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Case Study

Fintech Security Audit

Security audit and forensic incident response for a payments platform under active attack.

Industry: Fintech, Payments & Wallet Services

Results at a Glance

24
Vulnerabilities Found
$7.1k
Fraud Quantified
$5.1k
Recoverable
24h
Attack Stopped

The Challenge

A fintech platform processing payments was experiencing an active security breach. Attackers were exploiting payment webhook handling to create fraudulent credits.

The scope of the damage was unknown, and the attack was ongoing. The platform needed immediate containment while maintaining zero downtime for legitimate users.

Beyond stopping the attack, the client needed to understand exactly what happened, how much was lost, and whether recovery was possible.

My Approach

Phase 1: Vulnerability Assessment

Systematic Code Review

AI-augmented line-by-line code audit with manual expert analysis. Covered payment webhooks (3 providers), wallet operations, order processing, and admin functions.

Business Logic Analysis

Deep dive into financial operations looking for race conditions, double-spend vectors, and authentication bypasses in state-changing operations.

Attack Vector Mapping

Identified the exact vulnerability being exploited — a webhook fallback path that created payment records without proper validation.

Phase 2: Forensic Database Analysis

Transaction Timeline Reconstruction

With production database read access, reconstructed the complete attack timeline spanning 42 days.

Attack Quantification

Identified 1,058 duplicate payments affecting 720 accounts. Calculated exact fraudulent amount: $7,149.24.

Attacker Identification

Traced attack patterns to specific accounts. Top offender: 40 duplicate payments, $1,028 in fraudulent credits, $619 still in wallet.

Key Findings

5
Critical
7
High
5
Medium
7
Low

Arbitrary Payment Creation via Webhook

Fallback code path created payment records and credited wallets when no pre-existing payment was found. Attackers crafted webhooks with arbitrary amounts.

Race Condition in Payment Verification

Missing pessimistic locking allowed concurrent webhook calls to double-credit wallets. Impact: 2x-6x deposit multiplication.

Silent Signature Validation Failure

Invalid webhook signatures returned silently instead of throwing exceptions, allowing unsigned requests through under certain conditions.

Attack Pattern Analysis

Attack Window

42 days

Affected Accounts

720 (0.86% of users)

Duplicate Payments

1,058

Peak Day

46 duplicates

Attack escalated gradually from ~6/day to ~32/day, suggesting automated exploitation once the vulnerability was discovered.

Deliverables

Security Audit Report

40+ pages covering all 24 findings with severity ratings, code-level fix recommendations, and prioritized remediation roadmap.

Forensic Analysis Report

Complete attack timeline, affected account listing, top offender identification, and recovery recommendations.

SQL Query Library

Reusable queries for duplicate detection, balance discrepancy analysis, and ongoing attack monitoring.

Evidence Package

Documentation prepared for potential legal action against identified attackers.

Outcome

Attack vector closed within 24 hours of identification. All 5 critical vulnerabilities remediated within the first week.

Database constraints added preventing negative balances. Pessimistic locking implemented across all financial operations. Webhook security hardened across all providers.

$5,110 recovery path identified with evidence package prepared. The client now has ongoing monitoring capabilities to detect similar attacks early.

Key Lessons

Race conditions are the primary vulnerability class in fintech. Every state-changing operation needs proper locking.

Defense in depth requires each layer to actively block, not just log. Silent failures create attack vectors.

Forensic capability is valuable for quantifying and recovering from attacks. Knowing the damage enables informed decisions.

Need a Security Audit?

Whether you're dealing with an active incident or want to proactively secure your platform, I can help identify vulnerabilities before attackers do.

Client details anonymized. Engagement conducted under NDA. Case study shared with client approval.

Emmanuel Joseph © 2025