PLATE 01 · RESELLER ECOSYSTEM DISRUPTION

Reseller Ecosystem Disruption

CASE STUDY

Disruption of third-party automation and reseller ecosystems behind hundreds of thousands of abusive accounts: behavioral fingerprinting, payment-signal analysis, and graph-based account clustering across fragmented identity systems, carried through to legal enforcement.

100,000sABUSIVE ACCOUNTS IN SCOPE
<2 HRSCOORDINATED-NETWORK DETECTION
ATTRIBUTEDINFRASTRUCTURE TO REAL-WORLD OPERATORS

Problem

Third-party automation and reseller operations industrialized platform abuse: coordinated account farms created and resold access at scale, hiding behind fragmented identity signals spread across billing, usage, and authentication systems. No detection capability existed. Coordinated abuse surfaced only when damage was already visible.

Approach

Built behavioral detection in a data-constrained environment: payment signals, usage patterns, timing correlations, and prompt behavior combined into behavioral fingerprints that survive surface-level evasion.

Performed graph-based account clustering and entity resolution across fragmented systems, without dedicated graph infrastructure, to resolve farms, resellers, and their customers into navigable networks. Adversarial investigation, including OSINT and proactive threat-actor research, attributed infrastructure to real operators and informed enforcement strategy.

Outcome

Average detection time for coordinated abuse fell from none, to roughly 30 days of manual work, to under two hours through custom investigative tooling. Sustained enforcement disrupted ecosystems responsible for hundreds of thousands of abusive accounts, adversarial investigation attributed operating infrastructure to real-world entities, and evidence packets built from those investigations supported outside counsel on enforcement matters.

RESELLER A BROKER RESELLER B
FIG. 01 · ACCOUNT CLUSTER TOPOLOGY · SYNTHETIC RENDERING