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w3sa-bm-solidity

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W3SA - Solidity Repo Benchmark

This benchmark evaluates audited EVM projects containing smart contracts written in Solidity. It’s designed to assess the vulnerability detection capabilities of AI models and static analysis tools. The benchmark tests the ability of different models to detect high and medium severity vulnerabilities. Our model ALMX 1.5 demonstrates a significant advantage by catching up to 5x more high-severity vulnerabilities than traditional static analysis tools like Slither, with a slight improvement in performance on Medium Severity bugs and while outputting one fourth of the findings, reducing overall noise.

The benchmark covers 8 audited Solidity projects sourced from diverse origins such as Code4rena competitions, open datasets, and audit reports from various Web3 security firms.

Project Statistics

Project Platform Scanned Files Total files Cri-sev High-sev Med-sev Low/Info-Sev
Connext Eth, Optimism, Polygon 1 6 0 5 2 5
Sandclock Eth 11 25 0 5 15 5
InsureDAO Eth, Arbitrum, Optimism 10 30 0 13 9 0
algebra Base 5 175 0 5 4 16
arcadia_finance Base 21 409 0 1 7 4
seamlessfi Base 8 57 2 0 5 19
gamma Eth 5 19 0 8 2 0
Beebots Eth 1 1 0 6 3 7
Total ground truth bugs 62 722 2 43 47 56
Solidity Codebase Benchmark

ALMX-1.5 was able to capture 21.42% of High Severity bugs, against 14.28% captured by o1 and 4.76% captured by Slither.

Repo Structure 

.
├── README.md
├── benchmark
│   ├── config
│   ├── ground_truth
│   └── repositories
├── bm_src
└── resources
..

Set up

  • Install uv package manager if not yet available
  • Run uv sync

Run an experiment

  • Set your OPENAI_API_KEY or ANTHROPIC_API_KEY as environmental variable
  • Launch your experiment by running:
uv run experiment.py --model o3-mini

A tqdm progress bar will pop up and, at the end of the experiment, the results metrics will be printed out.

Contact Us

For or questions, suggestions, or to learn more about Almanax.ai, reach out to us at https://www.almanax.ai/contact

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