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brand-impersonation-response

Respond to a brand or executive impersonation incident — deepfaked executives, cloned support lines, fake apps, spoofed domains, or AI-generated scam content wearing your name

Install / Use

npx skills add mohitagw15856/pm-claude-skills --skill brand-impersonation-response

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

85/100

Supported Platforms

Universal

Tags

Our assessment of brand-impersonation-response

brand-impersonation-response scores 85/100 on our quality scale, 172nd of 335 Customer Support skills we index.

Its SKILL.md is 6.3 KB long, well organised into 8 sections and no code examples: a thorough specification that gives an agent plenty to work with.

With 1,396 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
13/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 8 days ago, so brand-impersonation-response is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

brand-impersonation-response compared with similar skills

All 4 of these similar skills score higher than brand-impersonation-response; compare them before choosing.

SkillScoreStarsUpdatedFormat
brand-impersonation-response (this skill)by mohitagw15856851.4k8d agoSKILL.md
algorithmic-artby anthropics100177.9k10d agoSKILL.md
pptxby anthropics100177.9k10d agoSKILL.md
designby nextlevelbuilder100130.2k11d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k11d agoSKILL.md

Frequently asked questions

How do I install brand-impersonation-response?
Run npx skills add mohitagw15856/pm-claude-skills --skill brand-impersonation-response. The install tabs above show the steps for each supported agent.
Which AI agents does brand-impersonation-response work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is brand-impersonation-response safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is brand-impersonation-response still maintained?
The repository was last updated 8 days ago, so brand-impersonation-response is actively maintained.

name: brand-impersonation-response description: "Respond to a brand or executive impersonation incident — deepfaked executives, cloned support lines, fake apps, spoofed domains, or AI-generated scam content wearing your name. Use when a deepfake of a leader is circulating, customers report a fake version of your product or support channel, or to prepare the impersonation playbook before it happens. Produces an incident response: verification protocol, takedown sequencing by platform, customer and public communications, and the hardening plan. For general crisis comms use press-release/pm-crisis skills; for security incidents inside your systems use security-incident-response."

Brand Impersonation Response Skill

Cheap generative tools made impersonation an industrial product: a CEO deepfake pushing a token, a cloned support line harvesting card numbers, a spoofed checkout collecting credentials. The attack isn't on your systems — it's on your customers' trust, using your face. Speed and sequencing decide the damage; this skill runs both.

What This Skill Produces

  • A verification protocol — confirm it's fake, preserve evidence, assess reach before amplifying it
  • A takedown sequence by platform/registrar/store, with the escalation paths that actually work
  • Communications for each audience: targeted customers, all customers, public, employees, and (deepfaked) the impersonated person
  • A hardening plan so the next attempt lands softer

Required Inputs

Ask for (if not already provided):

  • What's circulating: the artifact (video/audio/site/app/account), where it lives, how it was discovered
  • The harm mechanism: financial scam? credential harvesting? reputation/market manipulation? (Drives urgency and legal posture)
  • Reach so far — views, victim reports, whether it's spreading or stagnant
  • Who's impersonated — the brand, a product surface, or a named human (a deepfaked person is also a victim; the response includes them)

Response Method

Phase 1 — Verify and preserve (first hours). Confirm fabrication with the impersonated party directly (deepfakes are good; "that's obviously fake" is not a verification method). Preserve everything before takedowns delete the evidence: URLs, hashes, screen recordings, WHOIS, wallet addresses, timestamps — the takedown kills the scam, the evidence supports fraud referrals and platform escalation. Quietly assess reach; do not publicly respond yet — a statement about a 400-view scam gives it 40,000.

Phase 2 — Contain (same day). Takedowns in parallel, sequenced by harm-per-hour:

  • Payment/credential harvesting first: hosting provider + registrar (impersonation/phishing abuse reports), Google Safe Browsing / Microsoft SmartScreen flagging (kills most browser traffic faster than the registrar acts), payment processor fraud teams if cards are flowing
  • Platforms: impersonation reports via brand/IP channels, not generic user reports — trademark-based reports move in hours where "report account" moves in weeks; file with rights documentation attached
  • App stores: developer-impersonation + trademark claims through the formal IP channels
  • Route it as fraud, not just abuse, where money moved: law enforcement referral (IC3 or local equivalent) — platforms escalate faster with a case number Log every report: platform, ticket, time — the log is the escalation tool when nothing moves.

Phase 3 — Communicate (as reach demands). The proportionality rule: warn the targeted, inform the asking, broadcast only when reach forces it.

  • Targeted/victimised customers immediately: what happened, what we will never ask (the anchor line: "we will never DM you for payment/credentials/wallet transfers"), what to do if they engaged, one report channel
  • The impersonated executive (deepfake cases): they're a victim, not just an asset — align their personal statement with the company's; one voice
  • Public statement only past the reach threshold: short, factual, no link or screenshot of the fake, the never-ask anchor, the report channel. Never repeat the scam's claims in the correction (repetition entrenches)
  • Support + social teams get the script before the public does — they're already getting the questions

Phase 4 — Harden (the week after). Verification anchors customers can check (verified handles list on your domain, DMARC/BIMI, signed comms for high-stakes messages) · monitoring for the next round (domain-permutation watch, brand-mention alerts, app-store sweeps — impersonators retry) · the internal deepfake protocol (a "CEO" voice call requesting a transfer gets a callback on a known number — write it down now) · pre-registered abuse contacts at the platforms that were slow this time.

Output Format

Impersonation Response: [what's circulating] — [date]

Verification: [how fabrication was confirmed · evidence preserved (list) · reach assessment]

Takedown log | Target | Channel used | Filed | Status | Escalation path | |---|---|---|---|---|

Communications (drafted, per audience): [targeted-customer notice · support script · public statement (with its reach trigger) · executive's personal statement if applicable]

The never-ask anchor: [the exact line, everywhere]

Hardening plan: [verification anchors · monitoring · internal deepfake protocol · owner + dates]

Quality Checks

  • [ ] Evidence was preserved before takedowns were filed
  • [ ] Takedowns route through IP/trademark channels with documentation, not generic reports
  • [ ] Public response is gated on a stated reach threshold, not reflex
  • [ ] No communication links, screenshots, or restates the scam's content
  • [ ] Money-moved cases include the law-enforcement referral
  • [ ] The hardening plan includes the internal voice-deepfake protocol

Anti-Patterns

  • [ ] Do not amplify a low-reach scam with a high-reach denial — proportionality is the discipline
  • [ ] Do not file generic "report this account" tickets when trademark channels exist — wrong queue, weeks lost
  • [ ] Do not let takedowns destroy the evidence — preserve first, always
  • [ ] Do not leave the deepfaked human out of the response — an executive learning the plan from the press release is a second incident
  • [ ] Do not treat it as a one-off — impersonation that worked once is a campaign; monitoring is part of the response, not the postscript

Related Skills

View on GitHub
GitHub Stars1.4k
CategoryCustomer
Updated8d ago
Forks249

Languages

HTML

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions