/aegisops-ai, Autonomous Governance Orchestrator

AegisOps-AI is described by its upstream as a governance pipeline that integrates advanced AI reasoning directly into the SDLC. It acts as an intelligent gatekeeper for systems-level security, cloud infrastructure costs, and Kubernetes compliance.

Goal

To automate high-stakes security and financial audits by:

1. Identifying logic-based vulnerabilities (UAF, Stale State) in Linux Kernel patches.
2. Detecting massive "Silent Disaster" cost drifts in Terraform plans.
3. Translating natural language security intent into hardened K8s manifests.

When to Use

• Kernel Patch Review: Auditing raw C-based Git diffs for memory safety.
• Pre-Apply IaC Audit: Analyzing terraform plan outputs to prevent bill spikes.
• Cluster Hardening: Generating "Least Privilege" securityContexts for deployments.
• CI/CD Quality Gating: Blocking non-compliant merges via GitHub Actions.

When Not to Use

• Web App Logic: Do not use for standard web vulnerabilities (XSS, SQLi); use dedicated SAST scanners.
• Non-C Memory Analysis: The patch analyzer is optimized for C-logic; avoid using it for high-level languages like Python or JS.
• Direct Resource Mutation: This is an auditor, not a deployment tool. It does not execute terraform apply or kubectl apply.
• Post-Mortem Analysis: For analyzing why a previous AI session failed, use /analyze-project instead.

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🤖 Generative AI Integration

AegisOps-AI leverages the Google GenAI SDK to implement a "Reasoning Path" for autonomous security and financial audits: