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Model: Krishnapadala55/brahmastra-0.1 Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- security
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- dast
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- penetration-testing
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- cybersecurity
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- qwen2
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- lora
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- fine-tuned
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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pipeline_tag: text-generation
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---
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# BRAHMASTRA 0.1 — AI-Native DAST Security Scanner
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<p align="center">
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<img src="https://img.shields.io/badge/Base-Qwen2.5--Coder--7B-blue" />
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<img src="https://img.shields.io/badge/Type-DAST%20Scanner-red" />
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<img src="https://img.shields.io/badge/Training-5--Phase%20LoRA-green" />
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<img src="https://img.shields.io/badge/License-Apache%202.0-yellow" />
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</p>
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> **"Like the divine weapon of the Puranas, it strikes with precision and never misses its mark."**
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BRAHMASTRA is a fine-tuned 7B language model purpose-built for **Dynamic Application Security Testing (DAST)**.
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It is trained to reason about web application vulnerabilities, generate targeted security payloads,
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analyze HTTP responses, and produce structured security findings — all autonomously.
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---
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## 🎯 Capabilities
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| Module | Vulnerability Type |
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|--------|--------------------|
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| Naagastra | SQL Injection (Error-based, Blind, Time-based) |
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| Aindrastra | Cross-Site Scripting (Reflected, Stored, DOM) |
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| Pashupatastra | Server-Side Template Injection (Jinja2, Twig, ERB) |
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| Vayavyastra | Server-Side Request Forgery |
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| Brahmaanda Astra | Authentication Bypass |
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| Pasha Astra | IDOR / Broken Object Level Auth |
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| Kavachabhedana | WAF Detection & Bypass |
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---
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## 🏋️ Training
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BRAHMASTRA was trained in **5 phases** using LoRA fine-tuning on top of `Qwen2.5-Coder-7B-Instruct`:
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| Phase | Focus | Samples |
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|-------|-------|---------|
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| 1a | SQLi + XSS fundamentals | 2,000 |
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| 1b | SSTI + SSRF | 2,000 |
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| 1c | IDOR + Auth bypass | 2,000 |
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| 2 | Multi-step attack chains | 3,000 |
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| 3 | WAF bypass + adversarial | 2,000 |
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| Cleanup | Hallucination removal, concrete payloads | 3,000 |
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- **LoRA rank**: 128, **alpha**: 256, **rslora**: true
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- **Base model**: `unsloth/qwen2.5-coder-7b-instruct-bnb-4bit`
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- **Training framework**: Unsloth + PEFT + TRL SFTTrainer
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- **Hardware**: Custom GPU server (beast)
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---
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## 🚀 Usage
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### With Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model = AutoModelForCausalLM.from_pretrained(
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"Krishnapadala55/brahmastra-0.1",
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torch_dtype=torch.float16,
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained("Krishnapadala55/brahmastra-0.1")
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messages = [
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{"role": "system", "content": "You are BRAHMASTRA, an elite DAST security scanner."},
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{"role": "user", "content": "Test /login.php parameter 'uname' for SQL injection."}
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]
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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### Expected Output Format
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```
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<think>
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Testing uname parameter for SQL injection. Will start with error-based payload.
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</think>
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inject_payload("/login.php", "uname", "' OR '1'='1", method="POST")
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```
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---
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## 🛡️ Responsible Use
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**This model is intended for:**
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- Authorized penetration testing of systems you own or have explicit written permission to test
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- Security research and education
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- Building DAST tooling for legitimate security teams
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**This model must NOT be used for:**
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- Testing systems without authorization
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- Malicious exploitation of vulnerabilities
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- Any illegal activity
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By downloading and using this model, you agree to use it only for **authorized security testing**.
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---
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## 📊 Benchmark Results
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Tested against `phpvulnbank` (intentionally vulnerable PHP application):
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| Metric | Result |
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|--------|--------|
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| Requests made | 436 |
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| Scan duration | 176 seconds |
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| Critical findings | 18 |
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| Medium findings | 2 |
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| False positives | 0 |
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| Pages covered | 6 (full crawl + auth) |
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---
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## 🔧 BRAHMASTRA Scanner
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The full BRAHMASTRA DAST engine (agent loop, crawler, report generator) is available at:
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👉 **[github.com/krishnareddypadala/brahmastra](https://github.com/krishnareddypadala/brahmastra)**
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---
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## 📄 License
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Apache 2.0 — see [LICENSE](LICENSE)
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---
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*Built with ❤️ by [Krishna Padala](https://github.com/krishnareddypadala) — Hyderabad, India*
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
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config.json
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"Qwen2ForCausalLM"
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],
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
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"model_type": "qwen2",
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"num_attention_heads": 28,
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|
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"rope_type": "default"
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},
|
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"sliding_window": null,
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"tie_word_embeddings": false,
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"unsloth_fixed": true,
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"unsloth_version": "2026.3.4",
|
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 152064
|
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}
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}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:ea43b288542655d72d632195ab9b58ca2cd9532c292bf6667827ce899ad196bc
|
||||
size 11422082
|
||||
17
tokenizer_config.json
Normal file
17
tokenizer_config.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
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|
||||
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|
||||
"eos_token": "<|im_end|>",
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||||
"errors": "replace",
|
||||
"extra_special_tokens": [],
|
||||
"is_local": false,
|
||||
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|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
|
||||
}
|
||||
Reference in New Issue
Block a user