semvec/pypi-packages huggingface dataset:
pytegrity 0.1.6.3
Well Integrity Log analysis and Visualization tool [This is a Test Release]

# Well Integrity Visualization Tool

# pytegrity

`pytegrity` 
This application allows users to upload LAS files, visualize well integrity, and extract finger logs to analyze data related to Well integrity issues (Corrosion, Deposition, etc).

## Requirements
Before running the app, make sure to install the following libraries:

```bash
pip install streamlit lasio pandas plotly pytegrity
``` 

![Interactive application](https://raw.githubusercontent.com/Nashat90/pytegrity/main/images/stream.png)

## Features
File Upload: Upload LAS files for analysis.

Finger Log Selection: Choose which finger/pad logs to visualize.

Depth Range Control: Adjust the depth range for the plot using a slider.

Plot Customization: Customize the plot's height and width.

Well Integrity Visualization: View a detailed plot representing the well integrity with selected logs and depth ranges.

## Usage
Upload LAS File:

On the sidebar, click the "Upload LAS File" button to upload your LAS file.

The file is temporarily stored for processing.
![Interactive notebook](https://raw.githubusercontent.com/Nashat90/pytegrity/main/images/jup.png)
## Select Finger Logs:

Choose the desired finger logs to include in the visualization.

Adjust Depth Range:

Use the depth range slider to select the depth interval to visualize.

## Plot Customization:

Set the height and width of the plot for better visualization.

## Visualization:

After selecting your preferences, the app will generate the well integrity plot based on the LAS file data.

Code Breakdown
File Upload:
The file_uploader method is used to upload LAS files, and the uploaded file is saved temporarily for further processing.

Data Loading:
The LAS file is read using the lasio library and converted to a pandas DataFrame.

Finger Log Selection:
Users can select columns that contain "FING" to display the desired finger logs.

Depth Range Selection:
The depth range for visualization is controlled through the sidebar slider, adjusting the Y-axis range on the plot.

Visualization:
The plot_well_integrity method from the pytegrity module is used to plot well integrity data. The plot is generated dynamically with customizable height and width.
LogicPwn 0.1.3
A modular web application security testing framework
Requires Python: <4.0,>=3.9

# LogicPwn

LogicPwn is a modern, extensible framework for automated business logic vulnerability assessment, exploit chaining, and professional reporting.

## Features
- 🔐 **Authentication**: Flexible session management
- 🚀 **Request Runner**: Advanced HTTP operations
- ✅ **Response Validator**: Powerful response analysis
- 🔍 **Access Detector**: Automated IDOR & access control detection
- ⚡ **Exploit Engine**: Automated exploit chaining
- 📄 **Report Generator**: Professional, multi-format reporting (Markdown, HTML, JSON)
- 🧩 **Extensible**: Plugin-ready, template-driven, and highly modular
- 🛡️ **Security**: Automatic sensitive data redaction, CVSS scoring, and privacy compliance

## Quickstart

```python
from logicpwn.core.reporter.orchestrator import ReportGenerator, ReportConfig, VulnerabilityFinding, ReportMetadata
from datetime import datetime

# Configure the report
config = ReportConfig(
    target_url="https://target.com",
    report_title="Security Assessment Report"
)
reporter = ReportGenerator(config)

# Add a finding
finding = VulnerabilityFinding(
    id="IDOR-001",
    title="IDOR in User Profile",
    severity="High",
    description="User profile accessible without auth...",
    affected_endpoints=["/api/users/{id}"],
    proof_of_concept="GET /api/users/123",
    impact="Sensitive data exposure",
    remediation="Add access control",
    discovered_at=datetime.now()
)
reporter.add_finding(finding)

# Set metadata
reporter.metadata = ReportMetadata(
    report_id="RPT-001",
    title="Security Assessment Report",
    target_url="https://target.com",
    scan_start_time=datetime.now(),
    scan_end_time=datetime.now(),
    logicpwn_version="1.0.0",
    total_requests=100,
    findings_count={"High": 1}
)

# Generate and export
reporter.export_to_file("report.md", "markdown")
reporter.export_to_file("report.html", "html")
```

## Reporting Module Highlights
- **Multi-format**: Markdown, HTML, JSON (PDF coming soon)
- **Templates**: Customizable with Jinja2 or fallback
- **Streaming**: Handles large reports efficiently
- **Redaction**: Built-in and custom regex rules
- **CVSS**: Automated, extensible scoring
- **API Docs**: Full Sphinx documentation in `docs/`
- **Tests**: Comprehensive pytest suite in `tests/core/reporter/`

## Documentation
- **API Reference**: See `docs/build/index.html` (after running `poetry run sphinx-build docs/source docs/build`)
- **Getting Started**: See `docs/source/getting_started.rst`
- **Examples**: See `examples/reports/`

## Testing
Run all tests with:
```sh
poetry run pytest tests/core/reporter/
```

## Contributing
- PRs welcome! Please add tests and docstrings for new features.
- For questions or feature requests, open an issue.

---
LogicPwn © 2024 | MIT License