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security threat model

MD MUFTHAKHERUL ISLAM MIRAZ edited this page Jun 24, 2026 · 2 revisions

🎯 Siyarix Threat Model

As a security tool, it's important to understand the risks and protections built into Siyarix. This document outlines the basic threat model and the mitigations I've tried to engineer into the system.

💎 Critical Assets

Here is what Siyarix tries to protect locally:

Asset Description
AI Provider API Keys Your tokens for OpenAI, Anthropic, Gemini, etc.
Credential Store The encrypted vault holding your secrets.
Scan Results Discovered target data and vulnerabilities.
Session & Audit Logs Your command history and local trails.

🚧 Trust Boundaries

┌──────────────┐     ┌──────────────┐     ┌───────────────┐
│   User TTY   │────▶│   Siyarix    │────▶│  AI Provider  │
│  (Terminal)  │     │ CLI Process  │     │    (Cloud)    │
└──────────────┘     └──────┬───────┘     └───────────────┘
                            │
                    ┌───────▼───────┐
                    │   External    │
                    │    Tools      │
                    │ (nmap, etc.)  │
                    └───────────────┘

Boundary 1: User → Siyarix

  • The Threat: Shell or command injection.
  • Our Defense: The InputValidator enforces syntax rules and the PermissionGate validates commands before passing them to the OS.

Boundary 2: Siyarix → AI Provider

  • The Threat: Accidentally sending local secrets to a third-party AI cloud.
  • Our Defense: The DLP Engine tries to redact common secret patterns before data leaves your machine.

Boundary 3: Siyarix → External Tools

  • The Threat: An external tool acts unpredictably.
  • Our Defense: Subprocess isolation and strict command validation.

⚔️ Threats and Mitigations

T1: API Key Exfiltration

  • Defense: The CredentialStore encrypts your keys locally. The DLP engine attempts to redact them from prompts.

T2: LLM Prompt Injection

  • Defense: The AI does not have direct access to your shell. Everything the AI suggests must pass through the PermissionGate and you must manually confirm hybrid commands.

T3: Data Leakage to the Cloud

  • Defense: Masking replaces IPs, passwords, and API keys with safe placeholders (e.g., [REDACTED_IP_1]).

T4: Unauthorized Tool Execution

  • Defense: The Permission Gate blocks known dangerous commands like rm -rf /. Safe Mode can lock the system to reconnaissance-only tools.

T5: Audit Log Tampering

  • Defense: Siyarix uses a hash chain for audit logs to help detect local tampering.

🛡️ Core Security Assumptions

To maintain this security posture, Siyarix assumes:

  1. Your local terminal environment and OS user account are reasonably secure.
  2. The OS protects the file permissions of the ~/.siyarix/ directory.
  3. AI providers are treated as untrusted third parties.
  4. External tools execute as standard subprocesses without requiring raw root access unless explicitly authorized.

Note

👋 Welcome to Siyarix! This is a personal passion project built by a single developer. It's currently under active development and growing fast. Expect rough edges, but lots of love! ❤️

🗺️ Siyarix Documentation Map

Welcome to the Siyarix Documentation Map! This page serves as your master compass for navigating the extensive documentation we have built for the platform.

Whether you are a brand new user, a seasoned security operator, or a developer looking to contribute to the core engine, you can find exactly what you need here.


🧭 Quick Navigation

Not sure where to start? Pick the path that best describes you:

🌱 For New Users

Just getting started? We highly recommend following these guides in order:

  1. Installation Guide — Get Siyarix running on your machine.
  2. Onboarding Wizard — Let our interactive wizard help you set up your API keys and environment.
  3. Setup & Configuration — A deeper dive into customizing your setup.
  4. Your First Run — A gentle walkthrough of your very first Siyarix command.

🛡️ For Security Operators

Ready to put Siyarix to work? Dive into our operational guides:

💻 For Developers & Contributors

Looking under the hood or wanting to write some code? Start here:


📂 The Complete Documentation Tree

If you prefer to browse the raw structure, here is a complete layout of the docs/ folder:

docs/
├── 🚀 getting-started/       # Installation, onboarding, and configuration
│   ├── installation.md       # Multi-platform install (pip, brew, winget, docker)
│   ├── onboarding.md         # The interactive 11-step setup wizard
│   ├── setup.md              # Managing API keys, credentials, and settings
│   ├── first-run.md          # A walkthrough of your first session
│   ├── configuration.md      # A deep-dive into advanced settings
│   └── troubleshooting.md    # Common issues and how to fix them instantly
│
├── 📖 user/                  # Daily operations and workflows
│   ├── cli-commands.md       # Reference for 50+ CLI commands across 12 groups
│   ├── interactive-chat.md   # Mastering the AI REPL and 54+ slash commands
│   ├── security-workflows.md # Recon, vulnerability assessment, incident response
│   ├── cloud-scanning.md     # Multi-cloud security scanning (under development)
│   ├── compliance.md         # Framework mapping (SOC 2, NIST, GDPR, PCI-DSS)
│   ├── threat-intelligence.md# Integrations with OTX, NVD, and MITRE ATT&CK
│   ├── playbooks.md          # Building automated YAML-based IR playbooks
│   ├── workflow-files.md     # DAG workflow reference (programmatic API)
│   ├── reporting.md          # Multi-format report generation
│   ├── offline-registry.md   # Running without AI (Offline/Registry execution mode)
│   └── ai-workflows.md       # Advanced AI-driven autonomous operations
│
├── 💻 developer/             # Building, testing, and extending Siyarix
│   ├── codebase-overview.md  # Full module structure mapping
│   ├── contribution-guide.md # How to submit PRs and our coding standards
│   ├── module-architecture.md# Component design and responsibilities
│   ├── testing.md            # Writing tests (pytest), coverage, and CI/CD
│   └── building.md           # Packaging, distribution, and Docker builds
│
├── 🏗️ architecture/          # System design and core internals
│   ├── overview.md           # High-level data flow and layered orchestration
│   ├── ai-agent-pipeline.md  # The AgentCore reasoning and execution pipeline
│   ├── provider-abstraction.md# How we unify 26 different AI providers
│   ├── execution-engine.md   # Plan-based step orchestration
│   ├── memory-and-state.md   # Knowledge graph, session persistence, and learning
│   ├── security-model.md     # The Permission Gate, DLP, audit logging, and OPSEC
│   └── intent-routing.md     # Semantic intent classification and routing
│
├── 🧠 ai/                    # Deep dive into the AI provider & agent systems
│   ├── routing.md            # Managing 26 providers, failovers, and circuit breakers
│   ├── persona-system.md     # Overview of our 10 security personas
│   ├── agent-reasoning.md    # The Observe-Reason-Act loop and tool call repair
│   ├── tool-execution.md     # The tool registry, capability graph, and parsers
│   ├── ensemble.md           # Parallel LLM voting strategies
│   ├── multi-wave.md         # Iterative goal execution with context carry-over
│   ├── prompt-architecture.md# System prompt design and management
│   └── safety.md             # Our rigorous 8-layer hallucination mitigation system
│
├── 🛡️ security/              # Safety, ethics, and threat models
│   ├── reporting.md          # How to safely report vulnerabilities to us
│   ├── threat-model.md       # System threat model and our mitigations
│   ├── operational-security.md# TOR routing, stealth modes, and OPSEC controls
│   ├── ethical-policy.md     # Mandatory rules of engagement for all users
│   └── abuse-prevention.md   # How we prevent misuse of the AI engine
│
└── ⚖️ legal/                 # Licensing and governance
    ├── agpl-guide.md         # A plain-English overview of the AGPL-3.0-or-later license
    ├── why-agpl.md           # The philosophy behind our license choice
    ├── trademark-policy.md   # Branding and trademark guidelines
    ├── responsible-ai.md     # Our framework for ethical AI usage
    ├── disclaimer.md         # Important legal disclaimers
    └── plugin-exception.md   # The license exception for building custom plugins

📖 Key Terminology

As you read through the documentation, you might encounter some specific terms. Here is a quick cheat sheet:

Term What It Means
Provider The backend AI engine powering Siyarix (e.g., OpenAI, Anthropic, Ollama).
Tool A traditional security executable installed on your system (e.g., nmap, nuclei).
Plan A step-by-step sequence of tool commands intelligently generated by the AI.
Workflow A hardcoded, predefined execution path (usually defined in YAML/JSON) that doesn't require AI generation.
Persona A specialized behavioral profile given to the AI (e.g., instructing it to act specifically as a "Network Recon Specialist").
Knowledge Graph Siyarix's internal memory where it stores findings (like IP addresses, open ports) to contextually inform future steps.

Need help finding something specific? Feel free to use the search bar at the top of the documentation site, or open a discussion on our GitHub!

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