signature-replay-analysis

signature-replay-analysis is a skill for Claude Code from quillai-network/quillshield_skills. It costs 132 tokens per session (3,154 once invoked), scanned A, original, MIT.

A smart-contract security skill that checks whether cryptographic signatures can be reused, across transactions, blockchains, or contracts.

In plain words
What is it for?
Use it to audit contracts using ecrecover, ECDSA, or EIP-712, including permit approvals, gasless transactions, multi-signature systems, and signed orders.
Why use it?
It helps uncover missing protections such as chain and contract binding, one-time-use counters, expiry checks, or safe signature recovery.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the signature-replay-analysis plugin — 1 skill shipped together

Good fit Use it to audit contracts using ecrecover, ECDSA, or EIP-712, including permit approvals, gasless transactions, multi-signature systems, and signed orders.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/quillai-network/quillshield_skills/signature-replay-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add quillai-network/quillshield_skills --skill signature-replay-analysis
Clone the repo
git clone --depth 1 https://github.com/quillai-network/quillshield_skills

Made for: Claude Code.

Or install signature-replay-analysis, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for signature-replay-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/quillai-network/quillshield_skills/signature-replay-analysis/github.svg)](https://agentmods.dev/skills/quillai-network/quillshield_skills/signature-replay-analysis)
Your own site
<a href="https://agentmods.dev/skills/quillai-network/quillshield_skills/signature-replay-analysis"><img src="https://agentmods.dev/badge/skills/quillai-network/quillshield_skills/signature-replay-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for signature-replay-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/quillai-network/quillshield_skills/signature-replay-analysis"><img src="https://agentmods.dev/badge/skills/quillai-network/quillshield_skills/signature-replay-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,154 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00132 $0.03154
Opus 5 $0.00066 $0.01577
Sonnet 5 $0.00026 $0.00631
Haiku 4.5 $0.00013 $0.00315

Measured 13d ago against content hash a1b10db075d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

signature-replay-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/signature-replay-analysis/skills/signature-replay-analysis/SKILL.md · 332 lines

How it starts

The opening of the file, as written. The whole thing — 332 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Signature & Replay Analysis

Detect vulnerabilities where cryptographic signatures can be reused, replayed across chains/contracts, or exploited through implementation flaws. Research shows 19.63% of Ethereum contracts using signatures contain replay vulnerabilities.

When to Use

  • Auditing contracts that verify signatures (ecrecover, ECDSA, EIP-712)
  • Reviewing ERC-20 permit() / Uniswap Permit2 implementations
  • Analyzing meta-transaction / gasless relay systems
  • Verifying multi-sig signature aggregation
  • Checking off-chain order books or signed message execution

When NOT to Use

  • Contracts without any signature verification
  • Pure on-chain access control (use semantic-guard-analysis)
  • Token standard compliance (use external-call-safety)

Core Concept: The Signature Trust Model

A signature proves that a specific private key holder authorized a specific action. For this to be secure, the signature must be:

  1. Bound to context — specific chain, contract, and version (domain separation)
  2. Used exactly once — nonce prevents replay
  3. Time-limited — deadline/expiry prevents late execution
  4. Correctly verified — ecrecover edge cases handled

Any gap in this model creates a replay vulnerability.

The Five Replay Types

Type 1: Same-Chain Replay

The exact same signature is submitted multiple times to the same contract on the same chain.

// VULNERABLE: No nonce — same signature works forever
function executeWithSig(address to, uint256 amount, bytes memory signature) external {
    bytes32 hash = keccak256(abi.encodePacked(to, amount));
    address signer = ECDSA.recover(hash, signature);
    require(signer == admin, "Invalid signer");
    token.transfer(to, amount);
    // Attacker can submit this same signature again and again!
}

// SAFE: Use nonce
mapping(address => uint256) public nonces;

function executeWithSig(address to, uint256 amount, uint256 nonce, bytes memory signature) external {
    require(nonce == nonces[admin], "Invalid nonce");
    bytes32 hash = keccak256(abi.encodePacked(to, amount, nonce));
    address signer = ECDSA.recover(hash, signature);
    require(signer == admin, "Invalid signer");
    nonces[admin]++;
    token.transfer(to, amount);
}

Read the full file on GitHub · 332 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 332 lines · 132 tokens per session scan A a1b10db075d6

Subscribe to this mod's changes

signature-replay-analysis is a skill published in the GitHub repository quillai-network/quillshield_skills (121 stars, last pushed 5mo ago), licensed MIT. It adds 132 tokens to every session and 3,154 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

ansem-crypto

Use when evaluating crypto narratives, attention rotation, memecoin cycles, Solana-style ecosystem momentum, social distribution, and reflexive retail flows in an Ansem-style crypto market framework.

questflowai/investorskills · 41 tokens

arthur-hayes-liquidity

Use when evaluating crypto markets through an Arthur Hayes-style liquidity lens: dollar liquidity, funding, risk appetite, cycle psychology, and macro-driven crypto positioning.

questflowai/investorskills · 38 tokens

cobie-cycle-filter

Use when evaluating crypto decisions through a Cobie-style cycle filter: common-sense risk, narrative traps, leverage humility, and avoiding obvious stupid trades.

questflowai/investorskills · 35 tokens

cryptocred-structure

Use when evaluating crypto charts through a CryptoCred-style structure lens: levels, confluence, market structure, risk definition, and educational technical process.

questflowai/investorskills · 35 tokens

willy-woo-onchain

Use when evaluating Bitcoin and crypto cycles through a Willy Woo-style on-chain lens: holder behavior, realized value, supply dynamics, and on-chain demand.

questflowai/investorskills · 37 tokens

prompt-proximity-architecture

Turn an approved measurement charter, ICPs, and buyer jobs into a budget-aware prompt coverage blueprint across proximity bands, aided status, information acts, journey states, roles, locales, evidence grades, partitions, and measurement lanes. Use before prompt wording to define required, optional, and prohibited…

elvisun/newsjack · 67 tokens