---
language: en
license: apache-2.0
tags:
  - security
  - secrets-detection
  - code-analysis
  - onnx
library_name: onnxruntime
pipeline_tag: text-classification
---

# Argus Nano

A purpose-built SLM for secrets detection that runs entirely on your machine.

## Model Description

- Fine-tuned from CodeBERT for binary classification: REAL_SECRET vs BENIGN
- Designed to distinguish real API keys, tokens, and credentials from benign lookalikes (test values, hashes, UUIDs, placeholders)
- Context-aware: considers surrounding code, not just the string itself

## Intended Use

- Pre-commit hooks
- CI/CD pipeline scanning
- IDE integration
- Any tool that needs to detect leaked secrets in code

## How to Use

### Python

```python
from argus_nano import Scanner

scanner = Scanner()
results = scanner.scan_file("config.yml")
```

### Rust

```rust
let scanner = argus_nano::Scanner::new(Default::default())?;
let results = scanner.scan_file("config.yml")?;
```

### CLI

```bash
argus-nano scan ./my-repo
```

## Performance

Tested against a 1,180-file corpus (480 real secrets across 37 providers, 700 benign files).

| Metric | Value |
|--------|-------|
| Precision | 100.0% |
| Recall | 99.8% |
| F1 Score | 99.9% |
| False Positive Rate | 0.0% |
| Inference Speed | 11.0s / 1000 files |
| Model Size (quantized) | ~125MB |

## Supported Providers

See [patterns/providers/](https://github.com/arc-commander/argus-nano/tree/main/patterns/providers) for the full list.

## Limitations

- Optimized for standard provider key formats; custom/proprietary formats may require adding patterns
- Binary classification only (v1); multi-class planned for v2
- Designed for source code context; may be less accurate on log files or unstructured text

## License

Apache 2.0

## Made by the [Arc Commander](https://github.com/arc-commander) team