OCI CIS AI Agent

Oracle Cloud Infrastructure — CIS Foundations Benchmark 3.0 — AI-Powered Compliance Platform

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Overview

OCI CIS AI Agent is a self-hosted web application that automates CIS Oracle Cloud Infrastructure Foundations Benchmark 3.0 compliance checks, powered by OCI Generative AI for intelligent analysis and an MCP (Model Context Protocol) server architecture for extensible task execution.

The platform combines security compliance scanning, AI-powered chat with RAG (Retrieval-Augmented Generation), infrastructure exploration, and vector-based knowledge storage into a single, containerized solution with an Oracle Dark Premium theme (light/dark modes), KPI dashboard with compliance gauge, and Chart.js visualizations.

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Features

🤖 AI Chat Agent with RAG + MCP Tool Use

• OCI Generative AI integration via official SDK (oci.generative_ai_inference)
• RAG (Retrieval-Augmented Generation): automatically queries ADB vector store for relevant context before generating responses
• MCP Tool Use (Function Calling): GenAI models can call tools from registered MCP servers during chat — supports both Cohere and Generic (OpenAI-style) function calling formats with automatic tool execution loop (max 5 iterations)
• Chat Memory Compaction: automatic summarization of older messages when conversation exceeds ~6000 tokens — keeps 20 recent messages (10 interactions) intact and generates an LLM-based summary of older context
• Chat Sidebar: collapsible right-side panel with model parameters (temperature, max_tokens, top_p, top_k, penalties) for quick adjustment during conversation
• Multimodal Chat: upload images (PNG/JPG/GIF/WebP), PDFs, and text files directly in the chat for AI analysis — supports up to 5 files per message via OCI GenAI ImageContent and DocumentContent
• Async Background Processing: chat requests return immediately, GenAI + MCP tools process in background via dedicated thread pool (16 threads), frontend polls for results — eliminates 504 timeouts on long-running scans
• Thinking Indicator: button disables and shows spinner + "Pensando..." while waiting for GenAI response, with message timestamps
• 15 chat models + 3 embedding models across 5 providers: Meta (Llama 4), Google (Gemini 2.5), OpenAI (GPT-5.2/5.1/5 Mini/4.1/4o, o3/o4-mini), xAI (Grok 4/3)
• OCID-based model resolution: catalog maps model IDs to OCI resource IDs per region for reliable API calls
• 16 OCI regions supported with auto-generated endpoints
• Full parameter control: temperature, max_tokens, top_p, top_k, frequency/presence penalty
• Toggle MCP tools on/off per chat session
• Conversation history with session management
• On-Demand and Dedicated serving modes

🏗️ Terraform Agent (IaC)

• AI-powered Terraform code generation for OCI infrastructure provisioning
• Dedicated chat interface with OCI Terraform provider context
• Workspace management: create, plan, apply, destroy Terraform workspaces
• Compartment-aware: browse and select target compartment for provisioning, with existing OCI resources injected as context
• Plan/Apply/Destroy lifecycle: full Terraform workflow with real-time output tracking
• File management: view generated .tf files, copy, download individually or as bundle
• Confirmation modal: type "DESTROY" to confirm resource destruction
• Inline file editor: click any generated .tf file to edit in-place with monospace editor, Tab support, and save — auto-syncs with workspace code
• Split-panel terminal: real-time Plan/Apply/Destroy output in a dark terminal panel alongside files/plan/resources (always visible)
• Multi-file generation: AI generates separate .tf files via // filename: markers (main.tf, variables.tf, outputs.tf, etc.)
• Smart file correction: when fixing errors, model generates only changed files — frontend merges with existing workspace, preserving untouched files. Existing files, plan output, and apply errors are injected as context automatically
• 14-point validation checklist: system prompt enforces cross-references, CIDRs, security lists, route tables, DRG attachments, RPC peering, HCL block syntax, resource type validation, and variable declarations
• Auto-split pipeline (3 layers): frontend + backend auto-split of monolithic HCL files into categorized files (networking.tf, compute.tf, etc.) + backend deduplication to prevent duplicate resource errors
• HCL syntax fix: automatic expansion of single-line blocks with multiple arguments into valid multi-line HCL format
• Resource type validation: SQLite-based validation of ~937 OCI resource types with difflib.get_close_matches suggestions for invalid types — warnings appended automatically to model responses
• Chat history: ChatGPT-style session history with rename/delete, shared between Chat Agent and Terraform Agent
• Resizable split view: chat on top (50%), files/plan/resources + terminal on bottom (50%) with drag-to-resize
• Terraform CLI installed in container (v1.7.5)
• Terraform Resource Reference: auto-generated OCI provider resource catalog (~937 resources) injected into system prompt — built from terraform providers schema -json at container startup, stored in SQLite, refreshable via menu button
• Official Resource Docs Injection: on-demand fetch of Example Usage + Argument Reference from the official OCI Terraform provider docs (registry.terraform.io) — cached in SQLite, injected into model context based on detected resource types
• Smart variable resolution: auto-generates terraform.tfvars by scanning declared variables and mapping them to OCI config values (tenancy_ocid, user_ocid, fingerprint, compartment_id) — region is never forced, respecting variable defaults
• Multi-region provider management: auto-detects provider aliases and region variables in generated code, generates provider.tf with credentials and correct region references (var.region instead of hardcoded values)
• System prompt sync: Terraform system prompt in code is automatically synced to DB on every restart — single source of truth
• Compact system prompt optimized for OCI Terraform provider best practices (100K max_tokens)

⚡ OCI Resource Actions

• Start/Stop Compute Instances directly from OCI Account Explorer with one click
• Start/Stop Autonomous Databases from Explorer with confirmation prompt
• Update Network Access: add your IP to ADB ACL (whitelisted_ips) directly from Explorer
• ACL display: view current whitelisted IPs for Autonomous Databases in Explorer cards
• Auto-refresh: resource state updates automatically after Start/Stop actions (polling)
• Lifecycle state badges (RUNNING/STOPPED/AVAILABLE) with color indicators
• Actions audited in the audit log

🔍 OCI Account Explorer

• Tree-view navigation with resizable side panel and drag handle
• 40+ resource types across 8 categories:
  • IAM: Users, Groups, Policies, Dynamic Groups
  • Compute: Instances, Instance Pools, Container Instances
  • Networking: VCNs, Subnets, Security Lists, NSGs, Route Tables, NAT/Internet/Service Gateways, Public IPs, Network Firewalls, Firewall Policies
  • Storage: Block Volumes, Boot Volumes, Object Storage Buckets, File Systems, Mount Targets
  • Database: Autonomous Databases, DB Systems, MySQL DB Systems
  • Kubernetes: OKE Clusters
  • Observability: Alarms, Log Groups, Events Rules, Notification Topics
  • Security: Vaults, DNS Zones, API Gateways
• Multi-region support: select and filter by multiple OCI regions with checkbox selection
• Compartment tree: hierarchical compartment browser with full OCID visibility
• Security list detail: view ingress/egress rules directly in the explorer
• Select which OCI connection to explore
• Real-time API calls via OCI Python SDK

📊 CIS Compliance Reports (Oracle Official Engine)

• Powered by Oracle's official cis_reports.py (6660 lines, 48 CIS + 11 OBP checks)
• Granular execution parameters: CIS Level (1/2), OCI Best Practices, Raw Data, OCID Redaction
  • Level 1: Essential security controls that can be implemented with minimal impact on operations. Recommended as baseline for all organizations.
  • Level 2: Advanced security controls that may restrict functionality or require more effort to implement. Recommended for high-security environments.
• Multiple output formats: HTML summary, CSV per section/finding, JSON summary, optional XLSX
• Report history: full execution history with status, tenancy filter, and download actions (HTML/JSON) in the Reports tab
• File browser: dedicated Downloads tab with expandable cards per completed report, files grouped by category (Summary, CIS Findings, OBP, Raw Data, etc.)
• Region filtering with multi-select
• Real-time progress tracking with phase-based progress bar
• CIS Engine auto-update: check for new versions of cis_reports.py from Oracle's GitHub repository and update with one click (admin only). Custom patches are automatically reapplied after update

🛡️ Built-in CIS MCP Server (Granular Per-Section)

• Auto-registered CIS Compliance Scanner MCP server — available out of the box
• 12 granular tools instead of monolithic full-tenancy scan:
  • cis_scan_iam — IAM checks (CIS 1.1–1.17): users, policies, groups, MFA, API keys
  • cis_scan_networking — Network checks (CIS 2.1–2.8): security lists, NSGs, VCNs
  • cis_scan_compute — Compute checks (CIS 3.1–3.3): instance metadata, monitoring
  • cis_scan_logging_monitoring — Logging/Monitoring checks (CIS 4.1–4.17): audit, alarms, events
  • cis_scan_storage — Storage checks (CIS 5.1–5.3): buckets, block volumes, file systems
  • cis_scan_asset_management — Asset checks (CIS 6.1–6.2): compartments, tagging
  • cis_list_configs / cis_list_checks — list available OCI configs and CIS checks
  • cis_get_check / cis_get_remediation — detailed findings and remediation guidance
  • cis_get_scan_status / cis_invalidate_cache — session status and cache management
• Per-section data collection: each scan tool collects only the OCI data needed for that section, avoiding unnecessary API calls
• Region-specific scanning: all scan tools accept optional regions parameter to target specific OCI regions (e.g., ["us-ashburn-1"]) instead of scanning the entire tenancy
• Session caching: collected data is cached per config+regions scope (2-hour TTL), so subsequent scans on different sections reuse shared prerequisites (compartments, identity domains)
• Compartment filtering: scan results can be filtered by specific compartment, showing only relevant findings
• Collection error tracking: errors during data collection are captured per section and reported to the caller
• Parallelized data collection: base collectors and regional collectors run in parallel thread pools (up to 8 workers), with 30-minute timeout per tool call and 1 automatic retry on failure
• Based on Oracle's official cis_reports.py (6660 lines, 48 CIS + 11 OBP checks)

🔌 MCP Server Registry + Tool Discovery

• Register multiple MCP servers (stdio, SSE, Python module)
• Automatic tool discovery: connect to MCP servers and discover available tools with names, descriptions, and input schemas
• Manual tool definition: add/edit tools with JSON Schema parameter definitions
• Chat Agent integration: discovered tools are automatically available as GenAI function calls during chat
• Upload .py scripts directly to servers
• Link MCP servers to ADB Vector databases as tools
• Activate/deactivate servers
• Select which MCP server to use per report execution

🗄️ Autonomous Database Vector Storage

• Oracle Autonomous Database connection with mTLS Wallet authentication
• python-oracledb Thin mode (no Oracle Client needed)
• Wallet ZIP upload and automatic extraction
• Connection testing with case-insensitive table validation against ADB user_tables
• Multiple vector tables per ADB: register, edit, toggle active/inactive — tables managed inside the edit connection card
• Multi-table RAG search: queries all active tables across all ADB configs, merges results by cosine distance
• Auto-resolve embedding config: automatically uses existing OCI credentials for GenAI embeddings — no separate GenAI config required
• Case-insensitive table matching: supports both uppercase and lowercase table names in Oracle ADB with quoted identifiers

🧬 Embeddings & Knowledge Base

• Dedicated tab for managing vector embeddings and knowledge base
• CIS Recommendations: upload CIS PDF to populate the cisrecom vector table with Oracle Cloud security recommendations
• Knowledge Base (Base de Conhecimento): upload documents (.txt, .pdf, .csv, .json, .md) or import URLs (web pages, PDF links) to populate the engineerknowledgebase vector table — content is automatically extracted, chunked, and vectorized
• URL import: fetches web pages, strips HTML tags/scripts, extracts readable text, and generates embeddings — supports HTML pages and remote PDFs
• Embed CIS Reports: automatically chunk reports by section with tenancy name, regions, and compartments enrichment, with report_date metadata for tracking data freshness
• Purge & re-embed: option to purge old embeddings by tenancy before re-embedding updated reports
• Preview chunks before embedding: review generated sections before creating embeddings
• OCI GenAI Embeddings: uses Cohere Embed models (v4.0, multilingual) via OCI GenAI embed_text API
• Browse and inspect embeddings from the ADB vector store
• 3 embedding models supported: Cohere Embed v4.0, OpenAI Text Embedding 3 Large/Small

📜 Configuration & Chat Logs

• Persistent activity log per configuration tab (OCI, GenAI, ADB, MCP)
• Chat audit logs: all chat interactions (user messages, AI responses, tool calls, errors) logged with session/message ID, severity, and source
• Logs all test, save, upload, report, and ingest operations with severity (success/error/info)
• Inline log panel at the bottom of each config tab with severity filter
• Auto-cleanup of logs older than 30 days
• Admin can view all logs; users see only their own
• API endpoints for listing and clearing logs

🔄 Export / Import Configuration

• Full config export as JSON: OCI credentials (with private keys), GenAI configs, MCP servers, system prompts, app settings, ADB vector configs
• Import from exported JSON with merge-by-ID (skips existing, prevents duplicates)
• Private keys exported as base64 and restored to disk on import
• Enables full environment migration between machines (Mac ↔ Windows ↔ Linux)

🎨 Theme System & UI

• Light/Dark mode toggle in the sidebar footer
• Oracle Dark Premium design: deep dark backgrounds (#0D0F12), dark cards (#1A1D24), Oracle Red accent (#C74634)
• Oracle-branded light mode: warm light backgrounds (original theme)
• Theme preference persisted in localStorage across sessions
• All CSS driven by CSS custom properties — zero hardcoded colors
• SVG icon system: 45+ Lucide-based inline SVG icons replace all emojis for cross-platform consistency (Windows/Mac/Linux)
• KPI Dashboard: compliance score gauge (SVG semicircular arc with gradient), pass/fail/total KPI cards, donut chart (severity distribution), horizontal bar chart (findings by section) — powered by Chart.js 4.4.7
• Animated UI: staggered fade-in for cards/KPIs/tables, smooth theme transitions, hover effects with transforms, shimmer loading states, pulse alerts

✏️ Terraform Prompt Editor

• Inline prompt editor accessible from the Terraform menu (3-dot menu → Editar Prompt)
• Edit the active Terraform system prompt name and content
• Auto-save with debounce (800ms): changes saved to database automatically as you type
• Visual "Salvando..." → "Salvo ✓" indicator

🔐 Security

• JWT authentication with configurable expiry
• TOTP MFA (Google Authenticator / Authy compatible)
• RBAC with 3 roles: Admin, User, Viewer
• Audit logging for all operations
• Encrypted credential storage

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Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Docker Compose                            │
│                                                              │
│  ┌──────────────┐       ┌──────────────────────────────┐    │
│  │  Nginx        │       │  FastAPI Backend              │    │
│  │  (Frontend)   │──────▶│  (Python 3.12)               │    │
│  │  :8080        │       │  :8000                        │    │
│  └──────────────┘       │                                │    │
│                          │  ┌─────────────┐              │    │
│                          │  │ OCI SDK      │──▶ OCI APIs │    │
│                          │  ├─────────────┤              │    │
│                          │  │ GenAI Client │──▶ LLM      │    │
│                          │  ├─────────────┤   (tools)   │    │
│                          │  │ MCP Client   │──▶ MCP Svrs │    │
│                          │  ├─────────────┤   (discover │    │
│                          │  │              │   +execute) │    │
│                          │  ├─────────────┤              │    │
│                          │  │ Terraform    │──▶ Plan /   │    │
│                          │  │              │   Apply    │    │
│                          │  ├─────────────┤              │    │
│                          │  │ oracledb     │──▶ ADB      │    │
│                          │  ├─────────────┤              │    │
│                          │  │ RAG Pipeline │──▶ Embed +  │    │
│                          │  │              │   Search    │    │
│                          │  └─────────────┘              │    │
│                          │                                │    │
│                          │  SQLite (agent.db)             │    │
│                          └──────────────────────────────┘    │
│                                     │                        │
│                              agent-data volume               │
└─────────────────────────────────────────────────────────────┘

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Quick Start

Prerequisites

• Docker and Docker Compose
• OCI API Key pair (private .pem key + fingerprint)
• OCI Tenancy OCID, User OCID, Compartment OCID

1. Clone & Configure

git clone https://github.com/nogueiragustavo/oci-cis-agent.git
cd oci-cis-agent
cp .env.example .env

Edit .env:

APP_SECRET=your-very-long-random-secret-string-here-at-least-64-chars
JWT_EXPIRY_HOURS=12
PORT=8080

2. Build & Run

docker compose up -d --build

3. Access

Open http://localhost:8080

Default credentials:

• Username: admin
• Password: admin123

⚠️ Change the default password immediately after first login.

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Configuration Guide

Step 1 — OCI Credentials

Navigate to OCI Credentials tab and add:

Field	Description
Tenancy Name	Friendly name (e.g., my-company)
OCID Tenancy	ocid1.tenancy.oc1..xxxxx
OCID User	ocid1.user.oc1..xxxxx
Fingerprint	aa:bb:cc:dd:ee:ff:...
Region	sa-saopaulo-1, us-ashburn-1, etc.
Compartment OCID	ocid1.compartment.oc1..xxxxx
Private Key	.pem file
Key Passphrase	(optional) Only required if the private key is encrypted

Click Testar to validate the connection.

Step 2 — GenAI Model

Navigate to GenAI Config tab:

1. Select the OCI Credential created in Step 1 — Region and Compartment OCID are auto-filled from the selected credential
2. Choose a model from the catalog
3. Adjust the GenAI region if needed (auto-populated, must have Generative AI service available)
4. Adjust parameters (temperature, max_tokens, etc.)
5. The endpoint is auto-generated: https://inference.generativeai.{region}.oci.oraclecloud.com

For dedicated endpoints, switch Serving Type to DEDICATED and provide the endpoint ID.

The GenAI connection follows Oracle's official SDK pattern:

# Auth via stored OCI config
config = oci.config.from_file(config_path, "DEFAULT")

# Client with endpoint, retry, and timeout
client = oci.generative_ai_inference.GenerativeAiInferenceClient(
    config=config,
    service_endpoint=endpoint,
    retry_strategy=oci.retry.NoneRetryStrategy(),
    timeout=(10, 240)
)

# Chat with TextContent + Message objects
chat_detail = oci.generative_ai_inference.models.ChatDetails()
chat_detail.serving_mode = OnDemandServingMode(model_id="...")
chat_detail.chat_request = GenericChatRequest(messages=[...])
chat_detail.compartment_id = compartment_id

Step 3 — MCP Servers (Optional)

Register MCP servers for extended task execution and Chat Agent tool use:

Type	Use Case
stdio	Local Python scripts (e.g., CIS check runner)
SSE	Remote HTTP servers
module	Upload .py files directly

MCP servers can be linked to ADB Vector databases, enabling them to use the vector store as a tool during report execution.

Tool Discovery: After registering a server, click "Descobrir Tools" to automatically discover available tools via MCP protocol. You can also add tools manually with name, description, and JSON Schema parameters. Discovered tools are automatically available as function calls in the Chat Agent.

Step 4 — ADB Vector + RAG (Optional)

For persistent vector storage and RAG-powered chat:

1. Add DSN (TNS name from tnsnames.ora, e.g., myatp_high)
2. Set credentials (username/password)
3. Select an Embedding Model (Cohere Embed v4.0 recommended)
4. Upload Wallet ZIP (for mTLS)
5. Test the connection
6. Register vector tables: add the names of existing tables in your ADB (e.g., cisrecom, engineerknowledgebase). Table names are case-insensitive and validated against ADB. Toggle tables active/inactive to control which are queried during RAG.

GenAI Config is optional — the app auto-resolves embedding credentials from your existing OCI config.

Step 5 — Embeddings (Optional)

Navigate to the Embeddings tab to populate the vector store:

1. CIS Recommendations: Upload the CIS PDF to populate the cisrecom table with Oracle Cloud security recommendations
2. Knowledge Base: Upload documents (.txt, .pdf, .csv, .json, .md) or paste a URL to import web pages — all content goes to the engineerknowledgebase table
3. From CIS Reports (Downloads tab): Embed completed reports with option to purge old data first
4. Browse and inspect embeddings per table

Once embeddings exist, the chat automatically uses RAG — it queries all active vector tables across all ADB configs for relevant context before generating responses with the selected GenAI model.

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OCI IAM Policies

The following policies are required in your tenancy:

Allow group <group-name> to use generative-ai-family in compartment <compartment-name>
Allow group <group-name> to read all-resources in tenancy
Allow group <group-name> to inspect compartments in tenancy
Allow group <group-name> to inspect autonomous-databases in compartment <compartment-name>
Allow group <group-name> to read virtual-network-family in compartment <compartment-name>
Allow group <group-name> to read instance-family in compartment <compartment-name>
Allow group <group-name> to read objectstorage-namespaces in tenancy
Allow group <group-name> to read buckets in compartment <compartment-name>

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Project Structure

oci-cis-agent/
├── backend/
│   ├── app.py              # FastAPI application (~5300 lines)
│   ├── cis_reports.py       # Oracle CIS Benchmark checker (6660 lines, report engine)
│   ├── mcp_cis_server.py    # MCP server with 12 granular CIS tools (~700 lines)
│   ├── gen_tf_reference.py  # OCI Terraform provider resource catalog generator
│   ├── Dockerfile           # Python 3.12 + OCI CLI + Terraform CLI
│   └── requirements.txt     # Dependencies
├── frontend/
│   └── index.html           # SPA with Oracle Dark Premium theme (~2820 lines)
├── nginx/
│   └── default.conf         # Reverse proxy config
├── docker-compose.yml       # Orchestration
├── logo.svg                 # Project logo (Oracle AI Robot)
├── .env.example             # Environment template
├── .gitignore
└── README.md

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API Reference

Authentication

Method	Endpoint	Description
POST	/api/auth/login	Login (username + password + optional TOTP)
POST	/api/auth/logout	Logout and invalidate session
POST	/api/auth/register	Create user (admin only)
POST	/api/auth/change-password	Change password

OCI Management

Method	Endpoint	Description
POST	/api/oci/config	Save OCI credentials (multipart)
GET	/api/oci/configs	List OCI credentials
PUT	/api/oci/configs/{id}	Update OCI credential (multipart)
POST	/api/oci/test/{id}	Test OCI connection
DELETE	/api/oci/configs/{id}	Delete OCI credential

OCI Account Explorer

Method	Endpoint	Description
GET	/api/oci/explore/{id}/compartments	List compartments
GET	/api/oci/explore/{id}/compartment-tree	Hierarchical compartment tree
GET	/api/oci/explore/{id}/regions	List subscribed regions
GET	/api/oci/explore/{id}/vcns	List VCNs
GET	/api/oci/explore/{id}/subnets	List Subnets
GET	/api/oci/explore/{id}/security_lists	List Security Lists (with rules)
GET	/api/oci/explore/{id}/nsgs	List Network Security Groups
GET	/api/oci/explore/{id}/route_tables	List Route Tables (with rules)
GET	/api/oci/explore/{id}/nat_gateways	List NAT Gateways
GET	/api/oci/explore/{id}/internet_gateways	List Internet Gateways
GET	/api/oci/explore/{id}/service_gateways	List Service Gateways
GET	/api/oci/explore/{id}/network_firewalls	List Network Firewalls
GET	/api/oci/explore/{id}/network_firewall_policies	List Firewall Policies
GET	/api/oci/explore/{id}/public_ips	List Public IPs
GET	/api/oci/explore/{id}/instances	List Compute Instances
GET	/api/oci/explore/{id}/instance_pools	List Instance Pools
GET	/api/oci/explore/{id}/container_instances	List Container Instances
GET	/api/oci/explore/{id}/databases	List Autonomous Databases
GET	/api/oci/explore/{id}/db_systems	List DB Systems
GET	/api/oci/explore/{id}/mysql_db_systems	List MySQL DB Systems
GET	/api/oci/explore/{id}/buckets	List Object Storage Buckets
GET	/api/oci/explore/{id}/block_volumes	List Block Volumes
GET	/api/oci/explore/{id}/boot_volumes	List Boot Volumes
GET	/api/oci/explore/{id}/file_systems	List File Systems
GET	/api/oci/explore/{id}/mount_targets	List Mount Targets
GET	/api/oci/explore/{id}/oke_clusters	List OKE Clusters
GET	/api/oci/explore/{id}/load_balancers	List Load Balancers
GET	/api/oci/explore/{id}/functions	List Functions
GET	/api/oci/explore/{id}/iam_users	List IAM Users
GET	/api/oci/explore/{id}/iam_groups	List IAM Groups
GET	/api/oci/explore/{id}/iam_policies	List IAM Policies
GET	/api/oci/explore/{id}/iam_dynamic_groups	List Dynamic Groups
GET	/api/oci/explore/{id}/vaults	List Vaults
GET	/api/oci/explore/{id}/dns_zones	List DNS Zones
GET	/api/oci/explore/{id}/api_gateways	List API Gateways
GET	/api/oci/explore/{id}/alarms	List Alarms
GET	/api/oci/explore/{id}/log_groups	List Log Groups
GET	/api/oci/explore/{id}/notification_topics	List Notification Topics
GET	/api/oci/explore/{id}/events_rules	List Events Rules

OCI Resource Actions

Method	Endpoint	Description
POST	/api/oci/instances/{id}/action	Start/Stop compute instance
POST	/api/oci/autonomous-databases/{id}/action	Start/Stop Autonomous Database

Generative AI

Method	Endpoint	Description
GET	/api/genai/models	List available models and regions
POST	/api/genai/config	Save GenAI configuration
GET	/api/genai/configs	List GenAI configurations
PUT	/api/genai/configs/{id}	Update GenAI configuration
POST	/api/genai/test/{id}	Test GenAI connection
DELETE	/api/genai/configs/{id}	Delete GenAI config

MCP Servers

Method	Endpoint	Description
POST	/api/mcp/servers	Register MCP server
GET	/api/mcp/servers	List MCP servers
PUT	/api/mcp/servers/{id}	Update MCP server
PUT	/api/mcp/servers/{id}/toggle	Activate/deactivate
POST	/api/mcp/servers/{id}/upload	Upload script file
PUT	/api/mcp/servers/{id}/link-adb	Link to ADB Vector
POST	/api/mcp/servers/{id}/discover-tools	Auto-discover tools from MCP server
PUT	/api/mcp/servers/{id}/tools	Manually update tool definitions
DELETE	/api/mcp/servers/{id}	Delete MCP server

ADB Vector

Method	Endpoint	Description
POST	/api/adb/config	Save ADB connection (with GenAI config + embedding model)
GET	/api/adb/configs	List ADB connections (includes vector tables)
PUT	/api/adb/configs/{id}	Update ADB connection (multipart)
POST	/api/adb/parse-wallet	Parse wallet ZIP and extract DSN names
POST	/api/adb/{id}/upload-wallet	Upload wallet ZIP
POST	/api/adb/test/{id}	Test ADB connection
GET	/api/adb/{id}/tables	List vector tables for ADB config
POST	/api/adb/{id}/tables	Add vector table
PUT	/api/adb/{id}/tables/{tid}	Update vector table (name, description, active)
POST	/api/adb/{id}/tables/check	Validate registered tables against ADB (case-insensitive)
DELETE	/api/adb/{id}/tables/{tid}	Remove vector table
DELETE	/api/adb/configs/{id}	Delete ADB config

Embeddings

Method	Endpoint	Description
GET	/api/embeddings/preview/{rid}	Preview report chunks before embedding (with tenancy/regions/compartments)
POST	/api/embeddings/report/{rid}	Generate embeddings from CIS report (chunked by section, accepts table_name, report_date)
POST	/api/embeddings/upload	Upload file (.txt/.pdf/.csv/.json/.md) and generate embeddings
POST	/api/embeddings/upload-url	Import URL (web page or PDF), extract text, and generate embeddings
POST	/api/embeddings/{vid}/purge	Purge old embeddings by table + tenancy before re-embedding
GET	/api/embeddings/{vid}/list	List embeddings in ADB (paginated, accepts table_name query param)
DELETE	/api/embeddings/{vid}/{doc_id}	Delete individual embedding (accepts table_name query param)

Terraform Agent

Method	Endpoint	Description
POST	/api/terraform/chat	Send message to Terraform Agent
GET	/api/terraform/resources	List OCI resources in compartment (for context)
POST	/api/terraform/workspaces	Create Terraform workspace
GET	/api/terraform/workspaces	List user's workspaces
GET	/api/terraform/workspaces/{wid}	Get workspace details
PUT	/api/terraform/workspaces/{wid}/code	Update workspace Terraform code
POST	/api/terraform/workspaces/{wid}/plan	Run terraform plan
POST	/api/terraform/workspaces/{wid}/apply	Run terraform apply
POST	/api/terraform/workspaces/{wid}/destroy	Run terraform destroy
GET	/api/terraform/workspaces/{wid}/status	Poll workspace execution status
GET	/api/terraform/workspaces/{wid}/download	Download workspace .tf files
POST	/api/terraform/workspaces/{wid}/cancel	Cancel running Terraform operation
DELETE	/api/terraform/workspaces/{wid}	Delete workspace
POST	/api/terraform/refresh-reference	Regenerate OCI Terraform resource reference (UI button)

Chat & Reports

Method	Endpoint	Description
POST	/api/chat	Send message (with RAG + MCP tool use, accepts use_tools flag)
POST	/api/chat/upload	Send message with file attachments (multipart, images/PDFs/text)
GET	/api/chat/sessions	List chat sessions (history) with agent type filter
GET	/api/chat/sessions/{sid}/messages	Get messages for a session
PUT	/api/chat/sessions/{sid}/title	Rename a chat session
DELETE	/api/chat/{sid}	Delete chat session and messages
POST	/api/reports/run	Execute CIS report
GET	/api/reports	List reports
GET	/api/reports/{id}/html	View HTML report
GET	/api/reports/{id}/download	Download report
GET	/api/reports/{rid}/summary	Report KPI summary (score, pass/fail, sections)
GET	/api/reports/{rid}/files	List report files by category
GET	/api/reports/{rid}/files/{fid}/download	Download individual report file

CIS Engine

Method	Endpoint	Description
GET	/api/cis-engine/version	Current CIS engine version
GET	/api/cis-engine/check-update	Check GitHub for newer version (admin)
POST	/api/cis-engine/update	Download + apply update with patches (admin)

Config Logs

Method	Endpoint	Description
GET	/api/config-logs	List config logs (filterable by config_type, severity, config_id)
DELETE	/api/config-logs	Clear config logs (admin, filterable by config_type, config_id)

Admin

Method	Endpoint	Description
GET	/api/users	List users (admin)
PUT	/api/users/{id}	Update user role/status
POST	/api/mfa/setup	Generate MFA secret
POST	/api/mfa/verify	Activate MFA
GET	/api/audit-log	View audit log (admin)
GET	/api/health	Health check

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Supported GenAI Models (15 Chat + 3 Embedding)

All models include OCID mapping for us-ashburn-1. For other regions, use the "Personalizado (usar OCID)" option.

Chat Models

Provider	Model	Model ID	API Format
Meta	Llama 4 Maverick	meta.llama-4-maverick-17b-128e-instruct-fp8	GENERIC
Meta	Llama 4 Scout	meta.llama-4-scout-17b-16e-instruct	GENERIC
Google	Gemini 2.5 Pro	google.gemini-2.5-pro	GENERIC
Google	Gemini 2.5 Flash	google.gemini-2.5-flash	GENERIC
OpenAI	GPT-5.2	openai.gpt-5.2	GENERIC
OpenAI	GPT-5.1	openai.gpt-5.1	GENERIC
OpenAI	GPT-5 Mini	openai.gpt-5-mini	GENERIC
OpenAI	GPT-4.1 (Default)	openai.gpt-4.1	GENERIC
OpenAI	GPT-4.1 Mini	openai.gpt-4.1-mini	GENERIC
OpenAI	GPT-4o	openai.gpt-4o	GENERIC
OpenAI	o4-mini	openai.o4-mini	GENERIC
OpenAI	o3	openai.o3	GENERIC
xAI	Grok 4	xai.grok-4	GENERIC
xAI	Grok 3	xai.grok-3	GENERIC
xAI	Grok 3 Mini Fast	xai.grok-3-mini-fast	GENERIC

Custom OCID: You can also use any model available in your region by selecting "Personalizado (usar OCID)" and providing the full model OCID.

Embedding Models

Provider	Model	Model ID	Dimensions
Cohere	Embed v4.0 (Multimodal)	cohere.embed-v4.0	1536
OpenAI	Text Embedding 3 Large	openai.text-embedding-3-large	3072
OpenAI	Text Embedding 3 Small	openai.text-embedding-3-small	1536

GenAI Regions

us-chicago-1 · us-ashburn-1 · us-phoenix-1 · uk-london-1 · eu-frankfurt-1 · ap-tokyo-1 · ap-osaka-1 · sa-saopaulo-1 · ca-toronto-1 · ap-melbourne-1 · ap-mumbai-1 · eu-amsterdam-1 · me-jeddah-1 · ap-singapore-1 · ap-seoul-1 · sa-vinhedo-1

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Tech Stack

Component	Technology
Backend	Python 3.12, FastAPI 0.115, Uvicorn
Frontend	Vanilla JS SPA, Oracle Dark Premium theme, Chart.js
Auth	JWT + TOTP MFA + RBAC
Database	SQLite (WAL mode)
OCI SDK	oci 2.133.0, oci-cli
ADB	python-oracledb 2.4.1 (Thin mode)
GenAI	oci.generative_ai_inference
Container	Docker Compose, Nginx reverse proxy
MCP	Model Context Protocol SDK (stdio/SSE) with tool discovery + execution
Terraform	Terraform CLI 1.7.5, OCI Provider
CIS Scanner	Oracle CIS Foundations Benchmark 3.0 checker (cis_reports.py)

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Versioning

Version	Date	Changes
v2.3	2026-03	Knowledge Base & RAG Enhancements: Knowledge Base (Base de Conhecimento) with file upload + URL import to engineerknowledgebase vector table, CIS Recommendations upload to cisrecom table, URL content extraction (HTML tag/script stripping, remote PDF parsing), auto-resolve embedding config from OCI credentials (no separate GenAI config required), report_date metadata tracking for embedding freshness, purge & re-embed flow for updated reports. ADB Vector Improvements: case-insensitive table matching with quoted identifiers for Oracle ADB, table validation endpoint against user_tables, tables section moved inside edit connection card, case-preserving table registration (removed forced uppercase). Embeddings tab cleanup: removed delete buttons, simplified to read-only view, updated descriptions. Dependencies: added PyPDF2 for PDF text extraction
v2.2	2026-03	UI Modernization (Phases 1B-5): Oracle Dark Premium theme, 45+ Lucide SVG icons replacing all emojis, KPI dashboard with compliance gauge + Chart.js donut/bar charts, report summary API endpoint, Phase 5 animations (staggered fade-in, smooth theme transitions, hover effects) — animations scoped to tab switch only (no flickering on re-render). Terraform Intelligence: official resource docs injection from registry.terraform.io (Example Usage + Argument Reference, on-demand fetch + SQLite cache), smart tfvars auto-generation from declared variables, multi-region provider management with var.region support, RPC anti-cycle rule, system prompt auto-sync to DB, 60-min polling timeout for long-running applies. ADB fix: wallet_password always passed for thin mode mTLS (fixes DPY-6005). CIS_EMBEDDINGS default removed from ADB config
v2.1	2026-03	Terraform Agent (AI-powered IaC generation with plan/apply/destroy lifecycle, workspace management, Terraform CLI in container, inline file editor, split-panel terminal, multi-file generation via // filename: markers, smart file correction with merge-based updates, 14-point validation checklist, 100K max_tokens), 3-layer auto-split pipeline (frontend + backend monolithic HCL splitting into categorized files + backend deduplication), HCL syntax auto-fix (single-line blocks expanded to multi-line), SQLite-based resource type validation (~937 types with difflib suggestions for invalid types), Terraform Resource Reference (auto-generated OCI provider catalog from terraform providers schema -json, generated at startup to survive volume mounts, stored in SQLite, refreshable via menu button), compact system prompt for Terraform agent, ChatGPT-style chat history for both Chat Agent and Terraform Agent (rename/delete sessions), OCI Resource Actions (start/stop instances and Autonomous DBs from OCI Account Explorer), OCI Explorer expanded to 40+ resource types across 8 categories with tree-view navigation and resizable panels, compartment filtering for MCP CIS scans, chat sidebar with model parameters, chat audit logs, collection error tracking in MCP server, tool timeout increased to 30min with auto-retry, memory compaction tuned (6K threshold, 20 recent messages), model catalog trimmed from 69 to 15 curated models, improved GenAI response extraction with fallback for empty responses, fixed layout overflow (no page scroll), provider alias detection with brace-matching parser, multi-region Terraform support
v2.0	2026-03	Async background chat processing (no more 504 timeouts), frontend polling with timestamps, 8 uvicorn workers + 16-thread chat executor for ~12 simultaneous chats, parallelized MCP data collection (5-thread base + 8-thread regional), 2-hour MCP session cache, 5-min tool timeout, full dead code cleanup across backend/frontend/MCP
v1.9	2026-03	Multimodal chat (image/PDF/text file upload with OCI GenAI ImageContent/DocumentContent), region-specific MCP scanning (regions param on all scan tools), orphaned report auto-detection on progress poll, nginx timeout increased to 15min, improved API error handling for non-JSON responses
v1.8	2026-03	CIS Engine auto-update from Oracle GitHub with automatic patch reapplication, version check UI card (admin), new /api/cis-engine/* endpoints, report file listing and individual download endpoints, reorganized Reports tab (execution history + status) and Downloads tab (file browser only with expandable cards per report), CIS Level description tooltip, persistent log expand during report generation
v1.7	2026-03	Oracle official CIS report engine (replaces lightweight checker), granular report parameters (Level, OBP, Raw Data, Redact), per-report file storage with category browser, tenancy filter in Downloads, individual file download
v1.6	2026-03	Granular CIS MCP server (12 per-section scan tools: IAM, Networking, Compute, Logging/Monitoring, Storage, Asset Management), chat memory compaction with LLM-based summarization, GenAI tool use loop fix (accumulated conversation), chat thinking indicator, auto-registered CIS MCP server
v1.5	2026-03	MCP Tool Use in Chat (GenAI function calling with auto tool discovery + execution via MCP SDK), multi-table ADB vector search, preview chunks before embedding, enriched embeddings with tenancy/regions/compartments, searchable dropdowns, editable vector tables, orphaned report cleanup on restart
v1.4	2026-03	In-place config editing, 69 chat + 11 embedding models with OCID resolution (OpenAI GPT-5.3/5.2/5.1/5/4.1/4o/Codex/Image/Audio, xAI, Google, Meta, ProtectAI), OpenAI Text Embedding 3, custom OCID support, wallet auto-parse with DSN extraction
v1.3	2026-03	Persistent config logs per tab, GenAI auto-fill from OCI credentials, inline UX feedback with loading spinners, MCP type-switch fix, encrypted key passphrase support, Docker stdin hang fix
v1.2	2026-03	RAG pipeline (OCI GenAI embeddings + ADB vector search), dedicated Embeddings tab, CIS report chunking, file upload embedding
v1.1	2025-02	OCI SDK GenAI (exact pattern), OCI Account Explorer, MCP↔ADB linking, full chat parameters
v1.0	2025-02	Initial release: OCI theme, GenAI integration, MCP servers, ADB vector, JWT+MFA+RBAC

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Development

Run Backend Locally

cd backend
pip install -r requirements.txt
DATA_DIR=./data uvicorn app:app --reload --port 8000

Run with Docker

docker compose up -d --build
docker compose logs -f backend

Rebuild After Changes

docker compose down
docker compose up -d --build

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Troubleshooting

OCI CLI test fails with timeout: Check that your API key is correctly configured and the tenancy OCID is valid. Ensure outbound HTTPS (443) is allowed.

GenAI returns 401/403: Verify the IAM policy Allow group ... to use generative-ai-family in compartment ... exists. Check that the compartment OCID in the GenAI config matches the policy.

OCI CLI test hangs with passphrase prompt (Docker): If your private key is encrypted (ENCRYPTED in the PEM header), provide the passphrase in the Key Passphrase field when saving the credential. Unencrypted keys work without a passphrase. The app automatically detects encrypted keys and blocks upload if no passphrase is provided.

ADB connection fails (DPY-6005: cannot connect): Ensure the wallet ZIP contains tnsnames.ora and ewallet.pem. The DSN must match a service name in tnsnames.ora (e.g., myatp_high). If using an auto-login wallet without a custom password, leave the wallet password field empty — the app automatically passes an empty string for wallet_password which is required by python-oracledb thin mode even for auto-login wallets.

Container won't start:

docker compose logs backend

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License

MIT

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_{Built with ❤️ for Oracle Cloud Infrastructure security compliance}