Setting Up a Bug Bounty Program Focused on Gas Optimization

Gas optimization bug bounties incentivize security researchers to find and report inefficient code that leads to excessive transaction costs. Unlike traditional security bounties focused on critical vulnerabilities, these programs target gas-guzzling patterns, redundant operations, and sub-optimal storage in your smart contracts. For protocols with high transaction volume, even minor optimizations can save users millions in fees annually. Setting up a dedicated program signals a commitment to user experience and economic efficiency on-chain.

To launch your program, first define a clear scope and rules. Specify which contracts are in-scope (e.g., core vaults, AMM pools, governance) and list the types of gas inefficiencies you're seeking: expensive operations in loops, unnecessary SLOAD/SSTORE opcodes, or missed opportunities for using immutable/constant variables. Establish a severity and reward matrix. A common model ties rewards to estimated gas saved per transaction, multiplied by projected transaction volume. Publish these rules on a platform like Immunefi or HackerOne.

You must provide researchers with the tools for effective analysis. This includes deployment addresses on testnets and mainnet, verified source code on Etherscan, and a comprehensive test suite. Encourage the use of specialized tools like Hardhat Gas Reporter, EthGasReporter, or Ganache for profiling. Consider funding a dedicated testnet with ETH for researchers to simulate transactions. Clear documentation on the expected function of each contract is crucial, as researchers need to understand the intended behavior to identify unnecessary overhead.

Managing submissions requires a triage process. Valid reports should include a Proof of Concept (PoC) demonstrating the gas inefficiency, a comparison of gas usage before and after the suggested optimization (using tools like forge snapshot), and a suggested code fix. Your internal team must verify the findings, estimate the potential fee savings, and categorize the report's impact. Transparency in the evaluation process and timely communication with researchers are key to maintaining the program's credibility and attracting top talent.

Finally, integrate the process into your development lifecycle. Approved optimizations should be reviewed, tested, and scheduled for deployment. Publicly acknowledge the researcher's contribution (unless they opt for anonymity) and disburse the bounty payment promptly. Continuously update your scope and rules as you deploy new contracts. A successful gas optimization bounty program not only reduces costs but also fosters a collaborative relationship with the security community, leading to more robust and economical smart contracts.

Before launching a gas-focused bug bounty, ensure your core infrastructure is in place. Your smart contracts should be deployed on a testnet (like Sepolia or Goerli) with a complete suite of unit and integration tests. Provide auditors with a detailed technical specification, including the contract addresses, ABI, and a clear scope document. Essential tools include a local development environment (Foundry or Hardhat), access to a block explorer, and a gas profiling tool like Hardhat Gas Reporter or Foundry's gas snapshots. This setup allows researchers to replicate, test, and measure their findings accurately.

Define the primary goal of your program: to identify and remediate gas inefficiencies that lead to excessive transaction costs for users. This differs from traditional security bounties by focusing on economic vulnerabilities rather than exploits. Key objectives include finding suboptimal storage patterns, expensive loops, redundant computations, and missed opportunities for opcode optimization (e.g., using unchecked blocks for safe arithmetic). Establish clear success metrics, such as a target percentage reduction in average function gas cost or identifying the top 5 most expensive operations in your core workflow.

Structure your reward tiers to incentivize meaningful, actionable reports. Rewards should be scaled based on the potential gas savings and the complexity of the finding. For example, a high-severity report that demonstrates a 30% gas reduction in a frequently called function would warrant a maximum bounty. Provide a detailed submission template requiring a proof-of-concept, the exact gas measurements before and after the optimization (using standard conditions), and a clear explanation of the root cause. This ensures submissions are reproducible and valuable.

Effective scoping is critical. Explicitly list the in-scope contracts and functions. More importantly, define what is out of scope: theoretical gas savings without a working implementation, optimizations that compromise security or readability, and findings related to compiler settings that you already control. Specify the blockchain networks (e.g., Ethereum Mainnet, Arbitrum, Optimism) and the exact compiler version used, as gas costs can vary significantly across EVM implementations and compiler optimizations.

Finally, establish a transparent process for triage and remediation. Designate a technical lead to evaluate submissions against the program goals. Validated reports should trigger a clear workflow: acknowledgment, internal review, implementation of the fix, verification of the new gas metrics, and finally, bounty payment. Publicly acknowledging contributors (with permission) and publishing a retrospective on the gas savings achieved builds trust with the security community and demonstrates your project's commitment to efficiency.

The scope explicitly states which parts of your protocol are eligible for gas-related rewards. A broad scope like "all smart contracts" is unmanageable. Instead, specify the exact contract addresses, functions, and deployment networks (e.g., Ethereum Mainnet, Arbitrum). For gas optimization, you might focus on high-frequency functions like swap(), addLiquidity(), or claimRewards(). Exclude contracts that are deprecated, in testnets, or part of peripheral, non-critical systems. This precision directs researcher attention to the code that matters most for user experience and cost reduction.

Severity levels translate a gas saving into a tangible reward. Unlike security bugs, severity is based on impact and likelihood. A common framework uses four tiers: Critical, High, Medium, and Low. Define each tier with clear, quantitative thresholds. For example: a Critical finding saves >30% gas on a core, frequently called function; a High finding saves 15-30%; a Medium finding saves 5-15% with a clear execution path; a Low finding saves <5% or optimizes a rarely used function. Publish these criteria publicly to set expectations.

To operationalize this, create a structured document. Start with a list of in-scope contract addresses and their purposes. Follow with the severity matrix, using real function names from your code as examples. For instance: "Optimizing the _updatePool function in MasterChef.sol saving 20,000 gas per call would be classified as High." Reference industry standards like the Immunefi Vulnerability Severity Classification System for guidance, but adapt it specifically for gas efficiency metrics. This clarity is essential for fair and efficient triage.

The core of a gas-focused bounty program is a transparent reward formula. Unlike traditional security bounties that pay a fixed amount per vulnerability class, gas optimization rewards should be directly proportional to the savings achieved. A common and effective model is a percentage-of-savings approach. For example, your program might offer a reward equal to 10% of the total gas saved over a one-year period, based on a reasonable estimate of contract usage. This aligns the researcher's incentive with the protocol's long-term value.

To calculate the reward, you need three key inputs: the gas saved per transaction (in gas units), the estimated number of transactions over a period (e.g., 1 year), and the average gas price (in Gwei). The formula is: Reward = (Gas_Saved * Num_Transactions * Avg_Gas_Price * ETH_Price * Reward_Percentage). Use a tool like eth-gas-reporter for Hardhat or Foundry's gas snapshots to measure the before-and-after gas cost of the optimized function. Estimating transaction volume requires analyzing historical on-chain data or project projections.

For a concrete example, imagine a swap() function that uses 100,000 gas. A researcher optimizes it to 90,000 gas, saving 10,000 gas per swap. If your DEX is projected to process 1 million swaps in a year at an average gas price of 30 Gwei, and ETH is $3,000, the annual savings is: 10,000 * 1,000,000 * 30 Gwei * $3,000 / 1e9 = $900. A 10% reward on this saving would be $90. Publish this calculation methodology in your bounty brief so researchers can estimate their potential payout.

It's crucial to define the scope and baseline for measurements. Specify the exact Solidity compiler version and optimization settings (e.g., via-ir enabled, runs set to 999999) used for gas benchmarking. All submissions must be verified against this baseline. Also, decide how to handle one-time savings (e.g., in constructors or state-initializing functions) versus recurring savings in frequently called functions; the latter typically commands a higher reward multiplier due to its cumulative impact.

Implement a tiered reward cap to manage budget and risk. For instance, you might cap any single bounty at 50 ETH or $100,000, regardless of the formula's output. This protects the program from extreme scenarios while still offering significant rewards. Clearly state that final reward amounts are at the protocol's discretion, based on the verified calculations and the significance of the optimization. Transparency in the adjudication process builds trust with the researcher community.

Finally, document and share successful bounty cases. A public report showing the optimization, the gas savings calculation, and the awarded bounty serves as powerful social proof. It attracts more researchers and demonstrates your commitment to efficiency. Platforms like Immunefi and Hats Finance support custom reward models and can help administer these calculations.

The submission portal is your program's front door. Use a platform like Immunefi, HackerOne, or a custom form integrated with your GitHub repository. The submission form must require specific, structured data to prevent low-quality reports. Mandatory fields should include: the affected contract address and function name, a link to the exact code on a block explorer like Etherscan, a detailed description of the gas inefficiency, a proof-of-concept (PoC) test demonstrating the issue, and a quantified gas savings estimate using a tool like Hardhat Gas Reporter or foundry's --gas-report. Clear instructions prevent wasted time for both researchers and your team.

Upon receiving a report, the triage phase begins. A dedicated triager (often a senior developer or security engineer) performs initial validation. This involves: verifying the PoC compiles and runs against the correct network (e.g., a forked mainnet), confirming the gas measurement methodology is sound, and checking that the finding is within the program's scope (e.g., not a known issue or a stylistic preference). For a finding like an unnecessary storage read in a loop, the triager would run the provided test to confirm the baseline gas cost, then verify the suggested fix reduces it. Speed here is critical to maintain researcher engagement.

Effective triage requires standardized tooling and environments. Use a reproducible setup, such as a Foundry or Hardhat project pre-configured with mainnet forking and gas tracking. The triager should have a checklist for common gas optimization categories: - Storage Operations: Expensive SSTORE and SLOAD - Loop Optimizations: Bounds checking and memory variables - Math & Logic: Using unchecked blocks safely - External Calls: Minimizing cross-contract overhead. This ensures consistent evaluation. Validated reports are then assigned a severity level (e.g., Low, Medium, High) based on potential gas savings and frequency of function calls.

After triage, the report moves to the developer team for implementation review. The developer assesses the technical feasibility of the fix, its impact on code readability, and ensures it doesn't introduce new vulnerabilities. For example, a suggestion to use a uint8 for a loop counter to save gas might be rejected if the loop could ever exceed 255 iterations, causing an overflow. Communication is key; developers should comment directly on the report in the portal. Once a fix is agreed upon and merged into the codebase, the triager verifies the deployment and the gas savings on a testnet before marking the report as Resolved and initiating the bounty payout process.

A gas optimization bug bounty program is distinct from a general security audit. While both aim to improve code quality, the primary objective here is to identify and reward findings that reduce transaction costs for users. This includes inefficient storage patterns, redundant computations, expensive opcodes in loops, and missed opportunities for using assembly or newer EVM features. Structuring your program around these specific criteria attracts researchers with deep expertise in EVM mechanics and gas golfing.

To launch an effective program, you must define a clear scope and reward structure. The scope should include all production smart contracts, with special emphasis on high-frequency functions like swaps, staking, or voting. Rewards should be tiered based on impact, measured in average gas saved per transaction. For example, a finding that saves 5,000 gas on a core function used daily by 10,000 users has massive cumulative value. Platforms like Immunefi or HackerOne provide templates for structuring such programs.

When a valid report is submitted, integrate it into your development lifecycle using a structured triage process. First, verify the finding in a test environment using tools like hardhat-gas-reporter. Next, assess the gas savings and any potential trade-offs with code readability or security. Finally, create a prioritized ticket in your project management system (e.g., GitHub Issues) and implement the fix. Document each optimization in a public changelog or post-mortem to build trust with the community and demonstrate your commitment to efficiency.

Continuous integration is key. Automate gas tracking in your CI/CD pipeline with tools like eth-gas-reporter for Hardhat or solidity-coverage with gas options. Set gas budget thresholds for critical functions; if a new commit exceeds the budget, the pipeline fails. This ensures optimizations are preserved and regressions are caught immediately. Over time, this creates a culture where gas efficiency is a non-negotiable metric, alongside security and functionality.

Maximize the program's value by engaging with researchers. Share detailed technical write-ups of the most significant optimizations on your blog or developer forum. Consider offering bonus rewards for findings that introduce novel optimization techniques or that save gas across an entire category of transactions. This not only improves your codebase but also contributes to broader ecosystem knowledge, positioning your project as a leader in efficient smart contract design.

Launching your gas optimization bug bounty program requires clear communication and structured processes. Begin by publishing a detailed scope on platforms like Immunefi or HackerOne, explicitly listing the contracts in scope and excluding standard libraries or proxy implementations. Define severity tiers based on potential gas savings, such as: High for optimizations saving >20% gas in a core function, Medium for 5-20% savings, and Low for smaller, non-critical improvements. Clearly state that submissions must include a proof-of-concept, a gas benchmark comparing the original and optimized code, and a clear explanation of the vulnerability or inefficiency.

To manage submissions effectively, establish a triage workflow. Use a dedicated email or platform dashboard to receive reports. Each submission should be validated by: 1) Reproducing the gas savings in a forked testnet environment (e.g., using Hardhat or Foundry), 2) Verifying the optimization does not introduce new security risks or break functionality, and 3) Assessing the impact based on the function's frequency of use. For valid reports, determine the payout based on the pre-defined severity and the significance of the affected contract. Prompt communication and fair rewards are critical for maintaining researcher trust and engagement.

Your first bounty round will provide invaluable data. Analyze the findings to identify common patterns—are issues frequently related to storage layout, loop inefficiencies, or expensive opcodes like SSTORE? Use these insights to create internal gas optimization checklists and integrate automated tools like Slither or Ethlint with custom rules into your CI/CD pipeline. Consider open-sourcing non-sensitive findings and fixes to contribute to ecosystem knowledge. Finally, treat the bounty program as an ongoing process; periodically review scope, adjust payout amounts based on treasury health and market rates, and foster a community around efficient code to build a sustainable pipeline for gas savings.