104 lines
3.9 KiB
Markdown
104 lines
3.9 KiB
Markdown
# agentguard-ci
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A DevSecOps Argo Workflows pipeline designed to protect against AI coding agent hallucinations, supply chain attacks, and security misconfigurations in a homelab or solo-developer environment.
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## Problem
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AI coding agents are highly productive junior developers, but they lack intrinsic context. They can hallucinate credentials, introduce insecure logic, or pull in risky dependencies.
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This project adds a reusable security gate in front of deployment by cloning a repository into an Argo workflow, running multiple scanners in parallel, uploading supported results to DefectDojo and object storage, and enforcing a CVSS-based policy threshold.
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## What the pipeline does
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- Runs TruffleHog for secret scanning.
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- Runs Semgrep for first-party code scanning.
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- Runs KICS for infrastructure misconfiguration scanning.
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- Runs Socket.dev for dependency risk scanning.
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- Runs Syft and Grype for SBOM generation and vulnerability scanning.
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- Runs Pulumi CrossGuard for policy-pack validation.
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- Uploads supported reports to DefectDojo when enabled.
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- Uploads raw reports to S3-compatible storage when enabled.
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- Fails the workflow when findings meet or exceed the configured CVSS threshold.
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## Prerequisites
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Install these separately in your cluster before using this chart:
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- Argo Workflows
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- Infisical Kubernetes Operator, if you want this chart to sync secrets automatically
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- DefectDojo, if you want report ingestion enabled
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- MinIO or another S3-compatible store, if you want raw report uploads enabled
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You will also need the corresponding credentials for Socket.dev, Pulumi, AWS or MinIO, and DefectDojo.
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## Validation workflow
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For fast validation while wiring up infrastructure, use these tools together:
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- `helm lint ./helm`
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- `helm template agentguard-ci ./helm`
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- `helm template agentguard-ci ./helm | kubectl apply --dry-run=client -f -`
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- `helm template agentguard-ci ./helm | kubectl apply --dry-run=server -f -`
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- `argo lint rendered.yaml`
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Notes:
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- `helm lint` catches Helm chart problems.
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- `kubectl --dry-run=client` catches basic Kubernetes schema issues without talking to the cluster.
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- `kubectl --dry-run=server` is better once the cluster already has the Argo and Infisical CRDs installed.
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- `argo lint` is the most useful Argo-specific check once you have the Argo CLI installed.
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## Installation
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### 1. Build the tools image
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The workflow uses custom TypeScript utilities for policy enforcement and DefectDojo uploads.
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```bash
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cd tools
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docker build -t your-registry/agentguard-tools:latest .
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docker push your-registry/agentguard-tools:latest
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```
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### 2. Configure values
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Start from [`helm/values.yaml`](helm/values.yaml) and set at least:
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```yaml
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pipeline:
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toolsImage:
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repository: your-registry/agentguard-tools
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tag: latest
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infisical:
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enabled: true
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workspaceSlug: your-workspace-id
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projectSlug: your-project-id
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storage:
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enabled: false
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defectdojo:
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enabled: false
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```
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Keep `storage.enabled` and `defectdojo.enabled` disabled until those services are actually installed and reachable. Keep `infisical.enabled` disabled until the operator is installed and your project identifiers are ready.
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If you do not use Infisical, create the `amp-security-pipeline-secrets` secret yourself before running the workflow. For storage uploads, the secret should contain `S3_ACCESS_KEY_ID` and `S3_SECRET_ACCESS_KEY`.
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### 3. Deploy the chart
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```bash
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helm upgrade --install agentguard-ci ./helm -n argo
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```
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## DefectDojo integration
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DefectDojo is not installed by this repository.
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You install DefectDojo separately, then enable this chart's upload step. When enabled, the workflow uploads supported reports into DefectDojo through the API using the custom uploader in [`tools/src/upload-defectdojo.ts`](tools/src/upload-defectdojo.ts).
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## Secret management
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When `infisical.enabled` is `true`, this chart creates an `InfisicalSecret` that syncs the runtime credentials needed by the workflow into the `amp-security-pipeline-secrets` Kubernetes secret.
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