evm contract bytecode audit

    by Elyas Shukri Elmi

    1

    Audits EVM contract bytecode for honeypots, drainers, and malicious owner patterns before you interact.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurf+15 more

    See it in action

    You say

    Audit this unverified contract on Ethereum at 0x123... to see if it is a honeypot before I buy the token.

    Your agent does

    VERDICT: DANGER. Access: Decompiled bytecode (best-effort). Findings:

    • Malicious logic: Internal _transfer function contains a hardcoded blacklist gate.
    • Fake Renouncement: renounceOwnership() emits an event but does not zero the owner storage slot.
    • EIP-1967: Not detected.

    What you get

    Detect sell-blocking logic in new ERC-20 tokens before swapping.Identify hidden backdoors in contracts with "renounced" ownership.Audit unverified bytecode using decompilation for pre-flight safety checks.Check for malicious owner-only minting or fee-on-transfer manipulation.

    About this skill

    The problem

    Interacting with unverified or unfamiliar smart contracts is a primary cause of lost funds through honeypots, drainers, and malicious ownership rugs. Standard security scanners often miss these adversarial patterns because they focus on general vulnerabilities rather than intentional fraud.

    What it does

    • Performs dual-pass analysis using Slither for general vulnerabilities and a custom heuristic suite for honeypot-specific patterns.
    • Decompiles unverified bytecode using Heimdall-rs or Dedaub to audit logic even when source code is hidden.
    • Detects EIP-1967 proxy patterns, identify upgrade admins, and flag hidden centralization risks.
    • Exposes "fake renouncement" scams by auditing the internal logic of ownership transfer functions.
    • Categorizes risks into DANGER, SUSPECT, or NO-FINDING verdicts based on exploitability and blast radius.

    Frameworks & tools

    Slither, Heimdall-rs, Dedaub, EVM, EIP-1967.

    Why this beats prompting it yourself

    Most LLMs rely on general knowledge that overlooks specific honeypot techniques like fee-on-transfer gates or non-standard proxy implementations. This skill enforces a strict multi-tool workflow that prevents "clean" reports from general scanners being mistaken for a lack of fraud risk.

    Use cases

    • Audit a new ERC-20 token contract before approving a spend limit or swapping.
    • Identify if a minting contract is a drainer before connecting a wallet.
    • Verify if a "renounced" contract has hidden backdoors or hardcoded admin overrides.
    • Analyze unverified bytecode for malicious logic before an agent interacts with it.

    Known limitations

    Cannot simulate specific transaction effects like slippage or sandwiching. Does not detect non-standard proxy patterns like Beacon or Diamond proxies. Best-effort reconstruction for unverified code.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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