chore(sync): [skip actions] synced file(s) with jbcom/control-center

[jbdevprimary]

synced local file(s) with jbcom/control-center.

Changed files

• synced local directory ./ with remote directory sync-files/always-sync/global/

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This PR was created automatically by the repo-file-sync-action workflow run #20807422644

[jbdevprimary]

📦 Tracking: #62

[jbdevprimary]

🤖 AI Code Review

Summary

Adds 4 new GitHub workflows (autoheal, delegator, review, triage) to automate CI failure resolution, PR conflict handling, code reviews, and repository health management using AI tools.

Issues Found

🔴 Security: Docker images run with host workspace volume mount and write permissions without explicit image digest pinning
🔴 Security: Sensitive tokens (GITHUB_TOKEN, OLLAMA_API_KEY) passed to external Docker containers
🟠 Performance: Rebase-all-PRs job runs sequentially on every main push, could timeout on large repos
🟠 Reliability: No rate limiting or error handling for GitHub API calls in loops
🟡 Maintainability: Hardcoded Docker image tag :latest without version pinning

Suggestions

1. Pin Docker images to specific digests for security
2. Add rate limiting and retry logic for GitHub API calls
3. Consider parallelizing PR rebasing with matrix strategy
4. Add input validation for workflow parameters
5. Implement proper error handling and logging
6. Add workflow-level timeouts to prevent hanging jobs
7. Use GitHub Actions cache for Docker images to improve performance

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_{Reviewed by Ecosystem Reviewer using glm-4.6:cloud}

[jbdevprimary]

🤖 AI Code Review

Summary

Adds 4 new GitHub Actions workflows (autoheal.yml, delegator.yml, review.yml, triage.yml) that automate CI failure resolution, PR reviews, issue triage, and conflict resolution using Docker containers with AI capabilities.

Issues Found

🔴 Security: Exposing OLLAMA_API_KEY and ANTHROPIC_API_KEY in workflow logs via run steps without proper masking

🔴 Security: Using docker run with host workspace volume mount poses security risks - container can modify host files

🟠 Performance: Running Docker containers without caching will significantly slow down workflows

🟠 Reliability: No error handling or retry logic for Docker operations

🟡 Maintainability: Hardcoded Docker image tag :latest can cause unpredictable behavior

🟡 Security: Broad permissions (contents: write, actions: write) may exceed requirements

Suggestions

1. Add --add-host=github.com:192.30.255.113 to Docker commands for reliable API access
2. Use specific image version tags instead of :latest
3. Add continue-on-error: true and retry logic for Docker operations
4. Mask sensitive outputs using ::add-mask:: before echoing
5. Consider using GitHub-hosted runners' built-in tools instead of Docker where possible
6. Add timeout strategies for long-running operations
7. Implement proper secret handling with GH_TOKEN instead of GITHUB_TOKEN for gh CLI
8. Add workflow-level concurrency controls to prevent race conditions

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_{Reviewed by Ecosystem Reviewer using glm-4.6:cloud}

[jbdevprimary]

🤖 AI Code Review

Summary

New GitHub workflows for automated repository management:

• autoheal.yml: AI-powered CI failure resolution and merge conflict handling
• delegator.yml: Routes @claude commands to Claude agent
• review.yml: Automated PR reviews using AI
• triage.yml: Comprehensive issue/PR triage with automatic rebasing on main push

Issues Found

🔴 Security: Exposing GITHUB_TOKEN to untrusted Docker containers

• All workflows pass GITHUB_TOKEN to external Docker images without validation
• Risk of token exfiltration through malicious container images

🔴 Security: Using mutable Docker tags

• jbcom/control-center:latest can be updated with malicious code
• Should use immutable tags or SHA digests

🟠 Security: Broad permissions

• contents: write + actions: write is excessive for some operations
• Autoheal could potentially modify any workflow file

🟠 Performance: No rate limiting

• Bulk operations on all open PRs could hit API limits
• No pagination handling for large repositories

🟡 Reliability: Missing error handling

• Docker commands can fail silently
• No retry logic for network operations

Suggestions

1. Use GitHub-hosted runners or verified actions instead of arbitrary Docker images
2. Pin container digests: jbcom/control-center@sha256:...
3. Implement principle of least privilege for permissions
4. Add rate limiting and pagination for bulk PR operations
5. Validate container images before use (cosign verification)
6. Add timeout and retry logic for external service calls
7. Consider using GitHub's built-in merge conflict detection instead of custom tools
8. Add audit logging for all automated changes

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_{Reviewed by Ecosystem Reviewer using glm-4.6:cloud}

[jbdevprimary]

Claude encountered an error —— View job

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I'll analyze this and get back to you.

[jbdevprimary]

🤖 AI Code Review

Summary

New GitHub workflows for automated repository management:

• autoheal.yml: AI-powered CI failure resolution and merge conflict handling
• delegator.yml: Routes @claude commands to AI agents
• review.yml: Automated PR reviews using AI
• triage.yml: Comprehensive issue/PR triage with automatic rebasing on main push

Issues Found

🔴 Security: Hardcoded Docker image jbcom/control-center:latest without digest pinning
🔴 Security: Broad permissions (contents: write, actions: write) may exceed requirements
🟠 Performance: No rate limiting for API calls could trigger GitHub abuse detection
🟠 Reliability: Missing error handling for Docker command failures
🟡 Maintainability: Complex workflow logic embedded in shell scripts

Suggestions

1. Pin Docker images with SHA256 digests
2. Implement retry logic for API calls
3. Add workflow-level timeout (e.g., timeout-minutes: 30)
4. Use GitHub Actions' built-in functions instead of shell parsing where possible
5. Add input validation for workflow_dispatch parameters
6. Consider splitting large workflows into smaller, focused jobs

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_{Reviewed by Ecosystem Reviewer using glm-4.6:cloud}

[jbdevprimary]

🔧 CI Fix Suggestion

Branch: repo-sync/control-center/default

(Auto-fix analysis unavailable. Please review the CI logs manually.)

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_{🤖 Generated by Ecosystem Fixer using Ollama GLM 4.6}

[jbdevprimary]

Claude encountered an error —— View job

---

I'll analyze this and get back to you.

[jbdevprimary]

🤖 AI Code Review

Summary

Adds 4 new GitHub Actions workflows (autoheal, delegator, review, triage) that automate CI failure resolution, PR reviews, issue triage, and conflict resolution using AI tools. These consolidate and replace multiple existing workflows.

Issues Found

🔴 Critical Security:

• Docker images run with host workspace volume mount (-v "${{ github.workspace }}:/workspace") without proper isolation
• Secrets passed directly to Docker containers without sanitization
• No input validation for repository parameter (could allow path traversal)

🟠 High Risk:

• Auto-rebase on every main push could cause cascading failures
• No rate limiting on AI API calls could incur high costs
• Workflow permissions too broad (contents: write for all workflows)

🟡 Medium:

• No error handling for Docker container failures
• Missing concurrency controls could cause race conditions
• Hardcoded Docker image tag :latest could cause unexpected behavior

⚪ Low:

• Inconsistent environment variable naming (OLLAMA_HOST vs OLLAMA_API_KEY)
• Some placeholder comments ("not yet implemented")

Suggestions

1. Security: Use GitHub's built-in actions/checkout instead of direct Docker volume mounts
2. Validation: Add input validation for repository format (owner/repo)
3. Rate Limiting: Implement API call throttling and cost controls
4. Concurrency: Add concurrency groups to prevent duplicate runs
5. Error Handling: Wrap Docker calls in try/catch blocks with proper logging
6. Image Pinning: Use specific image tags instead of :latest
7. Permissions: Scope down permissions per workflow (e.g., review only needs pull-requests: write)
8. Testing: Add workflow test runs before production deployment

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_{Reviewed by Ecosystem Reviewer using glm-4.6:cloud}

[sonarqubecloud]

Quality Gate failed

Failed conditions
E Security Rating on New Code (required ≥ A)

See analysis details on SonarQube Cloud

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