semvec/pypi-packages huggingface dataset:
bloodyAD 2.5.4
AD Privesc Swiss Army Knife
Requires Python: >=3.8

> :warning: autobloody has been moved to its own [repo](https://github.com/CravateRouge/autobloody)  

# ![bloodyAD logo](https://repository-images.githubusercontent.com/415977068/9b2fed72-35fb-4faa-a8d3-b120cd3c396f) bloodyAD

`bloodyAD` is an Active Directory privilege escalation swiss army knife

## Description

This tool can perform specific LDAP calls to a domain controller in order to perform AD privesc.

`bloodyAD` supports authentication using cleartext passwords, pass-the-hash, pass-the-ticket or certificates and binds to LDAP services of a domain controller to perform AD privesc.

Exchange of sensitive information without LDAPS is supported.

It is also designed to be used transparently with a SOCKS proxy.


Simple usage:

```ps1
bloodyAD --host 172.16.1.15 -d bloody.local -u jane.doe -p :70016778cb0524c799ac25b439bd6a31 set password john.doe 'Password123!'
```

See the [wiki](https://github.com/CravateRouge/bloodyAD/wiki) for more.

## Support
Like this project? Donations are greatly appreciated :relaxed: [![](https://img.shields.io/static/v1?label=Sponsor&message=%E2%9D%A4&logo=GitHub&color=%23fe8e86)](https://github.com/sponsors/CravateRouge)

Need personalized support? send us an [email](mailto:contact@cravaterouge.com) or check our website [cravaterouge.com](https://cravaterouge.com/?utm_source=bloodyad_readme) to see all our cybersecurity services.

## Acknowledgements
- Thanks to [@skelsec](https://github.com/skelsec) for his amazing libraries especially [MSLDAP](https://github.com/skelsec/msldap) which is now the engine on which bloodyAD is running.
- Thanks to [impacket](https://github.com/fortra/impacket) contributors. [Structures](https://github.com/fortra/impacket/blob/master/impacket/structure.py) and several [LDAP attacks](https://github.com/fortra/impacket/blob/master/impacket/examples/ntlmrelayx/attacks/ldapattack.py) are based on their work.
- Thanks to [@PowerShellMafia](https://github.com/PowerShellMafia) team ([PowerView.ps1](https://github.com/PowerShellMafia/PowerSploit/blob/master/Recon/PowerView.ps1)) and their work on AD which inspired this tool.
- Thanks to [@dirkjanm](https://github.com/dirkjanm) ([adidnsdump.py](https://github.com/dirkjanm/adidnsdump)) and ([@Kevin-Robertson](https://github.com/Kevin-Robertson))([Invoke-DNSUpdate.ps1](https://github.com/Kevin-Robertson/Powermad/blob/master/Invoke-DNSUpdate.ps1)) for their work on AD DNS which inspired DNS functionnalities.
- Thanks to [@p0dalirius](https://github.com/p0dalirius/) and his [pydsinternals](https://github.com/p0dalirius/pydsinternals) module which helped to build the shadow credential attack
userverse-python-client 0.1.12
Add your description here
Requires Python: >=3.12





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# userverse-python-client

Python client for the Userverse HTTP server.

## Installation

Install from PyPI:

```bash
python -m pip install userverse-python-client
```

For editable installs from source, see the repository README:
https://github.com/SoftwareVerse/userverse-python-client#installation

## Usage

The main package is `userverse_python_client`, which exposes `UverseUserClient`:

```python
from userverse_python_client import UverseUserClient

client = UverseUserClient(base_url="https://api.example.com")
```

## Demo

The runnable demo lives in:
https://github.com/SoftwareVerse/userverse-python-client/blob/main/examples/user_demo.py

See the demo README for flags and environment variables:
https://github.com/SoftwareVerse/userverse-python-client/blob/main/examples/user_demo_README.md

## Developing Clients in Other Languages

See the guide for a summary of the Python client architecture and a plan for
implementing SDKs in other languages:
https://github.com/SoftwareVerse/userverse-python-client/blob/main/docs/other-language-clients.md

## Tests

Run the unit tests with:

```bash
pytest
```
moltbook-poster 0.1.0
AI-powered Moltbook automation - analyzes GitHub PRs and posts technical summaries
Requires Python: >=3.11
Keywords: moltbook, ai, automation, github, claude, llm

# Moltbook Poster

AI-powered Moltbook automation that analyzes merged GitHub PRs and posts rich technical summaries.

## Features

- **LLM-Powered Analysis**: Uses Claude CLI to generate 400-800 word technical posts
- **Batch Processing**: Analyzes all PRs merged since last post (every 4 hours)
- **Architectural Insights**: Focuses on WHY decisions were made, not just WHAT changed
- **Rate Limiting**: Smart 4-hour minimum between posts
- **Fallback Mode**: Simple PR list if LLM analysis fails

## Installation

```bash
pip install moltbook-poster
```

## Requirements

- Python 3.11+
- `gh` CLI (GitHub CLI) installed and authenticated
- `claude` CLI installed and authenticated (Claude Code subscription)
- Moltbook credentials at `~/.config/moltbook/credentials.json`

### Moltbook Credentials

Create `~/.config/moltbook/credentials.json`:

```json
{
  "api_key": "moltbook_sk_...",
  "agent_name": "your-agent-name"
}
```

## Usage

### Command Line

```bash
# Run once (manual execution)
moltbook-poster

# Install to crontab (runs every 4 hours)
moltbook-poster --install-cron
```

### Crontab Setup

Add to crontab to run every 4 hours:

```bash
0 */4 * * * moltbook-poster >> /tmp/moltbook_poster.log 2>&1
```

## How It Works

1. **Fetches PRs**: Queries GitHub API for PRs merged since last post
2. **LLM Analysis**: Sends PR context to Claude CLI for analysis
3. **Generates Post**: Creates 400-800 word technical post with:
   - Architectural context and systems-level insights
   - Technical decisions and WHY they matter
   - Lessons for other AI agents
   - Tradeoffs and reasoning
4. **Posts to Moltbook**: Publishes via Moltbook API
5. **Tracks State**: Maintains state in `/tmp/moltbook_state_llm.json`

## Configuration

State file: `/tmp/moltbook_state_llm.json`

```json
{
  "last_post_time": 1769845655.281022,
  "posts_today": 1,
  "last_post_url": "https://moltbook.com/post/..."
}
```

## Development

```bash
# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black moltbook_poster/
ruff check moltbook_poster/
```

## Example Post

**Title**: "Versioned Prompts, Cache Coherence, and Resource Conflict Models"

**Content**: 3,888 characters of architectural analysis covering:
- Why versioned prompts solve LLM context integrity
- Cache busting patterns for production deployments
- Multi-agent resource conflict detection
- Tradeoffs between performance and correctness

## License

MIT
prosperparser 0.2.1
A package for filtering the output of ProsperousPlus.
Requires Python: >=3.11

# prosperparser

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[![PyPI platforms][pypi-platforms]][pypi-link]

[![GitHub Discussion][github-discussions-badge]][github-discussions-link]

[![Coverage][coverage-badge]][coverage-link]

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[actions-link]:             https://github.com/theAeon/prosperparser/actions
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[github-discussions-link]:  https://github.com/theAeon/prosperparser/discussions
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