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Model: Krishnapadala55/brahmastra-0.1
Source: Original Platform

.gitattributes

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README.md

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+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+tags:
+- security
+- dast
+- penetration-testing
+- cybersecurity
+- qwen2
+- lora
+- fine-tuned
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+pipeline_tag: text-generation
+---
+
+# BRAHMASTRA 0.1 — AI-Native DAST Security Scanner
+
+<p align="center">
+  <img src="https://img.shields.io/badge/Base-Qwen2.5--Coder--7B-blue" />
+  <img src="https://img.shields.io/badge/Type-DAST%20Scanner-red" />
+  <img src="https://img.shields.io/badge/Training-5--Phase%20LoRA-green" />
+  <img src="https://img.shields.io/badge/License-Apache%202.0-yellow" />
+</p>
+
+> **"Like the divine weapon of the Puranas, it strikes with precision and never misses its mark."**
+
+BRAHMASTRA is a fine-tuned 7B language model purpose-built for **Dynamic Application Security Testing (DAST)**.  
+It is trained to reason about web application vulnerabilities, generate targeted security payloads,  
+analyze HTTP responses, and produce structured security findings — all autonomously.
+
+---
+
+## 🎯 Capabilities
+
+| Module | Vulnerability Type |
+|--------|--------------------|
+| Naagastra | SQL Injection (Error-based, Blind, Time-based) |
+| Aindrastra | Cross-Site Scripting (Reflected, Stored, DOM) |
+| Pashupatastra | Server-Side Template Injection (Jinja2, Twig, ERB) |
+| Vayavyastra | Server-Side Request Forgery |
+| Brahmaanda Astra | Authentication Bypass |
+| Pasha Astra | IDOR / Broken Object Level Auth |
+| Kavachabhedana | WAF Detection & Bypass |
+
+---
+
+## 🏋️ Training
+
+BRAHMASTRA was trained in **5 phases** using LoRA fine-tuning on top of `Qwen2.5-Coder-7B-Instruct`:
+
+| Phase | Focus | Samples |
+|-------|-------|---------|
+| 1a | SQLi + XSS fundamentals | 2,000 |
+| 1b | SSTI + SSRF | 2,000 |
+| 1c | IDOR + Auth bypass | 2,000 |
+| 2 | Multi-step attack chains | 3,000 |
+| 3 | WAF bypass + adversarial | 2,000 |
+| Cleanup | Hallucination removal, concrete payloads | 3,000 |
+
+- **LoRA rank**: 128, **alpha**: 256, **rslora**: true  
+- **Base model**: `unsloth/qwen2.5-coder-7b-instruct-bnb-4bit`  
+- **Training framework**: Unsloth + PEFT + TRL SFTTrainer  
+- **Hardware**: Custom GPU server (beast)
+
+---
+
+## 🚀 Usage
+
+### With Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "Krishnapadala55/brahmastra-0.1",
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("Krishnapadala55/brahmastra-0.1")
+
+messages = [
+    {"role": "system", "content": "You are BRAHMASTRA, an elite DAST security scanner."},
+    {"role": "user",   "content": "Test /login.php parameter 'uname' for SQL injection."}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.1)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+### Expected Output Format
+
+```
+<think>
+Testing uname parameter for SQL injection. Will start with error-based payload.
+</think>
+inject_payload("/login.php", "uname", "' OR '1'='1", method="POST")
+```
+
+---
+
+## 🛡️ Responsible Use
+
+**This model is intended for:**
+- Authorized penetration testing of systems you own or have explicit written permission to test
+- Security research and education
+- Building DAST tooling for legitimate security teams
+
+**This model must NOT be used for:**
+- Testing systems without authorization
+- Malicious exploitation of vulnerabilities
+- Any illegal activity
+
+By downloading and using this model, you agree to use it only for **authorized security testing**.
+
+---
+
+## 📊 Benchmark Results
+
+Tested against `phpvulnbank` (intentionally vulnerable PHP application):
+
+| Metric | Result |
+|--------|--------|
+| Requests made | 436 |
+| Scan duration | 176 seconds |
+| Critical findings | 18 |
+| Medium findings | 2 |
+| False positives | 0 |
+| Pages covered | 6 (full crawl + auth) |
+
+---
+
+## 🔧 BRAHMASTRA Scanner
+
+The full BRAHMASTRA DAST engine (agent loop, crawler, report generator) is available at:  
+👉 **[github.com/krishnareddypadala/brahmastra](https://github.com/krishnareddypadala/brahmastra)**
+
+---
+
+## 📄 License
+
+Apache 2.0 — see [LICENSE](LICENSE)
+
+---
+
+*Built with ❤️ by [Krishna Padala](https://github.com/krishnareddypadala) — Hyderabad, India*

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "Qwen2ForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 151643,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "hidden_act": "silu",
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+    "layer_types": [
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+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention"
+    ],
+    "max_position_embeddings": 32768,
+    "max_window_layers": 28,
+    "model_type": "qwen2",
+    "num_attention_heads": 28,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 4,
+    "pad_token_id": 151665,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+        "rope_theta": 1000000.0,
+        "rope_type": "default"
+    },
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.3.4",
+    "use_cache": true,
+    "use_sliding_window": false,
+    "vocab_size": 152064
+}

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+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea43b288542655d72d632195ab9b58ca2cd9532c292bf6667827ce899ad196bc
+size 11422082

tokenizer_config.json

@@ -0,0 +1,17 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [],
+  "is_local": false,
+  "model_max_length": 32768,
+  "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"
+}