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QtRecon follows a Model-View-Controller (MVC) architectural pattern to separate concerns and maintain clean code organization.

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MVC pattern

The application is structured around three primary layers:

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Controller

The Controller class serves as the central orchestrator of the application. It manages:
  • Application initialization and setup
  • Communication between models and views
  • Job execution and management
  • Database operations coordination
  • Configuration loading
core/controller.py
class Controller:
    APPLICATION_VERSION = "1.7.2"
    autosave_timer = QTimer()
    progression_bar_timer = QTimer()
    screenshot_mgr = None

    def __init__(self, ui):
        self.ui = ui
        self.view = View(ui, self)
        self.setup_initial_project()
        self.view.setup_ui()
        self.view.connect_slots()

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View

The View class handles all UI-related operations, including:
  • Rendering the graphical interface
  • Managing user interactions
  • Updating display elements
  • Creating and managing tabs

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Database

The Database class provides a static interface to the SQLite database:
core/database.py
class Database:
    database = None
    current_savefile = ""
    has_unsaved_data = False

    @staticmethod
    def init_DB():
        Database.database = sqlite3.connect(':memory:', check_same_thread=False)
        Database.database.row_factory = lambda C, R: {c[0]: R[i] for i, c in enumerate(C.description)}
QtRecon uses an in-memory SQLite database during runtime, which is exported to disk when you save your workspace.

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Data models

QtRecon implements four primary data models that extend QAbstractTableModel to provide data to Qt’s view components:

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HostModel

Manages host information and related operations:
core/models/hostmodel.py
class HostModel(QAbstractTableModel):
    data_updated = Signal(int, int)  # Displayed number of hosts / all hosts

    def __init__(self, parent, controller):
        QAbstractTableModel.__init__(self, parent)
        self.controller = controller
        self.hosts = []
        self.headers = ['host_id', 'OS', 'IP', 'Hostname']
Key responsibilities:
  • Host filtering and searching
  • CRUD operations on hosts
  • Managing host metadata (OS, hostname, IP, pwned status)
  • Creating and updating external tabs
  • Host highlighting and color coding

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JobModel

Handles job execution and lifecycle management:
core/models/jobmodel.py
class JobModel(QAbstractTableModel):
    def __init__(self, parent, controller):
        QAbstractTableModel.__init__(self, parent)
        self.ui = parent
        self.controller = controller
        self.jobs = []
        self.jobs_objects = dict()  # {(int) job_id: (Job) job}
Key responsibilities:
  • Creating and tracking jobs (scans, attached programs)
  • Managing job states and status updates
  • Handling nmap scan execution
  • Processing job completion and errors

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CredsModel

Manages credential storage and parsing:
core/models/credsmodel.py
class CredsModel(QAbstractTableModel):
    data_updated = Signal(int)  # Number of credentials

    def __init__(self, parent):
        QAbstractTableModel.__init__(self, parent)
        self.ui = parent
        self.creds = []
        self.headers = ['host_id', 'id', 'IP', 'Hostname', 'Type', 'Domain', 'Username', 'Password']
Key responsibilities:
  • Storing and retrieving credentials
  • Parsing credentials from various formats (secretsdump, user:password, user:hash)
  • Filtering and sorting credential data
  • Associating credentials with hosts

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LogModel

Manages application logging:
core/models/logmodel.py
class LogModel(QAbstractTableModel):
    def __init__(self, parent):
        QAbstractTableModel.__init__(self, parent)
        self.ui = parent
        self.logs = []
        self.headers = ['id', 'Date', 'Type', 'Log']
Key responsibilities:
  • Recording application events
  • Storing runtime, info, warning, and critical logs
  • Providing log history access

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Main components

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Configuration management

The Config class handles all configuration-related operations:
core/config.py
class Config():
    config = None
    config_template_filename = "conf.json.example"
    config_filename = "conf.json"
    config_root_path = ""
See Configuration for detailed information.

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Job execution

Jobs are executed as QProcess instances and can be:
  • Attached: Output is captured in tabs within the application
  • Detached: Programs run independently in external terminals
  • Privileged: Executed with elevated permissions using graphical sudo

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Nmap integration

Nmap scans are managed through the JobModel with special handling:
core/models/jobmodel.py
def new_scan(self, target: str, ports: str, type: str, speed: str, additional_args: str, 
             skip_host_discovery: bool, version_probing: bool, default_scripts: bool, 
             os_detection: bool, tcp_and_udp: bool):
    # Builds nmap command with output files
    arg_nmap_output = ['-oX', f"{self.nmap_output_folder}/scan-{job_id}.xml",
                       '-oN', f"{self.nmap_output_folder}/scan-{job_id}.nmap"]
Nmap scans that require privileged access (SYN scans, OS detection, UDP scans) will prompt for elevated permissions using the configured graphical sudo tool.

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Data flow

  1. User interaction → View captures input
  2. View → Controller processes the request
  3. Controller → Model updates data
  4. Model → Database persists changes
  5. Model → Emits signals to notify views
  6. View → Updates UI to reflect changes
This architecture ensures separation of concerns and makes the codebase maintainable and testable.

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