Files
mvt/docs/development/index.md
T
Donncha Ó Cearbhaill 104ffb167f Skip modules with unavailable dependencies instead of aborting the run (#895)
A module declaring a dependency its command does not provide made
_ordered_modules() give up on the whole run, so a single wrong declaration
in a module scoped to several commands turned a forensic analysis into
zero executed modules with one warning to explain it.

Drop only the modules that cannot run: the one with the unavailable
dependency, and anything depending on it. Each gets its own warning naming
the module missing a dependency and the dependency it is missing, and the
remaining modules run in the same stable topological order as before. A
cycle in the dependency graph is still a programming error and still stops
the run.
2026-08-27 14:47:14 +02:00

7.8 KiB

Development

The Mobile Verification Toolkit team welcomes contributions of new forensic modules or other contributions which help improve the software.

Local environment

MVT uses uv for dependency management. To install the project and development dependencies from the locked environment, run:

make install

Testing

MVT uses pytest for unit and integration tests. Code style consistency is maintained with ruff and mypy. All can be run automatically with:

make check

Run these tests before making new commits or opening pull requests.

Module dependencies

Modules can require other modules to run first by declaring their classes in dependencies. The command runner uses a stable topological ordering, so the existing module list order is preserved wherever dependency constraints allow.

class DependentModule(MVTModule):
    dependencies = (PrerequisiteModule,)

    def run(self):
        prerequisite_results = self.get_dependency_results(PrerequisiteModule)

Selecting a single module also runs its transitive dependencies.

A module can only depend on modules the command it runs in also has. When a declared dependency is not among them, the command logs a warning naming the module and the missing dependency, skips that module and everything depending on it, and runs the rest of the analysis. Selecting such a module with --module therefore leaves nothing to run, which the warning explains.

A cycle in the dependency graph is a programming error rather than a configuration problem: the command logs a warning and runs no modules at all.

Custom modules

Module-running check-* commands can load custom modules from Python files that are not installed as part of MVT. Load one file with:

mvt-ios check-backup --load-module ./example_module.py --output ./out ./backup

You can also load a folder. MVT loads non-hidden top-level *.py files in sorted order and skips __init__.py:

mvt-ios check-fs --load-module ./custom_modules ./filesystem-dump

Set MVT_CUSTOM_MODULES to load a folder for every module-running command. This folder is loaded before any --load-module path:

MVT_CUSTOM_MODULES=./custom_modules mvt-android check-bugreport ./bugreport.zip

Custom modules are normal MVTModule subclasses:

from mvt.common.module import MVTModule


class ExampleCustomModule(MVTModule):
    supported_commands = (("ios", "check-backup"), ("ios", "check-fs"))
    slug = "example_custom_module"

    def run(self):
        self.results = [{"message": "custom module ran"}]

    def check_indicators(self):
        pass

    def serialize(self, result):
        return None

Use supported_commands to declare the platform/command pairs a module supports. Empty supported_commands means the module will not run and MVT logs a warning. This explicit declaration is required for every command. Supported pairs are:

("ios", "check-backup")
("ios", "check-fs")
("ios", "check-iocs")
("ios", "check-sysdiagnose")
("android", "check-backup")
("android", "check-bugreport")
("android", "check-androidqf")
("android", "check-intrusion-logs")
("android", "check-iocs")

Custom modules can depend on existing MVT module classes. Dependencies are resolved with the same ordering logic as built-in modules, and custom modules are appended after built-ins before ordering:

from mvt.common.module import MVTModule
from mvt.ios.modules.backup.manifest import Manifest


class DependentCustomModule(MVTModule):
    supported_commands = (("ios", "check-backup"),)
    dependencies = (Manifest,)

    def run(self):
        manifest_results = self.get_dependency_results(Manifest)
        self.results = [{"manifest_entries": len(manifest_results)}]

Installed module packages

Python packages can register modules so they load automatically in every module-running check-* command, without --load-module or MVT_CUSTOM_MODULES. Register an entry point in the mvt.modules group in the package's pyproject.toml:

[project.entry-points."mvt.modules"]
mvt-plugin-amnesty-custom = "mvt_plugin_amnesty_custom:get_modules"

The entry point must resolve to an iterable of MVTModule subclasses, or to a callable returning one:

from mvt.common.module import MVTModule


class PackagedModule(MVTModule):
    supported_commands = (("ios", "check-backup"),)

    def run(self):
        self.results = [{"message": "packaged module ran"}]


def get_modules() -> list[type[MVTModule]]:
    return [PackagedModule]

Installed modules follow the same rules as other custom modules: each module must declare supported_commands, and dependencies are resolved with the standard ordering logic. A broken entry point is skipped with a warning and does not prevent MVT from running. As with custom commands, installed module packages run as trusted code inside the MVT process, so install only packages from sources you trust.

For a pipx installation of MVT, inject the package into MVT's environment:

pipx inject mvt mvt-plugin-amnesty-custom

Module packages that need their own settings, such as an API key, should store them in a namespaced plugin configuration file rather than in MVT's own config.yaml.

Naming module packages

Name module packages mvt-plugin-<name> (import package mvt_plugin_<name>), and include the name of the publishing organization or author so packages from different groups do not collide: for example, Amnesty International's custom modules would be distributed as mvt-plugin-amnesty-custom with the import package mvt_plugin_amnesty_custom.

The prefix makes module packages easy to find on PyPI and keeps their import names from clashing with unrelated Python packages. It is a convention, not a technical requirement: modules load through the mvt.modules entry point regardless of what the package is called, and existing packages with other names keep working. Note that the prefix is also not a mark of authenticity — anyone can publish a package with any available name, so vet a module package and its publisher before installing it, whatever it is called.

Module logging

Modules log through self.log, and MVT names the logger for where the module came from. MVT's own modules log under their dotted path (for example mvt.ios.modules.mixed.whatsapp). Everything external is namespaced under mvt.ext to keep it visually distinct from built-in modules and isolated from MVT's internal logger tree:

  • Installed packages log under mvt.ext.<package>, with the mvt_plugin_ prefix stripped: modules in mvt_plugin_amnesty_custom log as mvt.ext.amnesty_custom.*.
  • Files loaded with --load-module or MVT_CUSTOM_MODULES log as mvt.ext.<file name>.

Auditing loaded modules

Because installed module packages load automatically, MVT records where every module came from:

  • --list-modules groups the available modules by source: MVT itself (with its version), each installed package (with its version and, when installed directly from a repository, the commit), and each file loaded with --load-module or MVT_CUSTOM_MODULES (with the SHA-256 hash of the file).
  • When a command runs with an --output folder, the command.log file records one line per module source with the source's version or hash and the list of modules loaded from it.

Profiling

Some MVT modules extract and process significant amounts of data during the analysis process or while checking results against known indicators. Care must be take to avoid inefficient code paths as we add new modules.

MVT modules can be profiled with Python built-in cProfile by setting the MVT_PROFILE environment variable.

MVT_PROFILE=1 dev/mvt-ios check-backup test_backup

Open an issue or PR if you are encountering significant performance issues when analyzing a device with MVT.