semvec/pypi-packages huggingface dataset:
flax-metrics 0.4.0
Flax NXX implementation of common metrics.
Requires Python: >=3.10
Keywords: flax, jax, metrics, machine-learning

# 📏 Flax Metrics [![Flax Metrics](https://github.com/tillahoffmann/flax-metrics/actions/workflows/ci.yml/badge.svg)](https://github.com/tillahoffmann/flax-metrics/actions/workflows/ci.yml) [![PyPI version](https://img.shields.io/pypi/v/flax-metrics.svg)](https://pypi.org/project/flax-metrics/) [![Documentation Status](https://readthedocs.org/projects/flax-metrics/badge/?version=latest)](https://flax-metrics.readthedocs.io/)

Flax NXX implementation of common metrics. See the [documentation](https://flax-metrics.readthedocs.io/) for a comprehensive list of available metrics.

```python
>>> from flax_metrics import Precision, Recall
>>> from jax import numpy as jnp

>>> labels = jnp.asarray([ 0,  0,  0,  1,  1,  1])
>>> logits = jnp.asarray([-1, -2,  2,  1, -1, -2])

>>> metric = Recall()
>>> metric.update(labels=labels, logits=logits)
Recall(...)
>>> metric.compute()
Array(0.333..., dtype=float32)

```

## Masking

`jax.jit` requires re-compilation for arrays of different shapes, making evaluation on subsets challenging—we cannot index arrays with a mask. Flax Metrics supports masking through the keyword-only argument `mask`. The example below illustrates that passing `mask` is equivalent to indexing the input with a binary mask.

```python
>>> mask = jnp.asarray([True, True, True, True, False, True])
>>> metric = Recall()
>>> metric.update(labels=labels, logits=logits, mask=mask)
Recall(...)
>>> metric.compute()
Array(0.5, dtype=float32)

>>> metric.reset()
Recall(...)
>>> metric.update(labels=labels[mask], logits=logits[mask])
Recall(...)
>>> metric.compute()
Array(0.5, dtype=float32)

```

## Chaining

Metric creation, updates, and computation can be combined into one expression by chaining operations.

```python
>>> Recall().update(labels=labels, logits=logits).compute()
Array(0.333..., dtype=float32)

```
secretsdump-ng 1.1.2
Next-generation secretsdump tool using DSInternals for credential extraction
Requires Python: >=3.8
Keywords: security, pentest, active-directory, credentials, secretsdump, secretsdump-ng

# secretsdump-ng

Credential dumping tool that uses DSInternals for extracting credentials from Windows systems, using any available command-execution port (rather than relying on 445).

Massive props to DSInternals & Impacket; this tool really isn't anything revolutionary and uses the impressive work already completed by Michael Grafnetter and the Fortra team.

## Features

- NTDS.DIT extraction using DSInternals on Domain Controllers
- Registry hive dumping (SAM, SYSTEM, SECURITY) on Windows Servers
- Multi-threaded operations for dumping from multiple hosts
- Secure transfer of credentials via HTTPS
- Filtered extraction - dump only specific users with `--just-dc-user`

## Usage

```bash
# Dump all credentials from a single host
secretsdump-ng 192.168.1.10 username password

# Dump from multiple hosts using IP range
secretsdump-ng 192.168.1.10-20 username password

# Dump only a specific user
secretsdump-ng 192.168.1.10 username password --just-dc-user administrator

# Use more threads for faster scanning
secretsdump-ng 192.168.1.1-254 username password --threads 20

# Verbose output
secretsdump-ng 192.168.1.10 username password -v
```

## How It Works

1. **Sets up HTTPS server** on port 1338 to receive credential dumps
2. **Executes PowerShell remotely** on target systems using `AuthFinder`
3. **Extracts registry hives** (SAM, SYSTEM, SECURITY) from all Windows systems
4. **Extracts NTDS.DIT** using DSInternals on Domain Controllers
5. **Processes and formats** credentials using impacket-secretsdump
6. **Saves output** to `./secretsdump_ng_out/[IP]/secretsdump.out`


Admin accounts are highlighted with `(admin)` tag. Machine accounts are sorted to the bottom.

## Security Notes

- Uses temporary SSL certificates for HTTPS transfers
- Temporary files on target systems are stored in `$env:TEMP` and cleaned up after extraction

## License

MIT License - see LICENSE file for details

## Disclaimer

This tool is intended for authorized security assessments only. Ensure you have proper authorization before using this tool on any systems.