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

Описание и применение

ForgeGuard автоматизирует аудит кода, моделирование угроз STRIDE и исправление уязвимостей, сокращая время работы до под 10 мс на файл и обеспечивая нулевые сбои сборки.

Задача

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

Результат

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.

Рабочий процесс

• 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

Доказательства

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

Источник

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

Источник

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.

Источник