ForgeGuard: Building an Autonomous AI DevSecOps Side Hustle with Open-Weight Models

Description and use

ForgeGuard automates code audit, STRIDE threat modeling, and vulnerability patching, reducing audit time to sub‑10 ms per file with zero build failures.

Problem

Freelance DevSecOps consultants spend 10+ hours manually auditing repositories for vulnerabilities, threat modeling, and patching.

Outcome

ForgeGuard reduces audit time from 10+ hours to sub‑10 ms per file, provides automated STRIDE threat models, and generates AST‑verified patches with zero broken builds, enabling high‑margin security consulting.

Workflow

• Clone the ForgeGuard repo
• Run a high‑speed SAST scan: python -m forgeguard.cli scan <repo>
• Generate a full executive audit with STRIDE threat model: python -m forgeguard.cli audit <repo> --json audit_report.json
• Preview autonomous patches: python -m forgeguard.cli patch <repo> --dry-run
• Launch the interactive cyberpunk dashboard: python -m forgeguard.cli serve <repo> --port 8899

Evidence

ForgeGuard turns this into a high-margin, automated workflow: Scans entire Python codebases via recursive AST visitors in under 10ms.

Source

Synthesizes automated, AST-verified remediation patches powered by open-weight AI with guaranteed zero broken builds and 1-click snapshot rollbacks.

Source

Clients realistically pay $500 to $2,000 per audit before product launches or funding rounds to guarantee they aren't leaking hardcoded secrets, exposing SQL/command injection flaws, or violating OWASP Top 10 standards.

Source