---
language:
- en
license: mit
task_categories:
- text-generation
- text-classification
tags:
- cyber-security
- red-teaming
- chain-of-thought
- agent-reasoning
- synthetic
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: response
    dtype: string
  - name: hypothesis
    dtype: string
  - name: confirmed
    dtype: bool
  - name: severity
    dtype: string
  splits:
  - name: train
    num_bytes: 73400320
    num_examples: 100000
  download_size: 73400320
  dataset_size: 73400320
configs:
- config_name: default
  data_files:
  - split: train
    path: security_dataset.jsonl
---

# 🛡️ Security Analyst CoT Dataset (100k)

A massive-scale, synthetically generated dataset designed to train **AI Security Agents** in offensive reasoning, vulnerability verification, and false positive reduction.

## Dataset Summary
- **Size:** 100,000 Unique Samples
- **Format:** JSONL
- **Focus:** Chain-of-Thought (CoT) Reasoning for Web Security
- **Logic:** Observation -> Hypothesis -> Evidence -> Decision (O-H-E-D)

## Features
Each sample simulates a complete cognitive process of a Senior Security Analyst:
1.  **Instruction**: The raw HTTP request + The server's response code/body.
2.  **Reasoning**: A `

<div class="think">` block analyzing the anomaly, evidence, and conclusion.<br />3.  **Verdict**: Structured labels for `STATUS`, `SEVERITY`, and `NEXT_TEST`.<br /><br />## Attack Categories<br />The dataset covers a wide spectrum of modern web threats:<br />- **Injection**: SQLi, XSS (Reflected/Stored), Command Injection, LDAPi.<br />- **Business Logic**: Price Manipulation, Mass Assignment, Race Conditions.<br />- **Protocol**: HTTP Request Smuggling, Host Header Injection.<br />- **Anomalies**: Zero-Day simulations (Unknown patterns) and Fuzzing noise.<br />- **Benign**: High-entropy legitimate traffic to train False Positive rejection.<br /><br />## Sample Structure<br />```json<br />{<br />  "instruction": "Analyze: GET /api/v1/user?id=1' OR 1=1 HTTP/1.1...",<br />  "response": "<think>\nObservation: ...\nHypothesis: ...\nEvidence: ...\nDecision: ...\n</div>

\nSTATUS: VULNERABLE...",
  "hypothesis": "SQL Injection",
  "confirmed": true,
  "severity": "Critical"
}