cantordust-viz
Binary visualization for human pattern recognition - Ghidra plugin by Chris Domas (xoreaxeaxeax)
소스 정보
- 저장소
- plurigrid/asi
- 최근 소스 활동
- 2026년 6월 10일 11:55
- 감지된 SKILL.md 언어
- 영어
- 스타
- 67
- 포크
- 12
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소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
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SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- cantordust-viz
- description
- Binary visualization for human pattern recognition - Ghidra plugin by Chris Domas (xoreaxeaxeax)
- metadata
- {"trit":-1,"color":"#E54951","gf3_role":"MINUS","version":"1.0.0","repo":"Battelle/cantordust","author":"Chris Domas (xoreaxeaxeax)","interface_ports":["References"]}
# Cantordust Binary Visualization
> **Use when embeddings fail: humans see patterns algorithms miss.**
Visual binary analysis tool for Ghidra. Converts binary data to bitmaps/visualizations where structural patterns become visible to human pattern recognition.
## GF(3) Triad
```
cantordust-viz (-1) ⊗ skill-embedding-vss (0) ⊗ radare2-hatchery (+1) = 0 ✓
```
## Lineage: 2020 Binary Analysis
| Tool | Approach | Strength |
|------|----------|----------|
| **Cantordust** | Visual/human | Sees patterns ML misses |
| **Zignatures** | Soft signatures | Fuzzy matching + keyspace reduction |
| **skill-embedding-vss** | MLX embeddings | O(1) similarity at scale |
## Installation
```bash
git clone https://github.com/Battelle/cantordust.git
# Add to Ghidra Script Manager
```
## Key Insight
From xoreaxeaxeax's work:
- **movfuscator**: All x86 can be MOV (Turing-complete)
- **sandsifter**: Fuzzing reveals undocumented CPU instructions
- **Cantordust**: Binary structure visible in 2D projections
## When to Use
1. **Embedding similarity unclear** → visualize both binaries
2. **Obfuscation suspected** → visual patterns survive obfuscation
3. **Cross-architecture comparison** → structural similarity visible
4. **Malware family classification** → visual fingerprinting
## xoreaxeaxeax Ecosystem (19K+ stars)
| Repo | Stars | Category |
|------|-------|----------|
| movfuscator | 10,075 | obfuscation |
| sandsifter | 4,998 | hardware security |
| rosenbridge | 2,380 | hardware backdoors |
| REpsych | 1,031 | anti-RE |
## Integration with skill-embedding-vss
```python
# When embeddings show high similarity but you want visual confirmation
from cantordust import visualize_binary
from skill_embedding_vss import SkillEmbeddingVSS
vss = SkillEmbeddingVSS('/path/to/skills')
similar = vss.find_nearest('target', k=5)
# Visual confirm top matches
for name, dist in similar[:3]:
visualize_binary(f'/path/to/{name}') # Human reviews
```
## References
- [Cantordust GitHub](https://github.com/Battelle/cantordust)
- [Battelle Blog Post](https://inside.battelle.org/blog-details/battelle-publishes-open-source-binary-visualization-tool)
- [DEF CON talks by xoreaxeaxeax](https://www.youtube.com/results?search_query=xoreaxeaxeax+defcon)
## Cantordust ↔ Gay.jl Bridge
```julia
# cantordust_gay_bridge.jl connects:
# 1. Cantordust 2-tuple byte pair visualization
# 2. CJ Carr spectral features (diffusion transformers)
# 3. Gay.jl deterministic coloring (SPI)
result = analyze_binary_with_gay("target.bin")
# Returns: matrix, diagonal_score, ascii_score, trit_sum, sample_colors
```
## Pattern Theory
| Domain | Representation | Gay.jl Mapping |
|--------|----------------|----------------|
| Binary (Cantordust) | 2-tuple → 256×256 | entropy → trit → color |
| Audio (CJ Carr) | Mel spectrogram | centroid/flatness → HSL |
| Color (Gay.jl) | SplitMix64 + golden angle | SPI deterministic |
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