SecAgent

README

LEGAL DISCLAIMER — SecAgent is designed exclusively for authorized security testing, red team engagements, and vulnerability research on systems you own or have explicit written permission to test. Unauthorized use against systems without permission is illegal. The authors assume no liability for misuse.

Table of Contents

• What Is SecAgent
• Key Differentiators
• Capabilities Matrix
• Comprehensive System Architecture
  • 1. High-Level System Topology & Polyglot Engine
  • 2. Autonomous Scan Lifecycle Sequence
  • 3. Multi-Agent Swarm Decision Logic
  • 4. Multi-Provider LLM Fallback & Consensus Engine
• Quick Start Guide
• Installation Guide
  • Prerequisites
  • Method 1 — Automated Installation Engine (Recommended)
  • Method 2 — Manual Package Installation
• Releases, Deployments & Packages
  • Releases
  • Deployment Models
  • Package Artifacts
• Configuration & Operational Manifest
• Complete CLI Usage Reference
  • Subcommand Specifications & Flags
• Sample Deliverables & Deliverable Schemas
  • 1. Executive Markdown Deliverable
  • 2. Machine-Readable JSON Schema
• Project Directory Layout
• Troubleshooting & Operations Guide
• Contributing & Security Policy
• License

What Is SecAgent

Traditional vulnerability scanners are rigid, noisy, and context-blind. They execute static pattern matching, miss complex multi-stage attack vectors, and flood security operators with false positives that waste valuable time.

SecAgent is an Autonomous, Pure-CLI Red Teaming & Offensive Intelligence Framework.

It operates as a Distributed Cognitive Security Engine — harnessing specialized multi-agent AI swarms that reason through attack surfaces the way an elite red-team operator does. SecAgent identifies technology stacks, enumerates subdomains and HTTP endpoints via active httpx and Go probes, crafts context-aware exploits, validates vulnerabilities through deterministic proof-of-concepts, and generates correlated, impact-first deliverables.

Built for:

• Red Teams executing full-scope autonomous engagements
• Security Researchers performing automated attack surface discovery & zero-day research
• Bug Bounty Hunters conducting active recon and vulnerability verification
• Offensive AI Researchers auditing AI supply chains, prompt injections, and RAG pipelines

Key Differentiators

1. Pure CLI-First Architecture: No bloated web UI or complex database setup required. Designed for headless VPS execution, Docker containers, SSH sessions, and CI/CD pipelines.
2. Polyglot Performance Engine: High-speed Go microservices for concurrent network probing, Rust for microsecond priority scheduling, C++20 for SIMD regex signature matching, and Python for LLM multi-agent reasoning.
3. Aura Cognitive Memory Engine: Target DNA layering, payload pattern crystallization, decay-reinforcement mechanisms, and WAF fingerprint memory across scan missions (secagent memory).
4. Zero False-Positive Live Validation: Integrated CrucibleValidator replays proof-of-concept payloads with HTTP status code consistency & response body variance checks against target endpoints.
5. Shared Connection Pooling & High Concurrency: Connection-pooled CVEScanner and concurrent WebSecurityAgent scanning via asyncio.Semaphore task dispatching.
6. Headless Browser Inspection: BrowserAgent automated Chrome DOM extraction & dynamic Playwright form parsing with fallback HTTP inspection.
7. Strict SSL/TLS Enforcement: Environment-controlled dynamic SSL verification (SECAGENT_VERIFY_SSL) across all agent HTTP clients.
8. Hardware-Aware Local Fallback: Automatically detects GPU/CPU capabilities to provision local Ollama models (llama3, mistral, codellama) when cloud APIs are unavailable.
9. Model Context Protocol (MCP) Server Mode: Native JSON-RPC stdio server (secagent mcp) allowing Claude Code, Cursor, and VS Code Copilot to drive SecAgent with zero API cost.
10. Declarative YAML Playbooks: Define and version-control complex pentesting methodologies with conditional rules and LLM decision gates (secagent playbook).
11. Portable Proof Capsules & Replay Engine: Export verified vulnerabilities to .json proof capsules and re-prove them on demand via secagent replay.
12. Human-In-The-Loop (HITL) Teleoperation: Intercept double Ctrl+C during scan execution to drop into an interactive operator REPL (step, inspect, inject, resume, abort).
13. LLM Budget Guard & Cost Safeguard: Real-time token cost accounting and configurable budget limit enforcement (SECAGENT_PRICE_LIMIT).

Capabilities Matrix

Comprehensive System Architecture

1. High-Level System Topology & Polyglot Engine

graph TB
    subgraph CLI_LAYER["🖥️ CLI & Interface Control Plane"]
        CLI["secagent CLI (Rich TUI)"]
        MCP["🔌 MCPServer (JSON-RPC stdio)"]
        PLAYBOOK["📜 Playbook Engine (YAML Methodologies)"]
        CAPSULE["📦 Proof Capsule Engine & Replayer"]
        HITL["🕹️ Teleoperation Controller (Double Ctrl+C)"]
        BUDGET["💰 BudgetGuard (Token & Cost Accounting)"]
        SCOPE["Scope Gate (Fail-Closed Enforcer)"]
        VAULT["Vault Key Manager (.env Loader)"]
        PREFLIGHT["Preflight Integrity Checker"]
    end

    subgraph MEMORY_LAYER["🧠 Cognitive Memory Subsystem"]
        AURA["AuraMemoryManager (Target DNA & Pattern Engine)"]
        DB[("💾 SQLite / aura-memory SDK Database")]
    end

    subgraph SWARM_LAYER["🐝 Python Agent Swarm"]
        PLANNER["🎯 Planner Agent (Armada DAG Builder)"]
        RECON["🔍 Recon Agent (httpx + Async Prober)"]
        WEB["🌐 Web Security Agent"]
        API["⚡ API Security Agent"]
        WEB3["🕸️ Web3 Security Agent"]
        VALIDATOR["🔬 Validator Agent (Crucible)"]
        REPORTER["📊 Report Agent"]
    end

    subgraph ENGINE_LAYER["⚙️ Polyglot Core Engine"]
        CPP["⚡ C/C++ Foundational Core (cpp-core)"]
        RUST["🦀 Rust Engine & Priority Scheduler"]
        GO["🐹 Go Subdomain & Network Prober"]
        REDIS[("🔴 Redis Pub/Sub Event Bus")]
    end

    CLI --> SCOPE
    MCP --> SCOPE
    PLAYBOOK --> SCOPE
    CAPSULE --> VALIDATOR
    HITL --> SWARM_LAYER
    BUDGET --> SWARM_LAYER
    SCOPE --> PREFLIGHT
    PREFLIGHT --> VAULT
    VAULT --> PLANNER
    AURA <--> DB
    PLANNER <-->|Recall Target DNA| AURA
    PLANNER --> RECON
    PLANNER --> WEB
    PLANNER --> API
    PLANNER --> WEB3
    RECON --> GO
    RECON --> RUST
    RECON --> CPP
    SWARM_LAYER --> REDIS
    SWARM_LAYER --> VALIDATOR
    VALIDATOR -->|Export Proof Capsule| CAPSULE
    VALIDATOR -->|Crystallize Exploits| AURA
    VALIDATOR --> REPORTER

5. C/C++ Foundational Core Engine (cpp-core) & Native Bridge Demonstration

SecAgent incorporates a compiled C++20 Foundational Core (cpp-core) for sub-millisecond execution tasks, SIMD-accelerated regex/signature matching, and asynchronous raw socket probing.

C++ Core Architecture Topology

graph LR
    subgraph PYTHON_BRIDGE["🐍 Python Native Bridge"]
        PY_NATIVE["secagents.core.native"]
        CTYPES["ctypes C-ABI Loader"]
    end

    subgraph CPP_ENGINE["⚡ C++ Foundational Engine (secagent_core)"]
        C_API["c_api.cpp (extern 'C' Exported API)"]
        MATCHER["FastMatcher (C++20 SIMD Regex Engine)"]
        PROBER["RawSocketProber (Non-Blocking Socket Engine)"]
    end

    subgraph OS_KERNEL["💻 OS Kernel"]
        SOCKETS["Raw Sockets / AF_PACKET / Winsock2"]
    end

    PY_NATIVE --> CTYPES
    CTYPES ==>|Direct C-ABI Calls| C_API
    C_API --> MATCHER
    C_API --> PROBER
    PROBER ==>|Non-Blocking I/O| SOCKETS

Code Demonstration 1 — High-Speed C++ Signature Matching (fast_matcher.cpp)

#include "fast_matcher.hpp"
#include <regex>

namespace SecAgentCore {
    bool FastMatcher::scan_signature(const std::string& buffer, const std::string& pattern) {
        if (buffer.empty() || pattern.empty()) return false;
        try {
            std::regex re(pattern, std::regex_constants::icase | std::regex_constants::optimize);
            return std::regex_search(buffer, re);
        } catch (...) {
            return buffer.find(pattern) != std::string::npos;
        }
    }
}

Code Demonstration 2 — Non-Blocking C++ Socket Prober (raw_socket.cpp)

#include "raw_socket.hpp"
#include <chrono>

namespace SecAgentCore {
    ProbeResult RawSocketProber::probe_port(const std::string& host, int port, int timeout_ms) {
        auto start = std::chrono::high_resolution_clock::now();
        int sock = ::socket(AF_INET, SOCK_STREAM, IPPROTO_TCP);
        // Execute non-blocking socket connect with select() timeout monitoring...
        auto elapsed = std::chrono::high_resolution_clock::now() - start;
        double latency = std::chrono::duration<double, std::milli>(elapsed).count();
        return {true, port, "open", latency};
    }
}

Code Demonstration 3 — Exported C-ABI Bridge (c_api.cpp)

#include "c_api.h"
#include "fast_matcher.hpp"
#include "raw_socket.hpp"

extern "C" {
    SECAGENT_EXPORT int secagent_match_signature(const char* buffer, const char* pattern) {
        return SecAgentCore::FastMatcher::scan_signature(buffer, pattern) ? 1 : 0;
    }

    SECAGENT_EXPORT SecAgentProbeResult secagent_probe_port(const char* host, int port, int timeout_ms) {
        auto res = SecAgentCore::RawSocketProber::probe_port(host, port, timeout_ms);
        return {res.open ? 1 : 0, res.port, res.latency_ms};
    }
}

Code Demonstration 4 — Python Native Bridge Invocation (native.py)

from secagents.core.native import native_engine

# High-speed C++ signature scanning
matched = native_engine.match_signature(response_body, r"Apache/\d+\.\d+")

# High-speed native socket probing
result = native_engine.probe_port("127.0.0.1", 80, timeout_ms=500)
print(f"Port Open: {result['open']}, Latency: {result['latency_ms']}ms")

2. Autonomous Scan Lifecycle Sequence

sequenceDiagram
    autonumber
    actor Operator as Operator / CLI
    participant Pipeline as ScanPipeline
    participant Memory as Aura Cognitive Memory
    participant Swarm as Agent Swarm
    participant Recon as Recon Agent (Go/httpx)
    participant Validator as Crucible Validator
    participant Reporter as Report Generator

    Operator->>Pipeline: secagent scan -t target.com --depth standard
    Pipeline->>Pipeline: Enforce Scope & Run Preflight System Checks
    Pipeline->>Memory: Recall Target DNA & WAF Signature
    Memory-->>Pipeline: Return Historical Fingerprints & High-Confidence Payloads
    Pipeline->>Swarm: Initialize Swarm DAG with Recalled Memory
    Swarm->>Recon: Execute Active Subdomain & HTTP Probing
    Recon-->>Swarm: Return Active Hosts, Services & Parameters
    Swarm->>Swarm: Run Parallel Scans (Web, API, Web3, CVE Checks)
    Swarm-->>Validator: Submit Raw Finding Signals
    Validator->>Validator: Replay PoC Payloads & Linear-Scale Latency Checks
    Validator->>Memory: Crystallize Validated Exploit Patterns & Update Target DNA
    Validator-->>Reporter: Return 100% Confirmed Vulnerabilities
    Reporter->>Operator: Render Mission Intelligence Summary & Save Deliverables

3. Multi-Agent Swarm Decision Logic

graph LR
    SUB["Supervisor Agent"] -->|Classify Intent| PLAN["Planner Agent"]
    PLAN -->|Execution Graph| WORKERS["Worker Swarm"]
    
    subgraph WORKERS["Worker Swarm"]
        direction TB
        R["Recon Agent"]
        W["Web Security"]
        A["API Security"]
        W3["Web3 Security"]
    end

    WORKERS -->|Raw Signals| VAL["Crucible Validator"]
    VAL -->|Confirmed PoC| REP["Report Agent"]

    style SUB fill:#0f3460,stroke:#e94560,color:#fff
    style PLAN fill:#16213e,stroke:#00ffff,color:#fff
    style VAL fill:#1a6b1a,stroke:#00ff00,color:#fff
    style REP fill:#533483,stroke:#ff00ff,color:#fff

4. Multi-Provider LLM Fallback & Consensus Engine

flowchart TD
    REQ["Agent Task Request"] --> PROVIDER{"Primary LLM Configured?"}
    
    PROVIDER -- "OpenAI" --> OAI["OpenAI (GPT-4o)"]
    PROVIDER -- "Anthropic" --> ANT["Anthropic (Claude 3.5)"]
    PROVIDER -- "Gemini" --> GEM["Google (Gemini 1.5 Pro)"]
    PROVIDER -- "Groq" --> GROQ["Groq (Llama-3 70B)"]
    
    OAI -- "Fail / Rate Limit" --> ANT
    ANT -- "Fail / Rate Limit" --> GEM
    GEM -- "Fail / Rate Limit" --> GROQ
    GROQ -- "Fail / Offline" --> LOCAL["Local Ollama Fallback"]
    
    OAI --> CONSENSUS["Consensus Engine (Min Agreement: 2)"]
    ANT --> CONSENSUS
    GEM --> CONSENSUS
    LOCAL --> CONSENSUS
    
    CONSENSUS --> OUT["Validated Agent Decision"]

Quick Start Guide

# 1. Clone the repository
git clone https://github.com/gl1tch0x1/cog-ai.git
cd cog-ai

# 2. Run the automated deployment engine
python installer.py

# 3. Configure environment secrets
cp .env.example .env
nano .env  # Add OPENAI_API_KEY, ANTHROPIC_API_KEY, or GEMINI_API_KEY

# 4. Initiate an autonomous red-team scan
secagent scan --target example.com --depth standard

Installation Guide

Prerequisites

Method 1 — Automated Installation Engine (Recommended)

The installer sets up virtual environments, mounts core dependencies, creates entrypoints, and verifies system integrity:

python installer.py

Method 2 — Manual Package Installation

For developer control or integration into existing Python environments:

# 1. Create and activate virtual environment
python -m venv venv

# Windows PowerShell:
.\venv\Scripts\Activate.ps1
# Linux / macOS:
source venv/bin/activate

# 2. Install secagents package in editable mode
pip install -e ./python-agents[dev,browser]

Releases, Deployments & Packages

Releases

• Current Version: v0.3.0-dev
• Release Tracking: Managed via CHANGELOG.md
• Tagging: Follows Semantic Versioning (MAJOR.MINOR.PATCH).

Deployment Models

SecAgent is engineered for flexible deployment across local machines, remote servers, and containerized clusters.

Docker Compose Deployment

Run core background microservices (Redis event bus, Rust engine, Go prober):

docker compose up -d

Container inventory:

• redis: Pub/Sub event bus (:6379)
• rust-core: Rust priority task scheduler
• recon: Go high-concurrency network prober

Standalone CLI Binary Deployment

The installer generates executable binary wrappers for quick invocation:

• Windows: secagent.bat
• Linux/macOS: ./secagent

Package Artifacts

The Python agent core is packaged as a standard PyPI wheel:

# Build python package wheel
cd python-agents
python -m build

Artifact generated: python-agents/dist/secagents-0.2.0-py3-none-any.whl.

Configuration & Operational Manifest

Operational parameters and API credentials are read from .env:

# ─── Primary LLM Provider Keys ───
OPENAI_API_KEY=sk-proj-...
ANTHROPIC_API_KEY=sk-ant-...
GEMINI_API_KEY=AIzaSy...
GROQ_API_KEY=gsk_...
DEEPSEEK_API_KEY=sk-...

# ─── Local LLM Configuration ───
OLLAMA_HOST=http://localhost:11434
DEFAULT_LOCAL_MODEL=llama3:8b

# ─── Operational Scope & Infrastructure ───
ALLOWED_DOMAINS=example.com,target.local
REDIS_URL=redis://localhost:6379/0
RESULTS_DIR=cog-ai-results
SECAGENT_VERIFY_SSL=true

Complete CLI Usage Reference

usage: secagent [-h] [--version]
                {scan,vault,keyhacks,preflight,update,hardware,worker} ...

SecAgent — Autonomous Offensive AI Framework (authorized testing only)

positional arguments:
  {scan,vault,keyhacks,preflight,update,hardware,worker}
    scan                Execute autonomous red-team pipeline
    vault               Interface with secret storage and API keys
    keyhacks            Scan local assets for leaked credentials
    preflight           Validate system readiness
    update              Check and apply framework updates
    hardware            Hardware-aware model optimization
    worker              Start background workflow processor

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit

Subcommand Specifications & Flags

1. secagent scan — Autonomous Red-Team Pipeline

secagent scan --target <domain/URL> [options]

Options:
  --target, -t TEXT       Target domain or URL [Required]
  --depth {quick,standard,deep}  Scan intensity (default: standard)
  --workers, -w INT       Parallel agent swarm size (default: 4)
  --skip-os-check         Bypass OS security baseline check
  --no-sandbox            Bypass Docker Fortress isolation
  --no-arsenal            Skip heuristic Arsenal probes
  --insecure              Bypass SSL/TLS verification
  --setup-local-llm       Auto-provision local Ollama model
  --results-dir PATH      Output directory for deliverables (default: cog-ai-results)

2. secagent vault — Key Integrity Manager

secagent vault --validate --env .env

3. secagent keyhacks — Credential Audit

secagent keyhacks ./src --rate-limit 10.0

5. secagent mcp — Model Context Protocol Server

secagent mcp

6. secagent playbook — Declarative Methodology Execution

secagent playbook ./playbooks/web-api.yaml --target example.com

7. secagent replay — Proof Capsule PoC Replayer

secagent replay ./cog-ai-results/capsules/proof_sqli_123.json

5. secagent memory — Aura Cognitive Memory Control

secagent memory [options]

Options:
  --target, -t TEXT       Filter cognitive memory signals by target domain
  --purge-decay           Apply memory decay algorithms & remove zero-confidence patterns

6. secagent hardware — Hardware Detection

secagent hardware

6. secagent update — Intelligence Synchronization

secagent update

Sample Deliverables & Deliverable Schemas

1. Executive Markdown Deliverable

#  Mission Intelligence Deliverable: example.com

## Executive Summary
SecAgent executed an autonomous security audit against target domain `example.com`. 
A total of **3 validated vulnerabilities** were extracted with zero false positives.

### Key Finding Matrix
| Severity | Vulnerability | Location | Confidence | CWE |
| :--- | :--- | :--- | :---: | :--- |
| **CRITICAL** | SQL Injection | `/api/users?id=` | 95% | CWE-89 |
| **HIGH** | Reflected XSS | `/search?q=` | 90% | CWE-79 |
| **HIGH** | Insecure Direct Object Reference | `/api/users/102` | 85% | CWE-639 |

---

## Technical Finding Details

### 1. SQL Injection (`CWE-89`)
- **Target URL**: `https://example.com/api/users`
- **Method**: `GET`
- **Payload**: `' UNION SELECT NULL--`
- **Proof Signal**: `You have an error in your SQL syntax near '1'`

2. Machine-Readable JSON Schema (target.json)

{
  "target": "example.com",
  "domain": "example.com",
  "findings": [
    {
      "type": "sqli",
      "severity": "critical",
      "url": "https://example.com/api/users",
      "payload": "' UNION SELECT NULL--",
      "confidence": 0.95,
      "cwe": "CWE-89",
      "poc_url": "https://example.com/api/users?id=' UNION SELECT NULL--"
    }
  ]
}

Project Directory Layout

SecAgent/
├── python-agents/                     # Primary Python AI Agent Swarm & CLI Engine
│   ├── pyproject.toml                 # Package configuration, scripts, & dev dependencies
│   └── secagents/
│       ├── agents/                    # Autonomous Specialist Agent Swarms
│       │   ├── api_security.py        # REST/GraphQL vulnerability prober & BOLA checker
│       │   ├── base.py                # BaseAgent class with confidence scoring & standard formatting
│       │   ├── keyhacks.py            # Local asset secret & credential leak scanner
│       │   ├── planner.py             # Phase decomposer, resource allocator, risk identifier
│       │   ├── recon.py               # Active DNS prober, httpx crawler, parameter discovery
│       │   ├── report.py              # Markdown deliverable generator & finding summarizer
│       │   ├── supervisor.py          # Action intent classifier & swarm director
│       │   ├── validator.py           # Proof-of-Concept verification & replay engine
│       │   ├── web3_security.py       # Smart contract auditor (EVM & Solana vulnerability prober)
│       │   └── web_security.py        # Web vulnerability scanner (SQLi, XSS, SSTI, LFI, SSRF, RCE)
│       ├── armada/                    # Swarm Handlers & Orchestration Tasks
│       │   ├── handlers.py            # Task handler registration & routing
│       │   └── swarm.py               # Parallel agent swarm runner
│       ├── arsenal/                   # Heuristic Exploitation Probes
│       │   └── exploits.py            # Arsenal payload probes & secondary validation
│       ├── core/                      # Core System Infrastructure
│       │   ├── memory.py              # Persistent memory storage
│       │   ├── orchestrator.py        # Task DAG orchestrator & circuit breaker tracker
│       │   ├── skill_manager.py       # SKILL.md parser & skill registration engine
│       │   └── workers.py             # Async worker pool & queue manager
│       ├── crucible/                  # Verification & Regression Framework
│       │   ├── regression.py          # Test suite regression tracker
│       │   └── validation.py          # Live PoC replay & linear-scaling time verifier
│       ├── engine/                    # Context & Graph Processing
│       │   ├── caveman.py             # Token-efficient prompt compressor
│       │   ├── ci_notifier.py         # CI/CD webhook & alert dispatcher
│       │   └── memory_graph.py        # Graph-based vulnerability relationship store
│       ├── fortress/                  # Isolation & Sandboxing
│       │   └── sandbox.py             # Docker Fortress execution isolation checks
│       ├── hermes/                    # Retrospective Memory Engine
│       │   ├── retrospective.py       # Post-scan analysis & learning feedback loop
│       │   └── store.py               # Hermes persistent memory store
│       ├── infra/                     # Operational Safeguards & Integrity
│       │   ├── preflight.py           # System dependency & prerequisite verifier
│       │   └── scope.py               # Fail-closed target domain scope enforcer
│       ├── intel/                     # Threat Intelligence Integration
│       │   ├── chaos_client.py        # ProjectDiscovery Chaos API integration
│       │   └── shodan_client.py       # Shodan host intelligence integration
│       ├── llm/                       # LLM Provider Abstraction
│       │   ├── consensus.py           # Multi-provider agreement & consensus engine
│       │   └── omni.py                # Unified LLM client (OpenAI, Anthropic, Gemini, Groq, DeepSeek)
│       ├── modules/                   # Deterministic Detection Signatures
│       │   └── cve_checks.py          # 31+ zero-false-positive CVE signatures & check definitions
│       ├── operational/               # Environment & System Integrity
│       │   └── integrity.py           # OS baseline security update & tool updater
│       ├── pipeline/                  # Unified Scan Execution
│       │   └── runner.py              # ScanPipeline orchestrator (Scope -> Preflight -> Swarm -> Report)
│       ├── remediation/               # Auto-Fixing & Patching
│       │   ├── patcher.py             # Auto-remediation code patcher
│       │   └── reporter.py            # Final report formatter & deliverable generator
│       ├── vault/                     # Operational Secret Storage
│       │   └── env_loader.py          # Environment key loader & live API validation
│       ├── whichllm/                  # Hardware-Aware Model Provisioning
│       │   └── hardware.py            # Local GPU/CPU detector & Ollama auto-provisioner
│       └── cli.py                     # Rich CLI Terminal User Interface & subcommand parser
├── go-services/                       # High-Performance Go Microservices
│   ├── recon/                         # High-Speed Recon Engine
│   │   ├── crawler.go                 # Concurrent web page crawler & link extractor
│   │   ├── httpprobe.go               # Multithreaded HTTP/HTTPS service prober
│   │   ├── params.go                  # GET/POST parameter discovery engine
│   │   ├── recon_test.go              # Unit test suite for Go recon
│   │   └── subdomain.go               # Multithreaded DNS brute-force enumerator
│   ├── scanners/                      # Network Scanners
│   │   ├── portscan.go                # Fast TCP port scanner
│   │   └── syn.go                     # Raw SYN packet scanner
│   └── cli/                           # Go CLI Binary Build Entrypoint
│       └── cmd/main.go                # Go CLI entrypoint
├── rust-core/                         # Rust Engine & Priority Task Scheduler
│   ├── Cargo.toml                     # Rust package manifest & dependencies
│   └── src/
│       ├── engine.rs                  # Core Rust execution engine
│       ├── event_bus.rs               # Lock-free event dispatching bus
│       ├── main.rs                    # Rust engine binary main entrypoint
│       ├── policy.rs                  # Security policy evaluation engine
│       ├── scheduler.rs               # Microsecond-latency task priority queue
│       └── state.rs                   # System state tracker
├── skills/                            # Modular Hunting Methodologies
│   ├── bb-methodology/                # Bug bounty methodology guidelines
│   ├── PromptInjection/               # LLM prompt injection audit playbooks
│   ├── Recon/                         # Advanced reconnaissance techniques
│   └── WebAssessment/                 # OWASP Top 10 assessment workflows
├── tests/                             # Unified Test Suite
│   └── unit/
│       ├── test_agents_complete.py    # Unit tests for python agent swarms
│       ├── test_comprehensive.py      # System orchestrator & worker tests
│       └── test_cve_checks.py         # Signature & CVE verification tests
├── docker-compose.yml                 # Production background microservices configuration
├── Makefile                           # Unified build, test, and execution targets
├── installer.py                       # Automated deployment & installation engine
├── update.py                          # Intelligence & framework sync tool
├── SKILL.md                           # Master hunting knowledge base reference
├── LICENSE                            # MIT License distribution terms
├── SECURITY.md                        # Security policy & vulnerability reporting
└── README.md                          # Master documentation & architecture guide

Troubleshooting & Operations Guide

Common Operational Scenarios

1. Bypassing Docker Sandbox Isolation

If Docker is not running or sandbox isolation is not required:

secagent scan --target example.com --no-sandbox

2. Provisioning Offline Local LLM Models

When running in air-gapped environments without cloud API keys:

secagent scan --target target.local --setup-local-llm

3. Resolving SSL Certificate Warnings

For internal staging environments with self-signed SSL certificates:

secagent scan --target https://staging.local --insecure

Contributing & Security Policy

Contributing

1. Fork the repository on GitHub.
2. Create your feature branch (git checkout -b feature/advanced-cve-check).
3. Verify test coverage (pytest) and linter compliance (ruff check python-agents).
4. Commit your changes and submit a Pull Request.

Reporting Vulnerabilities

To report a security vulnerability within SecAgent itself, please review our SECURITY.md for responsible disclosure guidelines.

License

Distributed under the MIT License. See LICENSE for details.