vuln-seeker
CLI code security scanner — detects vulnerabilities with 25+ regex patterns and optional AI-powered triage, with JSON/Markdown reports and CI mode
Fast, regex-driven code security scanning with JSON/Markdown reports and optional AI-assisted triage.
Why
Security reviews are often delayed because lightweight checks are missing from day-to-day development. vuln-seeker is designed to fill that gap:
- Quick local feedback before code reaches CI.
- Broad language coverage via text pattern matching (not parser-dependent).
- Actionable output with severity, location, rule, and remediation advice.
- CI-friendly behavior with non-zero exits for policy enforcement.
- Optional AI analysis to prioritize likely true positives and remediation order.
Installation
Requirements
- Python
3.10+
Install from source
git clone https://github.com/vikasudasi/vuln-seeker
cd vuln-seeker
pip install -e .
Verify installation
vuln-seeker --version
vuln-seeker --help
Usage
Basic scan
vuln-seeker .
Scan a specific path with all patterns
vuln-seeker ./src --pattern-set all
CI mode (fail on high severity findings)
vuln-seeker . --ci
AI-assisted analysis
export VULN_SEEKER_API_KEY="your_api_key"
vuln-seeker . --ai gpt-4.1
CLI Reference
| Option | Type / Values | Default | Description |
|---|---|---|---|
path | positional path | . | Directory to scan recursively. |
--ai MODEL | string | none | Enables AI analysis and sets model name. |
--ci | flag | off | Exit with code 1 if HIGH findings are present. |
--ignore PATTERN | repeatable glob | [] | Ignore file/dir patterns. |
--output | json, markdown, both | both | Report format(s). |
--pattern-set | standard, extended, all | standard | Vulnerability rule coverage. |
Detection Categories
- SQL injection
- XSS
- Hardcoded secrets
- Command injection
- Path traversal
- Insecure deserialization
- Sensitive data exposure
Output Formats
Terminal: Color-coded findings with severity labels, file paths, descriptions, and fix suggestions.
JSON: Machine-readable report with tool, version, scanned_files, total_findings, severity_counts, and findings array.
Markdown: Human-readable report with scan metadata, severity summary, and detailed finding entries.
License
MIT