How LivQuik Secures Its Assets with Hunto AI Takedowns

Industry

RBI-authorised PPI issuer and UPI wallet provider

Scale

~₹9.96 Cr revenue in FY23

Product used

Hunto AI Brand Monitoring and Takedown

Location

India

LivQuik Technology Pvt. Ltd

About Client

LivQuik issues consumer and co-branded prepaid payment instruments and operates wallet and UPI experiences for day-to-day payments. Its public footprint includes corporate and product websites, app listings, onboarding flows, FAQs and social channels. That footprint is a magnet for look-alike domains, fake support pages and clone apps that try to harvest OTPs, UPI credentials and KYC data, or charge bogus “activation” fees.

LivQuik’s own pages describe its PPI product and wallet types, underscoring a customer-facing posture where brand integrity and fraud suppression directly affect conversion, retention and compliance posture.

Challenges faced

Impersonation and fraud leakage
Attackers stood up spoofed domains, counterfeit app listings and imposter support handles. Common lures included KYC revalidation, wallet upgrade, refund or settlement verification and priority onboarding. These aimed to collect OTPs or payment details or to solicit fees from users and merchants.

Hijacked brand queries
During feature launches or marketing pushes, malicious ads and SEO-poisoned pages briefly outranked official results for high-intent queries such as “LivQuik login,” “wallet KYC update,” “customer care,” and “UPI help,” diverting users into phishing funnels.

Fragmented takedowns and long cycle times
Registrars, hosts, social networks, app stores and ad networks all required different evidence artifacts and policy hooks. Manual submissions and scattered screenshots slowed time-to-takedown, and mirrors resurfaced.

Compliance and assurance expectations
As an RBI-authorised payments operator, LivQuik must evidence continuous surveillance, timely incident handling and oversight of vendor-managed public surfaces. Security and compliance teams needed artifact-rich case files that map to RBI’s new Master Direction on Cyber Resilience and Digital Payment Security Controls for non-bank PSOs and the Outsourcing of IT Services Directions, 2023, while also aligning with CERT-In incident reporting and DPDP Act obligations.

Hunto AI Solution

Objective: detect and remove impersonation infrastructure across domains, social, job boards, ads and messaging, and deliver artifact-rich proof that platforms, auditors and customers accept.

Always-on brand monitoring

  • Look-alike domain hunting using fuzzy and homograph checks with passive DNS and page-similarity scoring to flag suspicious registrations early.
  • Social and store sweeps to find imposter support pages, fake recruiters and clone apps misusing brand marks or claiming affiliation.
  • Search and ads watchlists to alert on malicious paid placements and SEO traps that intercept branded queries during onboarding peaks and feature announcements.
  • Messaging and link-hub tracking to surface amplification networks that keep scam infrastructure alive.
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Agentic takedown execution with evidence

  • Auto-assembled case files for each finding contained screenshots, WHOIS and ASN, hosting metadata, time-stamped crawls, link graphs and the policy citations that the target platform requires.
  • Platform-native notices to registrars and hosts, social networks, app stores and ad networks raised first-notice acceptance rates.
  • Post-removal re-scans mapped mirrors and connected infrastructure so clusters were removed, not only single URLs.
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Customer safety and CX enablement

  • A paste-ready Official Channels microsnippet listed verified URLs, app IDs and handles and provided “how to report” steps for users and partners.
  • Short support scripts standardized verification and escalation for CX and channel teams, lowering handle time and repeat investigations.
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Reporting and governance

  • An executive dashboard showed detections, median Time to Takedown, first-notice acceptance, scam survival time and directional trust or revenue protection proxies tied to onboarding and portal analytics.
  • A monthly evidence archive packaged all case files for internal audit and partner questionnaires, with labels for vendor-managed public assets to support third-party oversight.
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Impact

“We moved from ad-hoc removals to a measurable program. Fraud pages come down faster, users get clear guidance and our audit responses are faster with standardized evidence.”
– Head of Risk and Compliance, LivQuik

Measured outcomes in the first 120 days

Scale handled

  • More than 160 abusive assets detected across domains, social, app stores and ads
  • About 78 percent removed on first notice, with most of the remainder cleared after one follow-up

Velocity achieved

  • Median Time to Takedown under 24 hours for registrar and hosting cases
  • Median Time to Takedown under 12 hours for social and app-store listings after evidence submission
  • Malicious search ads reported within 2 to 6 hours of first appearance during campaign peaks

User protection

  • Noticeable drop in scam-related tickets once Official Channels guidance and scripts went live
  • Fewer repeat investigations due to standardized evidence packs and closure templates

Assurance enablement

  • Faster responses to partner and customer security questionnaires and internal audits via month-end exports

How Hunto AI maps to mandatory Indian cyber expectations

RBI Master Direction on Cyber Resilience and Digital Payment Security Controls for non-bank PSOs (2024)

  • Requires continuous monitoring, incident response, cyber threat readiness and customer awareness proportionate to payment system risk, with phased compliance timelines by PSO size. Hunto AI delivers 24×7 external surveillance, evidence-backed takedowns and reusable awareness content, supporting practical compliance for authorised PSOs. — KPMG Assets

  • Emphasise that outsourcing must not dilute obligations to customers or impede supervision and require governance, audit rights and risk controls for third parties. Hunto AI’s vendor and partner labeling, takedown performance metrics and evidence archives support oversight and periodic reviews with service providers hosting public assets.

  • Mandate reporting specified cyber incidents within six hours, prescribe 180-day log retention in India and require time synchronisation. Brand abuse involving phishing, identity theft or fake apps falls within reportable classes. Hunto AI’s case files and time-stamped artifacts align with these reporting and logging needs.

  • Requires reasonable security safeguards and breach notification to the Data Protection Board of India and affected individuals as prescribed. By suppressing impersonation infrastructure early and documenting actions, Hunto AI strengthens due diligence and breach-prevention posture for data fiduciaries.

Why this worked for a manufacturing brand

  • Breadth with proof
    One console covered domains, social, app stores and ads. Each takedown shipped with the exact artifacts platforms expect, lifting acceptance and shrinking cycle time.

    Lean-team friendly
    Automation handled discovery, evidence assembly, submissions and mirror hunts. Business teams reused consistent scripts and Official Channels content across web and app surfaces.

    Compliance and security together
    Evidence archives, trendlines and third-party labeling map cleanly to RBI PSO Master Directions, the Outsourcing Directions, CERT-In and the DPDP Act while tangibly reducing fraud in the wild.

About Hunto

Hunto AI quantifies external cyber and brand risk and resolves it automatically. Brand Monitoring and Takedown detects impersonation across domains, social, app stores, ads and messaging, then executes removals with evidence that stands up to scrutiny. Organisations can add Attack Surface Monitoring later to consolidate external hygiene in one platform.

Protect customers and brand trust while staying audit ready.

Request a no integration Brand Abuse Snapshot and receive an evidence ready takedown pack plus a 30 day suppression plan aligned to RBI expectations.