v0.1.5

Full Changelog: v0.1.4...v0.1.5

v0.1.4

refactor(config): rename app host/port to assistant and add log level

- Update .env.example to use ASSISTANT_HOST and ASSISTANT_PORT
- Remove unused AppConfigs class and related imports
- Add log_level field to Configs for configurable logging
- Move postgres_db import to top in main.py
- Update logger to use configurable log level from configs

BREAKING CHANGE: Environment variables APP_HOST and APP_PORT have been renamed to ASSISTANT_HOST and ASSISTANT_PORT. Update your environment configuration accordingly.

Release v0.1.0

🚀 OASM Assistant v0.1.0 (Initial Release)

First major release of OASM Assistant - an AI-powered security analysis platform for the Open Attack Surface Management (OASM) ecosystem.

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✨ Key Features

🤖 AI Security Analysis

Automated vulnerability analysis powered by specialized multi-agent architecture. Each agent handles specific aspects (recon, vulnerability detection, exploitation analysis) and coordinates through MCP protocol. Results are streamed in real-time, allowing step-by-step monitoring of the analysis process.

🌐 Domain Classification

Automatically categorize domains/targets into 50+ industry categories (E-commerce, Banking, Healthcare, Government, etc.). Leverages AI to accurately identify technology stacks and business sectors, with smart retry logic for API error handling, optimizing scanning strategies for each target type.

⚡ Nuclei Template Generate

Automatically generate custom Nuclei security templates based on vulnerability descriptions or analysis results. Uses RAG with Langchain to reference 11000+ existing templates, combined with attack pattern knowledge to create accurate, ready-to-use templates for verification and large-scale scanning.

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📋 What's Changed

• feat: Convert RAG module using LangChain, generate streaming analysis by @ntthanh2603 in #55
• feat: Use LlamaIndex for RAG pipeline by @ntthanh2603 in #53
• feat: Base agent architecture implementation by @ntthanh2603 in #44
• feat: Design database models for chatbot conversation history by @ntthanh2603 #30
• feat: Base agent architecture implementation by @ntthanh2603 #29

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🚦 Quick Start

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env

# Run server
python -m app.main

Full Changelog: https://github.com/oasm-platform/oasm-assistant/commits/v0.1.0