong answer belongs in response-level safety or quality feedback. Use a vulnerability or responsible-disclosure route when you can show a reproducible security weakness, such as unauthorized access or a systematic bypass with security impact.
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What if the chatbot’s interface has no report button?
Use the provider’s general feedback, support, content-reporting, or legal form and identify the product surface. Include the same reproducible details you would have entered in response-level feedback.
Does submitting a report guarantee that the answer will be removed or the model changed?
No. Providers describe review and possible mitigation, but decisions depend on the circumstances, applicable requirements, severity, and other factors. Keep the report factual and do not promise a particular outcome to someone else.
The Bottom Line
Report the exact unsafe response through the provider’s own control, provide a reproducible account, and inspect every attachment before sending. Use legal and security channels for those distinct issues, protect private data, and treat the report as a contribution to review—not a guaranteed fix.
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