Security Layers

MIESC implements 9 specialized security layers, each targeting different vulnerability classes.

Layer Overview

Layer

Name

Tools

Detection Focus

1

Static Analysis

Slither, Aderyn, Solhint

Code quality, known patterns

2

Pattern Detection

Semgrep, SmartBugs

Regex patterns, signatures

3

Symbolic Execution

Mythril, Halmos

Path exploration, constraints

4

Fuzzing

Echidna, Medusa, Foundry

Property-based testing

5

Formal Verification

Certora, SMTChecker

Mathematical proofs

6

ML Detection

DA-GNN, FP Classifier

Graph neural networks

7

LLM Analysis

SmartLLM, GPTLens

Semantic understanding

8

DeFi Security

DeFi Detector

Flash loans, oracles, MEV

9

Advanced Detection

Advanced Detector

Rug pulls, governance

Layer 1-2: Static Analysis

Fast, comprehensive code scanning:

  • Slither: 90+ detectors, AST-based analysis

  • Aderyn: Rust-based, fast detection

  • Solhint: Linting and best practices

  • Semgrep: Custom pattern rules

Strengths:

  • Very fast (<10 seconds)

  • Low false positive rate

  • Catches common vulnerabilities

Limitations:

  • Cannot detect runtime issues

  • Limited cross-function analysis

Layer 3: Symbolic Execution

Path exploration with constraint solving:

  • Mythril: SMT-based symbolic execution

  • Halmos: Symbolic testing framework

Strengths:

  • Finds deep logic bugs

  • Proves absence of bugs

  • Generates exploit inputs

Limitations:

  • Path explosion on complex code

  • Slow (30s-5min per contract)

Layer 4: Fuzzing

Random and guided testing:

  • Echidna: Property-based fuzzer

  • Medusa: Parallel fuzzer

  • Foundry Fuzz: Integrated testing

Strengths:

  • Finds edge cases

  • Tests invariants

  • Fast iteration

Limitations:

  • Requires test harnesses

  • May miss rare paths

Layer 5: Formal Verification

Mathematical correctness proofs:

  • Certora: CVL specification language

  • SMTChecker: Solc built-in verifier

Strengths:

  • Proves properties hold

  • Covers all paths

  • High confidence

Limitations:

  • Requires specifications

  • Complex to set up

  • False positives on timeouts

Layer 6: ML Detection

Machine learning vulnerability detection:

  • DA-GNN: Graph neural network

  • FP Classifier: False positive reduction

Strengths:

  • Learns from patterns

  • Reduces false positives

  • Adapts to new code

Limitations:

  • Requires training data

  • Black box predictions

Layer 7: LLM Analysis

Large language model semantic analysis:

  • SmartLLM: Multi-stage analysis

  • GPTLens: Auditor + Critic architecture

  • LLMBugScanner: Ensemble voting

Strengths:

  • Understands context

  • Explains findings

  • Generates fixes

Limitations:

  • Hallucinations possible

  • Slow (30s-2min)

  • API costs (for cloud models)

Layer 8: DeFi Security

DeFi-specific vulnerability detection:

  • Flash loan attacks

  • Oracle manipulation

  • Price manipulation

  • MEV vulnerabilities

  • Liquidation issues

Strengths:

  • DeFi domain expertise

  • Protocol-specific checks

  • Cross-contract analysis

Limitations:

  • Limited to DeFi patterns

  • Requires protocol knowledge

Layer 9: Advanced Detection

Emerging threat detection:

  • Rug pull patterns

  • Governance attacks

  • Honeypot detection

  • Proxy vulnerabilities

  • Centralization risks

Strengths:

  • Catches modern attacks

  • Token security analysis

  • Upgrade safety

Limitations:

  • Higher false positive rate

  • Requires context

Layer Selection

MIESC automatically selects layers based on:

  1. Tool availability

  2. Contract complexity

  3. Time budget

  4. Confidence requirements

# Full analysis (all layers)
miesc audit full contract.sol

# Quick scan (layers 1-2 only)
miesc audit quick contract.sol

# Static + LLM (layers 1-2, 7)
miesc audit static contract.sol --llm-interpret