In late June 2025, Brazil’s financial sector was rocked by one of its largest systemic cyberattacks. C&M Software is a key infrastructure provider that connects banks and fintechs to Brazil’s real-time payments platform PIX. It became the entry point for an insider-led fraud attack that siphoned hundreds of millions of reais from reserve accounts at Brazil’s Central Bank (BACEN).
Driven by the collusion of a privileged IT analyst, attackers abused valid credentials to forge and digitally sign fraudulent outbound PIX transactions, enabling funds to flow swiftly out of at least six institutions. A single night’s activity saw as much as $100 million go missing from just one institution, with total damage estimates potentially reaching R$1 billion. Much of the money was laundered through crypto exchanges and payment platforms using Bitcoin and US dollars, making any recovery extremely challenging.
What Went Wrong Exactly
The incident made one point unmistakable: instant payment ecosystems can be subverted with transactions that look valid at first glance. The headline is not the lesson, however. The lesson is that insider access, thin behavioral monitoring and opaque third-party flows can overwhelm defenses before alarm bells ring.
When operating in real time, intent can hide inside of format correctness. Credentials authenticate a user but don’t explain how a transfer comes to be, whether it follows a typical sequence or if the device and network context make sense. Malicious activity can blend into routine traffic when that context is absent at the decision point.
The breach exposed a perfect storm of vulnerabilities:
- Insufficient segmentation allowed one IT insider to manipulate transaction logic and obtain multiple client certificates.
- Fraudulent orders that were cryptographically valid and compliant with PIX protocols were injected and automatically settled by the Central Bank, as no behavioral or context-based monitoring existed on the originating channel.
- Third-party flows and API integrations lacked real-time anomaly detection. Suspicious transactions blended in, as neither C&M nor affected fintech partners could distinguish malicious sessions from legitimate high-frequency API activity.
- Funds rapidly moved to mule accounts and crypto exchanges, exploiting weak onboarding controls and limited transaction monitoring at various payment institutions.
Within 48 hours, BACEN suspended six fintechs for lacking adequate fraud controls and monitoring practices.
The Third-Party Visibility Gap
This incident exposed how trust can be shattered when visibility into real-time behavior, device integrity and transactional context is missing at each hop in the payment chain. When context and origin signals stop at the first integration layer, fraud can flow unimpeded through static policy checks, even as every credential and digital signature looks valid. True resilience demands that risk data and behavioral context be preserved and analyzed across partners and platforms at every stage.
This isn’t an argument against partners. It’s a case for preserving risk context across the chain. When origin signals and counterparty risk don’t travel with the transaction, teams cannot distinguish an urgent payout from a coordinated drain.
Why SEON Could Have Made the Difference
This is precisely the scenario SEON is designed to prevent: sophisticated fraud flowing through valid credentials, API integrations and privileged sessions that look legitimate by traditional controls.
SEON draws on hundreds of data points — from device intelligence and behavioral biometrics to IP, email, digital footprint analysis and more — at every onboarding, login and transaction event. Key features highly relevant to this scenario include:
- Real-Time Data Enrichment and Risk Scoring: SEON automatically analyzes 900+ signals, including device, network, behavioral and digital context, to generate risk scores on every interaction. Transaction screening and user verification occur in under a second, making real-time fraud prevention possible at any scale.
- Behavioral Analytics and Insider Detection: SEON monitors for abnormal behavior (e.g., sudden privilege use, burst transaction volumes, API usage patterns outside normal baselines), meaning even trusted insiders triggering fraud are quickly flagged.
- API-First, Modular Integration: SEON’s solution can sit before payment and onboarding APIs, instantly scoring and contextualizing all events, including those from partner and third-party integrations, without slowing legitimate traffic.
- AML and Compliance Readiness: SEON combines fraud and AML protection, tracing funds, checking against watchlists and aiding in compliance with regulatory standards, critical as Brazilian regulators increase oversight following this incident.
- Network Intelligence: SEON links transactions, devices and user entities to reveal shared connections, spot money mules, synthetic identities and orchestrated attacks, going beyond static checks to reveal system-wide fraud chains before money leaves the financial system.
Deployed as an API-first layer in front of payment and integration endpoints, SEON preserves risk context throughout the entire user and transaction lifecycle, flagging fraud as it happens, even when it originates from within or across trusted partners. This layer of protection, missing during the C&M Software breach, is precisely what Brazil’s evolving payment ecosystem and new regulatory demands now require.
Moving From Trust to Verified Intelligence
This attack was not unprecedented; it was a textbook case of how overreliance on static credentials, perimeter authentication and surface-level monitoring can allow highly damaging fraud to move unimpeded. Banking and payment providers, especially as BACEN enacts tighter controls, must adopt dynamic, context-aware risk evaluation at every stage. With SEON’s approach, financial services can move beyond yesterday’s trust models, detecting sophisticated threats in real time and preventing the next ecosystem-wide breach.
