metadata
tags:
- safetensors
- zkaedi-prime
- hamiltonian-dynamics
- vulnerability-detection
- bytecode-analysis
- bare-metal
- evm
- smart-contracts
- security
- ensemble-specialist
license: mit
🔱 Kraken v2.2 — Bytecode Feature Vulnerability Classifier
Ensemble Specialist #2 (Leviathan v2 = Specialist #1)
8 independent binary MLP classifiers detecting EVM bytecode vulnerability patterns. Each classifier answers one question: "Is this bytecode vulnerable to [specific class]?"
Architecture
EVM Bytecode
→ Disassemble (skip PUSH immediates)
→ 32-dim hand-crafted feature vector:
[0-15] Category ratios (16 opcode categories)
[16] Unguarded CALL→SSTORE (reentrancy signal)
[17] SSTORE before CALL (CEI safe pattern)
[18-21] Dangerous opcode flags (DELEGATECALL, SELFDESTRUCT, ORIGIN, TIMESTAMP)
[22] Guarded CALL→SSTORE (anti-reentrancy)
[23] Arithmetic without guard ratio (overflow risk)
[24-25] Context (CALLVALUE, BALANCE)
[26] Consecutive CALLs without SSTORE (flash loan)
[27] Unchecked CALL (CALL→POP)
[28-31] Statistical (total ops, unique ops, entropy, CALL density)
→ 8× BinaryMLP(32 → 32 → 1)
→ 19-dim score vector
Performance
| Class | F1 | Precision | Recall |
|---|---|---|---|
| Reentrancy (SWC-107) | 1.000 | 1.000 | 1.000 |
| Integer Overflow (SWC-101) | 1.000 | 1.000 | 1.000 |
| tx.origin Auth (SWC-115) | 1.000 | 1.000 | 1.000 |
| Delegatecall Inj (SWC-112) | 1.000 | 1.000 | 1.000 |
| Flash Loan Attack | 1.000 | 1.000 | 1.000 |
| Selfdestruct (SWC-106) | 1.000 | 1.000 | 1.000 |
| Timestamp Dep (SWC-116) | 1.000 | 1.000 | 1.000 |
| Unchecked Return (SWC-104) | 1.000 | 1.000 | 1.000 |
Total parameters: 8,712 (1,089 per classifier × 8 classifiers)
Ensemble Fusion (v2.2)
For 2 specialists (Leviathan + Kraken), simple rule-based fusion:
- Both flag > 0.5 → THREAT (mean + 0.10 agreement boost)
- One flags > 0.8 → THREAT (max × 0.85 single-detect)
- One flags > 0.5 → UNCERTAIN (max × 0.50)
- Neither flags → CLEAN (pass through)
No FHN Laplacian coupling (caused cross-class energy leaking in v2.1). FHN with kappa=0 reserved for 3+ specialists.
ZKAEDI Security Pipeline
Solidity Code
→ gemma-2-9b-solidity-merged (vulnerability energy signatures)
→ prime-swarm-hunter (12-agent temporal compound detection)
→ LEVIATHAN v2 (EVM trace topology: 265K params)
→ KRAKEN v2.2 (bytecode features: 8,712 params) ← THIS MODEL
→ PRIME Simple Fusion (rule-based for 2 specialists)
→ solidity-vuln-auditor-7b (final audit report)
Usage
from safetensors.numpy import load_file
import numpy as np
# Load weights
d = load_file("kraken_v2.2.safetensors")
# Reconstruct classifier (example for reentrancy)
w1, b1 = d["reentrancy.w1"], d["reentrancy.b1"]
w2, b2 = d["reentrancy.w2"], d["reentrancy.b2"]
# Inference
features = extract_features(bytecode) # 32-dim vector
h = np.maximum(features @ w1.T + b1, 0) # ReLU
score = 1.0 / (1.0 + np.exp(-(h @ w2.T + b2)[0])) # sigmoid
Companion Files
| File | Purpose |
|---|---|
kraken_v2.2.safetensors |
Trained weights (safetensors) |
kraken_v2.2.npz |
Trained weights (numpy) |
kraken_v2.2_weights.h |
C header for bare-metal inference |
Version History
- v1.0: CNN on 16×16 manifold, 265K params → dead (all outputs 0.105)
- v1.1: +MaxPool, 19K params → still dead (sparse manifold)
- v2.0: Feature-based + 8 binary MLPs → 7/8 F1=1.0, reentrancy FPs
- v2.1: Strict reentrancy features → 8/8 F1=1.0, but FHN Laplacian leaked
- v2.2: Simple fusion rules for 2 specialists → clean, no false positives ✓
Author
ZKAEDI — Offensive Healer