Protocol Fee Manipulation Vulnerability Due to Unbounded Input Data in request Function

Summary

The request function within the Swan protocol's LLMOracleCoordinator contract accepts unbounded input and models parameters without enforcing size limitations. This lack of validation exposes the contract to potential Denial of Service (DoS) attacks through storage bloat and excessive gas consumption. Attackers can exploit this vulnerability by submitting excessively large inputs, leading to exorbitant gas costs and potential disruption of protocol operations. Consequently, legitimate users may experience failed transactions, increased operational costs, and overall degradation of the protocol's reliability and performance.

Vulnerability Details

Function Under Scrutiny:

Issue Description:

• Unbounded Input Parameters:

  • The input and models parameters are declared as bytes memory, allowing them to accept data of any size.

  • Without enforcing size restrictions, these parameters can be exploited to submit excessively large data payloads.

• Storage Bloat:

  • Storing large amounts of data increases the contract's storage requirements.

  • EVM storage costs are significant, with:

    • 20,000 gas per 32 bytes for new storage.

    • 5,000 gas per 32 bytes for storage modifications.

• Gas Consumption:

  • Large inputs result in high gas costs for transactions.

  • Example Calculations:

    • Normal Usage:

      • Input: ~200 bytes

      • Models: ~50 bytes

      • Total: 250 bytes → 8 storage slots → 160,000 gas (~$0.16 at 50 gwei, assuming 1 ETH = $40,000)

    • Attack Scenario:

      • Input: 500 KB (500,000 bytes)

      • Models: 100 KB (100,000 bytes)

      • Total: 600 KB → 19,200 storage slots → 384,000,000 gas (~$384 at 50 gwei)

• Oracle Node Impact:

  • Memory Exhaustion: Oracle nodes with limited memory may struggle to process large data payloads.

  • Increased Processing Time: Handling large inputs increases the time required for data processing.

  • Network Congestion: Large data submissions can lead to network congestion, affecting overall protocol performance.

• Cross-Request DoS:

  • Attack Method:

    • Submit multiple large requests in quick succession to inflate the contract's storage and gas consumption.

    • Example:

      // Attack Contract

      contract OracleAttack {

      LLMOracleCoordinator public coordinator;

      constructor(address _coordinator) {

      coordinator = LLMOracleCoordinator(_coordinator);

      }

      function attack() external {

      // Create large data

      bytes memory largeInput = new bytes(500_000); // 500KB

      bytes memory largeModels = new bytes(100_000); // 100KB

      // Basic task parameters

      LLMOracleTaskParameters memory params = LLMOracleTaskParameters({

      difficulty: 1,

      numGenerations: 1,

      numValidations: 0

      });

      // Submit multiple requests

      for(uint i = 0; i < 10; i++) {

      coordinator.request(

      bytes32("ATTACK"),

      largeInput,

      largeModels,

      params

      );

      }

      }

      }

      ​

    • Impact:

      • Oracle Nodes Overload: Forced to process large amounts of data, leading to potential crashes or slowdowns.

      • Legitimate Requests Blocked: Genuine users may find their requests failing due to gas limits or storage constraints.

      • Economic Costs: Attackers incur high gas fees, but the protocol suffers from disrupted services and increased operational costs.

Real-World Examples:

1. Ethereum State Bloat Attacks (2016):

   • Overview: Attackers sent transactions with large data payloads to increase the Ethereum state size.

   • Impact: Caused network congestion, increased node synchronization times, and raised gas costs across the network.

2. IPFS Node DoS Through Large Files:

   • Overview: Attackers uploaded excessively large files to IPFS, overwhelming node storage and bandwidth.

   • Impact: Led to node performance degradation and potential unavailability for legitimate users.

3. API Service DoS Through Payload Size:

   • Overview: Attackers sent requests with extremely large payloads to overwhelm API servers.

   • Impact: Resulted in server crashes, service unavailability, and increased operational costs for mitigation.

Impact

Severity: High

Potential Consequences:

1. Service Disruption:

   • Function Unavailability: The request function may become uncallable when gas costs exceed block limits due to large input sizes.

   • Operational Halts: Critical protocol operations dependent on successful task submissions are blocked.

2. Economic Loss:

   • Increased Gas Costs: Legitimate users incur higher transaction fees due to inflated gas consumption.

   • Protocol Operational Costs: The protocol may need to allocate additional resources to handle inflated storage and processing demands.

3. User Experience Degradation:

   • Failed Transactions: Users attempting to submit legitimate tasks may experience failed transactions, leading to frustration and loss of trust.

   • Delayed Processing: Even if transactions succeed, the processing time for large inputs can delay protocol operations.

4. Protocol Reliability:

   • Inconsistent Performance: Repeated DoS attacks can lead to unstable protocol performance, affecting overall reliability.

   • Trust Erosion: Persistent vulnerabilities and service disruptions can erode user and stakeholder trust in the protocol.

Recommendation

Implement Size Validation for Input Parameters

To mitigate the risk of DoS attacks through unbounded input data, enforce strict size limits on the input and models parameters within the request function. This ensures that only reasonably sized data can be submitted, preventing storage bloat and excessive gas consumption.

Implementation Example:

Benefits:

• Prevents Storage Bloat: Limits the amount of data stored per task, ensuring efficient use of contract storage.

• Controls Gas Consumption: Restricts gas costs by capping the size of data that can be processed in a single transaction.