---
name: aegisops-ai-0aa841e2906e
description: "Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance."
risk: safe
source: community
author: Champbreed
date_added: "2026-03-24"
---

# /aegisops-ai — Autonomous Governance Orchestrator

AegisOps-AI is a professional-grade "Living 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.

---
## 🤖 Generative AI Integration

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

* **Neural Patch Analysis:** Performs semantic code reviews of Linux Kernel patches, moving beyond simple pattern matching to understand complex memory state logic.
* **Intelligent Cost Synthesis:** Processes raw Terraform plan diffs through a financial reasoning model to detect high-risk resource escalations and "silent" fiscal drifts.
* **Natural Language Policy Mapping:** Translates human security intent into syntactically correct, hardened Kubernetes `securityContext` configurations.

## 🧭 Core Modules

### 1. 🐧 Kernel Patch Reviewer (`patch_analyzer.py`)

* **Problem:** Manual review of Linux Kernel memory safety is time-consuming and prone to human error.
* **Solution:** Gemini 3 performs a "Deep Reasoning" audit on raw Git diffs to detect critical memory corruption vulnerabilities (UAF, Stale State) in seconds.
* **Key Output:** `analysis_results.json`

### 2. 💰 FinOps & Cloud Auditor (`cost_auditor.py`)

* **Problem:** Infrastructure-as-Code (IaC) changes can lead to accidental "Silent Disasters" and massive cloud bill spikes.
* **Solution:** Analyzes `terraform plan` output to identify cost anomalies—such as accidental upgrades from `t3.micro` to high-performance GPU instances.
* **Key Output:** `infrastructure_audit_report.json`

### 3. ☸️ K8s Policy Hardener (`k8s_policy_generator.py`)

* **Problem:** Implementing "Least Privilege" security contexts in Kubernetes is complex and often neglected.
* **Solution:** Translates natural language security requirements into production-ready, hardened YAML manifests (Read-only root FS, Non-root enforcement, etc.).
* **Key Output:** `hardened_deployment.yaml`

## 🛠️ Setup & Environment

### 1. Clone the Repository

```bash
git clone https://github.com/Champbreed/AegisOps-AI.git
cd AegisOps-AI
```
## 2. Setup

```bash
python3 -m venv venv
source venv/bin/activate
pip install google-genai python-dotenv
```
### 3. API Configuration

Create a `.env` file in the root directory to securely 
store your credentials:

```bash
echo "GEMINI_API_KEY='your_api_key_here'" > .env
```
## 🏁 Operational Dashboard

To execute the full suite of agents in sequence and generate all security reports:

```bash
python3 main.py
```
### Pattern: Over-Privileged Container

* **Indicators:** `allowPrivilegeEscalation: true` or root user execution.
* **Investigation:** Pass security intent (e.g., "non-root only") to the K8s Hardener module.

---

## 💡 Best Practices

* **Context is King:** Provide at least 5 lines of context around Git diffs for more accurate neural reasoning.
* **Continuous Gating:** Run the FinOps auditor before every infrastructure change, not after.
* **Manual Sign-off:** Use AI findings as a high-fidelity signal, but maintain human-in-the-loop for kernel-level merges.

---

## 🔒 Security & Safety Notes

* **Key Management:** Use CI/CD secrets for `GEMINI_API_KEY` in production.
* **Least Privilege:** Test "Hardened" manifests in staging first to ensure no functional regressions.

## Links

+ - **Repository**: https://github.com/Champbreed/AegisOps-AI
+ - **Documentation**: https://github.com/Champbreed/AegisOps-AI#readme

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.


---
Source attribution: Champbreed
Original project: https://github.com/Sansar35/claude-agent/blob/d046d088ce5a79a083f0abc0fe1b7ded73bc5b1f/claude-config/skills/antigravity/aegisops-ai/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Claude Agent Team contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: Champbreed
Original project: https://github.com/Sansar35/claude-agent/blob/d046d088ce5a79a083f0abc0fe1b7ded73bc5b1f/claude-config/skills/antigravity/aegisops-ai/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering, Product Management
Roles: DevOps / SRE, ML / AI Engineer, Backend Developer, Product Manager, Growth Product Manager
Specialties: DevOps, Backend, API
Tools: Google Gemini, Terraform, Kubernetes
Country applicability: Country not specified
Classification basis: Source category, role and specialization labels
Instruction SHA-256: 9202d80908d3aaef9bb94058f1b2f161e3b2017e26224fd339e67af8762a0a70