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Freedom251 › Blog › AI Safety

How to Spot and Report AI-Generated Spam, Scams, and Fake Reviews

By Freedom251 Team · · 11 min read

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Do not treat “AI-sounding” writing as proof of fraud. Generative tools can produce convincing reviews, profiles, emails, voice calls, videos and entire scam websites at scale, but a real finding of deception depends on conduct: a false identity, no genuine transaction or experience, impersonation, materially misleading claims, or an attempt to steal money or credentials.

When something looks suspicious, stop interacting, preserve the original evidence, verify the supposed sender through an independent channel, report the content to the service hosting it, and then use the appropriate government and financial-fraud channels. The workflow below shows what to check, what to save and where to file a report.

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What “AI-generated” tells you—and what it does not

AI can generate plausible prose, product photographs, profile pictures, audio, video, chat replies and web pages. A scammer can also combine generated material with stolen names, copied branding and real business details. That makes authorship a weak starting point: a human may edit AI text, and an honest customer may use an AI writing assistant to polish a genuine opinion.

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The relevant question is whether the content is deceptive. A review is potentially fraudulent when the named person does not exist, never bought or used the product, is being impersonated, or is presented as having an opinion they did not hold. A message is potentially a scam when it impersonates an organization, creates false urgency, requests money or credentials, or directs you to a site or account controlled by the sender.

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“Since it can be difficult to identify when content is AI-generated, the FBI is providing the following examples to increase public recognition and scrutiny.”

Use AI clues to decide when to verify; do not use them alone to accuse a person or remove a review. False positives can harm legitimate reviewers and businesses.

Signals that deserve verification

No single signal proves that a post or message was generated by AI or is fraudulent. Look for several independent indicators, then confirm the underlying identity, transaction and requested action.

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Signal What to examine Why it matters
Unnatural or recycled language Generic praise or outrage, repeated sentence patterns, vague descriptions, identical phrases across accounts, or a sudden change in a person’s normal style. Templates and generation tools make it inexpensive to produce many variants, but ordinary users can also write in a formulaic way.
Review bursts Many reviews posted within a short period, especially for one business or from accounts created at the same time. Coordinated campaigns often have timing patterns that a single review cannot show.
Extreme or unverifiable claims “Guaranteed” results, impossible performance, medical or financial promises, or specific events that do not match the product or service record. Materially misleading claims matter more than whether a sentence was machine-written.
Mismatched details A reviewer names a model, location, date, shipping method or feature that the business never offered, or a message references an account you do not have. Inconsistencies can reveal copied text, impersonation or a fabricated transaction.
Suspicious account history New profile, little activity, unrelated locations, repeated five-star or one-star posts, stolen-looking photos, or usernames that imitate an official account. Identity and history provide context that text style cannot.
Impersonation Look-alike domains, profile names, logos, signatures, caller IDs or voices claiming to be a bank, government agency, employer or merchant. Scammers use generated media to make a false identity appear credible.
Urgency and secrecy Demands to act immediately, keep the request confidential, bypass normal approval, or move to a private chat. Pressure prevents independent verification and is common in impersonation scams.
Requests for money or credentials Gift cards, cryptocurrency, wire transfers, payment-app transfers, one-time codes, passwords, identity documents or remote-access software. The requested action and payment method often distinguish a scam from a routine notification.

These indicators are screening signals, not a detector score. Short text, edited text and multilingual writing can evade automated detectors, while genuine writing can trigger them. Treat a detector result as one weak data point and seek corroborating behavioral, identity and transaction evidence.

Verify the claim without increasing your risk

  1. Stop engagement. Do not reply, click, download an attachment, share a code, or pay while authenticity is uncertain. A reply can confirm that your address or phone number is active.
  2. Open the trusted route yourself. Type the organization’s known domain, use its official app or select a bookmark you created earlier. Do not use a link, QR code, phone number or email address supplied in the suspicious content.
  3. Contact the purported organization independently. Use a number printed on a statement or card, or a contact method listed on the organization’s own site. Ask whether the message, invoice, account change or review campaign is genuine.
  4. Check the transaction and identity. For a review, look for an order, appointment or visit that matches the date, location, product and account. For a message, inspect the sender domain, message headers, account activity and the destination address without signing in.
  5. Compare explanations. If both an innocent mistake and coordinated fraud fit the facts, compare identity history, timing, consistency with verifiable product or transaction details, language or media reused across accounts, the requested action and payment method, and the platform policy that may have been violated.

Verification is not an invitation to confront the suspected author. Let the platform, financial institution or investigator assess disputed identity and intent.

Preserve evidence before the post or account disappears

Capture evidence while you can still view it, and keep an untouched copy separate from any edited notes. Google’s safety guidance for malicious review-bombing or merchant extortion specifically says to preserve “screenshots, emails, chat logs” for law enforcement.

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  • Location: Save the complete URL, platform name, review or post ID if shown, profile URL and the business or account name.
  • Time: Record the date and time you saw the content, including your time zone. Note when a call, payment request or account change occurred.
  • Visual record: Take dated screenshots that include the username, profile image, wording, ratings, replies, links and any warning banner. Capture the surrounding page so the context is clear.
  • Original messages: Preserve the email in its original form, including headers or message metadata when your mail service allows it. Export chat logs rather than relying only on screenshots.
  • Contact details: Record phone numbers, email addresses, usernames, domain names, wallet addresses and payment handles exactly as displayed.
  • Financial records: Keep receipts, invoices, bank or card transaction entries, payment-app confirmations, gift-card numbers and shipping records. Do not send full account numbers in a public report unless the recipient specifically requires them through a secure form.
  • Conversation history: Save the complete thread, not just the message containing the demand. Include attachments without opening them and note whether a file was downloaded.
  • Your account of events: Write a short chronology while the details are fresh: what you received, how you verified it, what you clicked or disclosed, and what loss or exposure followed.

Do not alter the original files. If you must redact a copy for a public-facing platform form, retain the unredacted evidence for the platform, your bank or law enforcement.

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Report at the point of abuse first

Use the platform’s own reporting path because its moderators can remove a review, suspend an account, preserve logs or contact the affected business. Choose the category that describes the conduct, not merely the possibility that software wrote the text.

  1. Open the content or profile. Use the review, post, message or account menu and select Report, Flag, Spam, Impersonation, Phishing, Fraud or the closest available option.
  2. Provide precise identifiers. Include the original URL, account name, profile link, dates, transaction or order reference when relevant, and a concise description of the observable violation.
  3. Explain the evidence. State, for example, that the profile claims a purchase that cannot be matched to any order, that several accounts reused the same wording within an hour, or that the sender requested a one-time code while impersonating a bank. Avoid asserting “AI” as the only proof.
  4. Attach safe copies. Upload screenshots or exported logs if the form accepts them. Never upload passwords, full payment credentials or identity documents unless the platform’s verified secure process requires them.
  5. Save the case number. Keep the confirmation email, ticket number and date. Do not repeatedly submit identical reports; add new evidence to the existing case where possible.

For malicious review-bombing or extortion, Google’s advisory says: “Immediately report the malicious activity using the official merchant extortion report form, and be sure to preserve all records (screenshots, emails, chat logs) of their demands as evidence for law enforcement.” Use the official form reached from the service’s own help center rather than a link supplied by the extorter.

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Use government and financial-fraud channels

Situation Next report What to include
Consumer fraud, an impersonation attempt or a deceptive review in the United States ReportFraud.ftc.gov Your contact information, the impersonated organization, dates, amount lost or requested, payment method, URLs, phone numbers and a factual narrative.
Internet-enabled crime, credential theft, coordinated activity or financial loss IC3.gov Suspect identifiers, domains, email and phone details, transaction records, cryptocurrency addresses if relevant, screenshots and a chronology.
Unauthorized card, bank or payment-app activity Your bank, card issuer, payment app or account provider, using an independently verified contact route The transaction date and amount, recipient, dispute details, account exposure and any steps already taken. Ask what account holds, recalls or resets are available.
Compromised credentials or an account takeover The affected service’s official recovery and abuse channel Account identifier, takeover time, password-reset evidence and the devices or sessions you still control.

The FTC reported $2.95 billion in consumer losses from impersonation scams in 2024. Its 2024 data put the median loss to an FTC impersonator at $7,000, up from $3,000 in 2019. Those figures describe reported U.S. consumer losses and do not predict the loss in an individual case; report even when the amount is zero.

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What the U.S. review rule changes

The FTC’s Consumer Reviews and Testimonials Rule took effect on October 21, 2024. It covers fake or false reviews and testimonials attributed to nonexistent people, AI-generated personas or people without actual experience, and prohibits specified deceptive review practices. The rule focuses on the truthfulness and attribution of the testimonial, not on proving which software produced the words.

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When reporting a suspected review, document the factual basis: no matching transaction, an invented employee or customer, coordinated accounts, an impersonated individual, or a claim that materially misrepresents the product. A business should not report a legitimate negative review merely because it is polished, unusually short or grammatically unusual.

FTC consumer guidance says: “Report fake reviews to the website or platform where they appear — like Google, Amazon, or Walmart, among others.” The platform report is the first practical step; the FTC channel adds a consumer-fraud record and does not replace the host’s moderation process.

How to distinguish a fake review from an honest AI-assisted review

Check identity and experience

Ask whether the profile belongs to a real person and whether that person could have had the claimed experience. Compare the review’s date, location, model or service tier with business records available to you. A missing public order number is not conclusive because privacy settings and offline purchases can hide it, but several independent mismatches are meaningful.

Check coordination

Map the posting times, account creation dates, wording, images and destinations. Reviews from unrelated accounts that appear in a narrow burst and reuse unusual phrases deserve escalation. Preserve each URL instead of reporting only one representative account.

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Check the claim, not the prose style

Specific, verifiable details can be genuine even when the grammar is polished. Conversely, a human-written review can be fabricated. Describe what is false, impossible or impersonated, and let the platform decide whether the review violates its policy.

Common scam patterns involving generated media

  • Executive or family impersonation: A convincing voice note or video asks for an urgent transfer. Verify through a known number and require the normal approval process.
  • Account or delivery notices: A branded email or text claims that payment, identity or delivery information must be updated. Open the official app or type the known domain rather than following the message link.
  • Investment, employment or romance approaches: A polished profile builds trust, then requests fees, cryptocurrency, gift cards or account access. Search independently for the organization and refuse unusual payment methods.
  • Review extortion: A person threatens a wave of negative reviews unless money or free goods are provided. Preserve every demand, do not negotiate, report the activity through the platform’s official merchant channel and include the records in an IC3 or FTC report as appropriate.
  • Fake support: A look-alike account replies to a public complaint and asks for a password or remote-access session. Contact support through the service’s published app or site instead.

Protect accounts and finances after exposure

  1. Change any exposed password from a clean device, beginning with email and financial accounts. Do not reuse the new password elsewhere.
  2. Enable multifactor authentication, preferably with the strongest method the service supports, and review recovery email addresses, phone numbers, forwarding rules and active sessions.
  3. Call the bank, card issuer, payment app or account provider through a number from a statement, card or independently opened official site. Ask about freezing, reversing or disputing the transaction.
  4. Monitor statements, login alerts, credit activity and password-reset notices. Save new alerts as part of the incident timeline.
  5. Warn people who may be targeted through the compromised account, but do not forward malicious links or attachments.

Reporting cannot guarantee removal, reimbursement or prosecution. It creates a record and gives the service, financial institution and investigators the identifiers they need to connect related incidents.

Frequent mistakes to avoid

  • Relying on an AI detector alone: Detector scores vary with length, editing and language. Pair them with identity, timing and transaction evidence.
  • Clicking to “test” a link: A preview can still load a tracking page or exploit. Use a separately opened official route.
  • Confronting the suspected author: It can trigger deletion, retaliation or further social engineering. Report observable conduct instead.
  • Publishing personal data: Do not dox a reviewer or expose a victim’s phone number, address, credentials or full payment details. Give sensitive material only to a verified reporting channel.
  • Waiting to collect perfect proof: Save what is available and report promptly; platforms may retain additional logs that you cannot see.
  • Assuming a small loss is not worth reporting: Aggregated reports help identify campaigns, and early bank contact can improve recovery options.

A compact decision checklist

  • Is there a false identity, missing real-world experience, impersonation or materially misleading claim?
  • Do timing, account history, reused media or payment demands suggest coordination?
  • Have you stopped engagement and avoided the supplied links and contact details?
  • Did you save the URL, profile, timestamps, screenshots, headers, chats and transaction records?
  • Did you verify the supposed sender through a typed domain, official app, bookmark or known phone number?
  • Did you report the content to its host using the closest spam, impersonation, phishing or fraud category?
  • Did you file with ReportFraud.ftc.gov or IC3.gov when the conduct fits, and notify the relevant financial provider?
  • Did you change exposed credentials, enable multifactor authentication and monitor accounts?

The safest standard is evidence-led skepticism: pause, verify independently, preserve the record and describe the conduct precisely. Whether a language model helped write the content is secondary to whether the identity, experience and transaction behind it are real.

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