Race Condition - Double Spend Scanner
Tests for double-spend vulnerabilities in financial operations.
What is Race Condition - Double Spend?
Double-spend race conditions occur when financial operations (withdrawals, purchases, transfers) can be executed multiple times for a single balance or credit. Attackers send parallel requests that all read the same balance, each deducting from it, resulting in spending more than available funds.
Why is This Important?
Double-spend vulnerabilities cause direct financial loss. A user with $100 can potentially withdraw $200 or more. These affect banking applications, cryptocurrency exchanges, gift card systems, loyalty points, in-app purchases, and any system involving balance deduction. Financial losses can be significant and immediate.
How It Works
1. Attack Surface Mapping
Identifies complex attack vectors including race conditions, desync points, and logic flaws in your application.
2. Advanced Exploitation
Executes sophisticated attack techniques that bypass traditional security controls and detection mechanisms.
3. Impact Assessment
Demonstrates real-world impact with detailed exploitation chains and business risk analysis.
Key Capabilities
Expert-level security testing for sophisticated vulnerabilities that evade traditional scanning tools.
- Race condition and timing attack detection
- Request smuggling and desync analysis
- Business logic flaw identification
- Chained exploit development
- Protocol-level vulnerability testing
Frequently Asked Questions
How does a double-spend attack work?
A user has $100 balance. They send 10 parallel $100 withdrawal requests. Each request reads balance=$100, validates sufficient funds, processes withdrawal. Due to race condition, multiple withdrawals succeed before any updates the balance, resulting in $500+ withdrawn from $100.
What makes systems vulnerable to double-spend?
Vulnerabilities arise from: checking balance in one query and updating in another, using optimistic locking without retry, caching balance values, database read replicas with lag, microservices with eventual consistency, and lack of transaction isolation.
Which applications are most at risk?
High-risk applications: payment processors, cryptocurrency exchanges, e-commerce platforms, gift card systems, loyalty programs, in-game currency, prepaid systems, and any multi-step financial transaction without proper atomicity.
How do I prevent double-spend vulnerabilities?
Prevention: use database transactions with proper isolation levels (SERIALIZABLE for critical operations), implement pessimistic locking (SELECT FOR UPDATE), use atomic compare-and-swap operations, implement idempotency keys, queue financial operations, and add post-transaction validation.
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