TH Dashsecurity

Manipulating price oracles—external data feeds used by smart contracts—can destabilize protocols, leading to financial losses or systemic failures. Attackers often exploit poorly designed oracle mechanisms to inflate or deflate asset prices temporarily.

Business logic vulnerabilities arise when contracts fail to execute their intended functions correctly. These errors have led to significant losses ($63M in 2024) through various attack vectors:

• Improper token minting mechanisms
• Flawed lending protocol implementations
• Incorrect reward distribution calculations
• Faulty state transition logic

These vulnerabilities often result from complex business rules being incorrectly translated into smart contract code, leading to exploitable inconsistencies in contract behavior.

Failure to validate user inputs can allow attackers to inject malicious data into smart contracts. Common validation issues include:

• Missing bounds checking on numerical inputs
• Insufficient validation of external contract addresses
• Improper handling of array lengths and indices
• Unchecked return values from external calls

Proper input validation is crucial for maintaining contract integrity and preventing manipulation of contract state.

Reentrancy attacks exploit a contract's ability to call external functions before completing its own state updates. Notable impacts include:

• The DAO hack of 2016 ($70M in losses)
• Multiple DeFi protocol exploits
• Cross-function reentrancy vulnerabilities

Prevention strategies include:

• Implementing the checks-effects-interactions pattern
• Using reentrancy guards
• Ensuring all state updates occur before external calls

When smart contracts fail to verify the success of external calls, they risk proceeding with incorrect assumptions about transaction outcomes. Critical issues include:

• Failure to check return values from low-level calls
• Improper handling of failed token transfers
• Unsafe assumptions about external contract behavior
• Callback function manipulation

Best practices include implementing proper error handling and using safe transfer patterns for all external interactions.

Flash loans are a unique DeFi feature that allows users to borrow funds without collateral, provided the loan is repaid within the same transaction block. While innovative, this mechanism can be exploited in several ways:

• Market manipulation through large-scale temporary borrowing
• Draining liquidity pools through price manipulation
• Exploiting arbitrage opportunities across multiple DeFi protocols

These attacks have become increasingly sophisticated, often combining multiple vulnerabilities for maximum impact.

Arithmetic errors occur when calculations exceed data type limits, potentially allowing attackers to manipulate balances or bypass restrictions. Common scenarios include:

• Token balance manipulation through overflow in transfer functions
• Bypassing maximum supply limits through arithmetic wraparound
• Exploiting underflow in subtraction operations to create large balances

While modern Solidity versions include SafeMath by default, many legacy contracts remain vulnerable.

Blockchain's deterministic nature makes generating secure randomness challenging. This vulnerability affects:

• Gambling and lottery smart contracts
• Random token distribution mechanisms
• NFT minting sequences

Predictable randomness can be exploited by attackers who can calculate outcomes in advance, compromising the fairness of these systems. Solutions often require external sources of entropy or verifiable random functions (VRFs).

DoS attacks in smart contracts target resource-intensive functions, making them unusable by:

• Exhausting gas limits through complex loops or calculations
• Blocking critical contract functions through state manipulation
• Creating resource bottlenecks in external calls

These attacks can render contracts temporarily or permanently unusable, potentially trapping funds or disrupting essential services. Proper gas optimization and fail-safe mechanisms are essential for prevention.