Behavioral State Analysis logo

Behavioral State Analysis

Organization
quillai-network
behavioral-state-analysis

Token-efficient smart contract security auditing via Behavioral State Analysis (BSA). Scopes analysis to contract type, runs only relevant threat engines, and uses tiered output depth. Use for auditing smart contracts, security reviews, or DeFi threat modeling.

Overview

Publisherquillai-network
Repositoryquillshield_skills
Skill namebehavioral-state-analysis
Stars
131
Forks
28
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by quillai-network on GitHub. Read the source before you install it.

Installation

Install the Behavioral State Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/quillai-network/quillshield_skills/tree/main/plugins/behavioral-state-analysis/skills/behavioral-state-analysis
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/quillai-network/quillshield_skills.git /tmp/quillshield_skills
mkdir -p .claude/skills
cp -r /tmp/quillshield_skills/plugins/behavioral-state-analysis/skills/behavioral-state-analysis .claude/skills/behavioral-state-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Behavioral State Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Behavioral State Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Behavioral State Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Behavioral State Analysis (BSA)

Audit smart contracts by extracting behavioral intent, then systematically breaking it across security dimensions.

When to Use

  • Smart contract security audits
  • DeFi protocol threat modeling (DEXs, lending, staking, vaults)
  • Cross-contract attack surface analysis
  • Vulnerability prioritization with confidence scoring

When NOT to Use

  • Pure context building (use audit-context-building)
  • Entry point identification only (use entry-point-analyzer)
  • Single-dimension only (use semantic-guard-analysis or state-invariant-detection)

Token Budget Rules

Follow these strictly to avoid context exhaustion:

  1. Be terse. Use bullet points and tables, not prose. No filler sentences.
  2. Smart scope first. Classify the contract type in Phase 1, then run ONLY relevant engines in Phase 2 (see engine selection matrix below).
  3. Tiered output depth:
    • Critical/High findings → full detail + PoC code
    • Medium findings → root cause + exploit scenario (no PoC)
    • Low/Info findings → one-line description only
  4. No redundant analysis. If a dimension has no attack surface (e.g., no value flows = skip ETE), say "N/A" and move on.
  5. Cap Phase 1 output to ≤30 lines per contract. List invariants and states, skip verbose specification documents.
  6. PoC generation only for Critical and High severity findings. For others, describe the exploit path in ≤3 steps.
  7. Combine phases in output — don't repeat findings across phases. Each finding appears once with all metadata inline.

Pipeline

Phase 1: Behavioral Decomposition (keep brief)

Extract intent from code and docs. Output per contract:

Contract: <Name>
Type: <DeFi/Token/Governance/NFT/Utility/Proxy>
States: [list]
Key Invariants (≤5):
  - <invariant>
Privileged Roles: [list]
Value Entry/Exit Points: [list or "none"]

Then select engines:

Contract TypeRun ETERun ACTERun SITE
DeFi (DEX/lending/vault/staking)YesYesYes
Token (ERC20/721/1155)YesLiteLite
Governance/DAOLiteYesYes
NFT marketplaceYesYesLite
Utility/LibraryNoLiteLite
Proxy/UpgradeableNoYesYes

Lite = check only the top-priority item for that engine (see below).

Phase 2: Threat Modeling (selected engines only)

Run only the engines selected above. For each engine, analyze in this priority order — stop if contract surface is exhausted:

Economic Threat Engine (ETE):

  1. Value flow tracing — where can value enter/leave? Any sinks or circular flows?
  2. Economic invariant verification — does deposits == withdrawals + balance hold?
  3. Incentive analysis — any rational actor exploits (MEV, sandwich, griefing)?

Access Control Threat Engine (ACTE):

  1. Unprotected privileged functions — any admin/owner actions callable by anyone?
  2. Role escalation paths — can User → [actions] → Admin?
  3. msg.sender vs tx.origin confusion; signature replay

State Integrity Threat Engine (SITE):

  1. Non-atomic state updates — partial updates before external calls?
  2. Sequence vulnerabilities — initialization bypass, unexpected call ordering?
  3. Cross-contract stale data or reentrancy vectors

Lite mode = run only item #1 from that engine's list.

Phase 3: Exploit Verification

For each hypothesis from Phase 2:

  • Build attack sequence (≤5 steps)
  • For Critical/High: generate minimal Foundry/Hardhat PoC (keep code short — test the specific vuln, not a full test suite)
  • Quantify impact: Critical (all funds/system) | High (significant loss/privesc) | Medium (griefing/DOS) | Low (info/best practice)

Phase 4: Score & Prioritize

Score: Confidence = (Evidence × Feasibility × Impact) / FP_Rate

Factor1.00.70.40.1
EvidenceConcrete path, no depsSpecific state neededPattern-basedHeuristic
FeasibilityPoC confirmedAchievable stateExternal conditionsInfeasible

Impact: 5=total loss, 4=partial loss, 3=griefing, 2=info leak, 1=best practice FP_Rate: 0.05 (known pattern) → 0.15 (moderate) → 0.40 (weak) → 0.60 (heuristic)

Prioritization: Report findings ≥10% confidence. Never suppress Impact ≥4.

Finding Format (use for every finding)

### [F-N] Title
Severity: Critical|High|Medium|Low  |  Confidence: X%
Location: contract.sol#L10-L25, functionName()
Root Cause: <1-2 sentences>
Exploit: <numbered steps, ≤5>
Impact: <1 sentence with quantified risk>
Fix: <code diff or 1-2 sentence recommendation>
PoC: <only for Critical/High — minimal test code>

Advanced Checks (run only if relevant to contract type)

  • Cross-contract: Map external call chains A→B→C, test transitive trust
  • Time-based: block.timestamp manipulation, expired signatures, replay
  • Upgradeable: Storage collisions, re-initialization, migration atomicity

Mindset

  • "Standard function" → can behave non-standardly in context
  • "Admin is trusted" → model admin compromise, check excessive powers
  • "Known pattern" → novel interactions in specific contexts
  • "Small value" → compounds; griefing scales
  • "Trusted external contract" → trust boundaries shift; verify actual code

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Behavioral State Analysis AI skill do?

Token-efficient smart contract security auditing via Behavioral State Analysis (BSA). Scopes analysis to contract type, runs only relevant threat engines, and uses tiered output depth. Use for auditing smart contracts, security reviews, or DeFi threat modeling.

Why use Behavioral State Analysis on TypingMind?

Because you install it once and use it with any model. Behavioral State Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Behavioral State Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/quillai-network/quillshield_skills/tree/main/plugins/behavioral-state-analysis/skills/behavioral-state-analysis. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Behavioral State Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Behavioral State Analysis?

As many as you like. As long as a model supports skills, you can use Behavioral State Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Behavioral State Analysis AI skill free?

Yes. It is published on GitHub by quillai-network under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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