Shadowscan: Local AI Agent Data Exposure Scanner

Shadowscan is a local security tool designed to scan a machine for potential AI data exposure. It operates without making any network calls, ensuring that all findings remain local and private. The tool identifies various categories of exposed secrets, including API keys in environment variables, unencrypted SSH private keys, and AWS credentials. It also checks for secrets in `.env` files, clipboard content, and git commit history.

The tool provides explanations and fix instructions for each finding, enabling users to address the identified vulnerabilities. Shadowscan's stateless design ensures that each run is independent and does not store any scan history. The tool is designed to be easily integrated into development workflows, with options to skip certain scans for faster execution and disable color output for cleaner reports.

Shadowscan represents a proactive approach to AI security, empowering users to identify and mitigate potential data exposure risks before they can be exploited. By focusing on local scans and providing clear, actionable insights, Shadowscan helps developers and security professionals maintain a secure environment for AI development and deployment. As AI agents become more prevalent, tools like Shadowscan will play an increasingly important role in protecting sensitive data.

_Context: This intelligence report was compiled by the DailyAIWire Strategy Engine. Verified for Art. 50 Compliance._