bambu-studio-ai
Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pi...
secrets scan
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install aronchick/expanso-secrets-scanInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Detect hardcoded secrets (API keys, tokens, passwords) in text or code
expanso-edge binary in PATH)clawhub install expanso-edge
# Run standalone
echo '<input>' | expanso-edge run pipeline-cli.yaml
# Start as MCP server
expanso-edge run pipeline-mcp.yaml
expanso-cli job deploy https://skills.expanso.io/secrets-scan/pipeline-cli.yaml
| File | Purpose |
|---|---|
skill.yaml |
Skill metadata (inputs, outputs, credentials) |
pipeline-cli.yaml |
Standalone CLI pipeline |
pipeline-mcp.yaml |
MCP server pipeline |
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
Detect hardcoded secrets (API keys, tokens, passwords) in text or code.
Scan code, configs, and logs for accidentally committed credentials. Essential for:
export OPENAI_API_KEY=sk-...
# Scan a file
cat config.yaml | expanso-edge run pipeline-cli.yaml
# Scan before committing
git diff --cached | expanso-edge run pipeline-cli.yaml
# Scan entire codebase
find . -name "*.py" -exec cat {} \; | expanso-edge run pipeline-cli.yaml
PORT=8080 expanso-edge run pipeline-mcp.yaml &
curl -X POST http://localhost:8080/scan \
-H "Content-Type: application/json" \
-d '{
"text": "const API_KEY = \"sk-abc123def456\";",
"types": ["api_key", "token"]
}'
| Variable | Required | Default | Description |
|---|---|---|---|
OPENAI_API_KEY |
Yes | - | OpenAI API key |
SECRET_TYPES |
No | all | Comma-separated secret types |
PORT |
No | 8080 | HTTP port for MCP mode |
| Type | Examples |
|---|---|
api_key |
sk-xxx, AKIA..., api_key=... |
token |
ghp_xxx, Bearer xxx |
password |
password=xxx, pwd:xxx |
private_key |
-----BEGIN RSA PRIVATE KEY----- |
aws_key |
aws-xxx, aws_secret_access_key |
github_token |
ghp_xxx, gho_xxx |
slack_token |
slack-xxx |
openai_key |
sk-xxx |
const config = {
apiKey: "sk-proj-abc123def456ghi789",
database: {
password: "supersecret123!"
},
aws: {
accessKeyId: "YOUR_AWS_ACCESS_KEY_ID",
secretAccessKey: "YOUR_AWS_SECRET_KEY"
}
};
{
"findings": [
{
"type": "openai_key",
"value": "sk-p...789",
"line": 2,
"severity": "high",
"context": "OpenAI API key in apiKey field"
},
{
"type": "password",
"value": "supe...123!",
"li...
# secrets-scan Detect hardcoded secrets (API keys, tokens, passwords) in text or code ## Requirements - Expanso Edge installed (`expanso-edge` binary in PATH) - Install via: `clawhub install expanso-edge` ## Usage ### CLI Pipeline ```bash # Run standalone echo '<input>' | expanso-edge run pipeline-cli.yaml ``` ### MCP Pipeline ```bash # Start as MCP server expanso-edge run pipeline-mcp.yaml ``` ### Deploy to Expanso Cloud ```bash expanso-cli job deploy https://skills.expanso.io/secrets-scan/pipeline-cli.yaml ``` ## Files | File | Purpose | |------|---------| | `skill.yaml` | Skill metadata (inputs, outputs, credentials) | | `pipeline-cli.yaml` | Standalone CLI pipeline | | `pipeline-mcp.yaml` | MCP server pipeline |
# secrets-scan
> Detect hardcoded secrets (API keys, tokens, passwords) in text or code.
Scan code, configs, and logs for accidentally committed credentials. Essential for:
- Pre-commit hooks
- CI/CD pipelines
- Code review automation
- Security audits
## Quick Start
### CLI Mode
```bash
export OPENAI_API_KEY=sk-...
# Scan a file
cat config.yaml | expanso-edge run pipeline-cli.yaml
# Scan before committing
git diff --cached | expanso-edge run pipeline-cli.yaml
# Scan entire codebase
find . -name "*.py" -exec cat {} \; | expanso-edge run pipeline-cli.yaml
```
### MCP Mode
```bash
PORT=8080 expanso-edge run pipeline-mcp.yaml &
curl -X POST http://localhost:8080/scan \
-H "Content-Type: application/json" \
-d '{
"text": "const API_KEY = \"sk-abc123def456\";",
"types": ["api_key", "token"]
}'
```
## Configuration
| Variable | Required | Default | Description |
|----------|----------|---------|-------------|
| `OPENAI_API_KEY` | Yes | - | OpenAI API key |
| `SECRET_TYPES` | No | all | Comma-separated secret types |
| `PORT` | No | 8080 | HTTP port for MCP mode |
## Secret Types
| Type | Examples |
|------|----------|
| `api_key` | sk-xxx, AKIA..., api_key=... |
| `token` | ghp_xxx, Bearer xxx |
| `password` | password=xxx, pwd:xxx |
| `private_key` | -----BEGIN RSA PRIVATE KEY----- |
| `aws_key` | aws-xxx, aws_secret_access_key |
| `github_token` | ghp_xxx, gho_xxx |
| `slack_token` | slack-xxx |
| `openai_key` | sk-xxx |
## Example Output
### Input
```javascript
const config = {
apiKey: "sk-proj-abc123def456ghi789",
database: {
password: "supersecret123!"
},
aws: {
accessKeyId: "YOUR_AWS_ACCESS_KEY_ID",
secretAccessKey: "YOUR_AWS_SECRET_KEY"
}
};
```
### Output
```json
{
"findings": [
{
"type": "openai_key",
"value": "sk-p...789",
"line": 2,
"severity": "high",
"context": "OpenAI API key in apiKey field"
},
{
"type": "password",
"value": "supe...123!",
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