GnomeMan4201/BANANA_TREE
GitHub: GnomeMan4201/BANANA_TREE
BANANA_TREE 是一个对抗性训练生态系统,通过模拟真实攻击来提升安全防御能力。
Stars: 1 | Forks: 0
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```
[](https://github.com/GnomeMan4201)
[](https://github.com/GnomeMan4201)
[](https://github.com/GnomeMan4201)
## 查看 /etc/banana_tree/philosophy.txt 的内容
```
BANANA_TREE exists to teach the adversarial mindset.
not designed....but evolved out of NECESSITY
every tool in this ecosystem was built to close a real gap
in a real problem at a real moment.
laid side by side they form a complete end-to-end
adversarial training environment.
that was not the plan.
but became part of it..
```
## 列出 ./ecosystem 的详细信息
```
BANANA_TREE/
│
├── roots/ # observe — know your environment
│ ├── LANimals
│ ├── OpenSight
│ └── devto-analytics-pro
│
├── trunk/ # simulate — model the threat
│ ├── Lune
│ ├── Decoy-Hunter
│ └── bad_BANANA
│
├── branches/ # execute — apply the pressure
│ ├── zer0DAYSlater
│ ├── OWN
│ └── Blackglass_Suite
│
└── fruit/ # adapt — close the loop
├── reflexive-identity
├── devto-bot-audit
└── badBANANA zine // Issue 01
```
## 列出 ./roots/ 的详细信息
### 🌿 LANimals
实时局域网映射、异常检测、行为风险评分、
蜜罐陷阱引擎、力导向图可视化。
这是基础——无法被看见的东西就无法被防御。
```
role: observation layer — maps the environment in real time
feeds: threat surface data into simulation and execution layers
stack: Python · FastAPI · SQLite · D3.js · SQLAlchemy
```
[](https://github.com/GnomeMan4201/LANimals)
### 🌿 OpenSight
实体提取、类型化知识图谱、社区检测、
LLM 摘要、调查包系统。
将原始文档转化为结构化情报。
```
role: intelligence layer — extracts signal from unstructured data
feeds: entity and relationship data into analysis and adaptation
stack: Python · FastAPI · SQLAlchemy · Canvas API · SQLite
```
[](https://github.com/GnomeMan4201/OpenSight)
### 🌿 devto-analytics-pro
追踪开发者平台的参与度、增长信号和行为模式。
针对公开画像的表层OSINT。
```
role: signal layer — monitors public-facing behavioral patterns
stack: Python · FastAPI · SQLite
```
[](https://github.com/GnomeMan4201/devto-analytics-pro)
## 列出 ./trunk/ 的详细信息
### 🌿 Lune
64模块的谍报技术库。由LLM驱动的突变引擎。
预构建的操作链。加密的C2(AES-128-CBC + HMAC-SHA256)。
统一的身份系统。具有加密信标/报告周期的加固代理。
```
role: simulation layer — models adversarial behavior end-to-end
note: authorized red team ops and controlled lab simulation only
stack: Python · MIT licensed · CI passing
```
[](https://github.com/GnomeMan4201/Lune)
### 🌿 Decoy-Hunter
主动欺骗部署与检测工具。
布置陷阱。观察其触发。学习是什么触发了它。
```
role: deception layer — creates false surfaces, detects contact
feeds: behavioral data back into observation layer
stack: Python
```
[](https://github.com/GnomeMan4201/Decoy-Hunter)
### 🌿 bad_BANANA
适用于 Android (Termux) + Debian 的无需root权限的攻击性工具包。
为在传统实验室环境之外工作的操作员而构建。
```
role: mobile simulation layer — extends the environment off-network
stack: Python · Shell
```
[](https://github.com/GnomeMan4201/bad_BANANA)
## 列出 ./branches/ 的详细信息
### 🌿 zer0DAYSlater
AI驱动的有效载荷突变、自适应持久化、
实时漏洞利用技术。
```
role: execution layer — applies offensive pressure to test defense
note: authorized simulation environments only
stack: Python
```
[](https://github.com/GnomeMan4201/zer0DAYSlater)
### 🌿 OWN
```
role: execution layer — payload staging and persistence testing
note: authorized simulation environments only
stack: Python
```
[](https://github.com/GnomeMan4201/OWN)
### 🌿 Blackglass Suite
```
role: execution layer — operational support and environment setup
stack: Shell · Bash
```
[](https://github.com/GnomeMan4201/Blackglass_Suite)
## 列出 ./fruit/ 的详细信息
### 🌿 reflexive-identity
针对自主代理的持续信任评分。
当系统质疑自身时——那就是适应层。
```
role: adaptation layer — closes the loop, updates the model
stack: Python
```
[](https://github.com/GnomeMan4201/reflexive-identity)
### 🌿 badBANANA // Issue 01 — 生命系统
从运行此生态系统中学到的一切——
浓缩成一份安全研究出版物。
树之果实。
```
topics: adversarial AI · prompt-space security · network deception
living off the land · red team ops
release: DEF CON
format: monospace · cream / black / maroon
```
[](https://github.com/GnomeMan4201/bad_BANANA/releases/tag/issue-01)
## 查看 ./origin.txt 的内容
```
BANANA_TREE was not planned.
each tool was built alone, in the moment,
to solve a problem that existed right then.
LANimals because the network was invisible.
OpenSight because the documents were unreadable.
Lune because simulation required a real engine.
Decoy-Hunter because traps needed to be set.
zer0DAYSlater because defense needed real pressure.
reflexive-identity because the agent needed to doubt itself.
laid side by side:
a complete adversarial training environment.
that is what emergence looks like.
that is the adversarial mindset in practice —
built the tools you needed,
discovered the system you had.
```
```
good defense takes good offense
```
*© badBANANA collective // LANimals // gnomeman4201*
标签:Cutter, TGT, 人工智能安全, 反取证, 合规性, 安全评估, 密钥泄露防护, 对抗训练, 应用安全, 攻击模拟, 攻防演练, 数据展示, 机器学习安全, 生态系统, 红队, 网络安全, 逆向工具, 隐私保护, 集体协作, 驱动签名利用