India’s largest e-commerce player x Hunto AI
How an India’s largest E-Commerce playter protects its assets with Hunto AI takedowns.
Industry
E-commerce/Marketplace
Employees
30k+ (ecosystem: hundreds of thousands of sellers)
Solutions used
Hunto AI — Takedown Service
Operations
Pan-India, app + web, multi-category retail
About Client
India’s largest e-commerce player operates a nationwide marketplace spanning electronics, fashion, home, grocery, and more. With peak season campaigns, high-velocity flash sales, and a vast third-party seller network, the company runs one of the country’s most visible consumer brands.
That visibility attracts fraudsters who spin up look-alike domains, fake apps, social imposters, and search ads designed to divert payments and harvest customer data, directly impacting trust, support load, and revenue.
Problem Statement and Challenges Faced
As seasonal traffic surged, the client’s security and brand teams grappled with a rapidly changing external landscape:
Exploding brand impersonation: Fraudsters launched phishing domains, counterfeit app listings, and “support” social handles. Many were short-lived but highly convincing, surfacing during festivals and major sales.
Search & social abuse: Paid ads and boosted posts occasionally outranked legitimate results during campaign windows, siphoning users to scam pages.
Manual, slow, fragmented takedowns: Each platform (registrars, hosts, social networks, app stores, ad networks) required different evidence formats, contacts, and legal phrasing, consuming hours per incident and creating backlogs.
Customer & support impact: Scam fallout drove ticket spikes and reputation strain; CX teams lacked a single source of truth to educate customers in real time.
Proof for leadership: Marketing, risk, and legal needed evidence-ready reporting quantifying exposure, actions taken, and revenue/cost protection, without adding headcount.
Business risk if unaddressed: Loss of revenue, loss of customer trust, conversion drop on key funnels, increased chargebacks/refunds, rising support costs, and reputational damage during flagship events.
Hunto AI Solution (How We Helped)
Objective:
Detect and remove brand-abuse infrastructure quickly across domains, social, app stores, and ads, while generating evidence credible for leadership and partners.
Rapid Onboarding & Playbooks
Hotlist ingestion: Official domains, social handles, app IDs, campaign keywords, and seller-support phrases.
Abuse patterns library: Known typosquats (IDN homographs), fake-coupon lures, OTP/UPI bait, refund scams, and “priority support” scripts—seeded into our monitors.
Unified SOPs: Takedown playbooks customized per registrar/host/platform/ad network, including legal hooks and policy references.
24/7 Brand Monitoring
Look-alike domain hunt: Fuzzy-matching + passive DNS to flag suspicious registrations as they appear (not just when they rank).
App store sweeps: Periodic and event-driven scans for clone apps, logo/name/description misuses, and malicious SDK markers.
Social & messaging: Detection of imposter handles, scam giveaway pages, and link farms; packaging of platform-specific violation evidence.
Search ads & SEO traps: Monitoring of malicious paid placements and SEO-poisoned pages that intercept branded searches.
Takedown Automation with Evidence
Agentic evidence packs: For each incident, Hunto AI auto-builds a dossier—screenshots, WHOIS/ASN, hosting metadata, link graphs, timestamps, and policy-line citations.
One-click notices: Registrar/host abuse desks, social platforms, app stores, and ad networks receive pre-formatted submissions with all proofs attached.
Chaining & mirroring control: After primary removal, the system re-scans for mirrors and related infrastructure to prevent whack-a-mole recurrence.
Customer-Safety & Internal Enablement
“Official channels” microsnippet: A ready-to-paste banner/FAQ for CX, clarifying verified URLs/handles and how to spot fakes.
Weekly intel to Marketing/Legal: Emerging lure themes (e.g., delivery rescheduling, payment failures) to inform campaign copy and reduce social-engineering success
Reporting & Governance
Executive dashboard: Volume of detections, median Time-to-Takedown (TTD), survival time of scams, and revenue-risk protection proxy.
Evidence archive: Audit-ready case files and a monthly Board/Leadership pack summarizing trends, hotspots, and recommended mitigations
Impact
“Hunto AI turned brand abuse into an operational metric we could actually control. We now remove impersonators within hours, protect campaign traffic, and brief leadership with evidence instead of anecdotes.”
— Head of Risk & Brand Protection
Results in the first 90 days (figures adapted for public sharing):
- Takedown velocity: Median TTD < 24 hours for domains/hosts; < 12 hours for social/app listings after evidence submission.
- Scale: 400+ abusive assets detected; ~78% removed on first notice; most remaining cleared after one follow-up.
- Search protection: Malicious paid placements detected and reported within 2–6 hours of first appearance during sales peaks.
- Support deflection: CX scripts + “official channel” guidance correlated with a measurable drop in scam-related tickets during campaign weeks.
- Revenue protection proxy: Reduced leakage from diverted traffic and payment fraud vectors during marquee events (directionally validated against campaign analytics).
Why Hunto AI worked here
- Speed & breadth: Multi-surface monitoring (domains, social, app stores, ads) with agentic evidence assembly shaved days off traditional takedowns.
- Platform-native submissions: Each platform got the right template, proof, and policy citation—first-time acceptance rate improved significantly.
- Closed loop: From signal → takedown → mirror hunt → CX guidance → exec reporting, the client gained a repeatable muscle for the busiest retail weeks.
About Hunto AI
Hunto AI quantifies external cyber and brand risk, and resolves it automatically. Our Brand Monitoring & Takedown Service pairs real-world detection with one-click, evidence-rich removals. Adjacent modules include Attack Surface Monitoring (shadow assets, misconfigurations) and Human Risk (phishing simulations) to harden customer-facing operations end-to-end
Note: Client identity and certain metrics are anonymized due to confidentiality commitments.