Loadout
Forensic Training Toolkit
Realistic forensic training, openly synthetic by design.
Loadout places openly-synthetic text messages, call logs, contacts, and photos onto lab-owned training devices, each backed by a documented ground-truth manifest and removable, with read-back confirming the scenario data is cleared between exercises.
Request a capability briefingby
with
The problem
Forensic training lacks realistic scenario data
DOMEX and mobile-device forensic training programs rely on trainees extracting and analyzing artifacts from a phone. Without realistic scenario data on that phone, the training is abstract. Instructors have no reliable way to place a coherent set of text messages, call logs, contacts, and photos onto a training device ahead of a practical exercise.
Loadout solves that. It places openly-synthetic scenario data onto lab-owned training devices so trainees can practice against lifelike artifacts, backed by a documented ground-truth manifest the instructor controls.
Capability
Openly-synthetic scenario data for forensic training
Loadout places openly-synthetic text messages, call logs, contacts, and photos onto lab-owned training devices, each backed by a documented ground-truth manifest and removable, with read-back confirming the scenario data is cleared between exercises.
| Artifact | Rooted | Unrooted |
|---|---|---|
| Contacts | Supported(ADB) | Supported(ADB) |
| Call logs | Supported(ADB) | Supported(ADB) |
| Photos | Supported(ADB) | Supported(ADB) |
| Text messages (SMS) | Supported(ADB) | Supported(on-device app) |
| Picture messages (MMS) | Supported(ADB) | Supported(on-device app) |
On unrooted, lab-owned devices, text and picture messages are written by the on-device companion app, because ADB cannot write them without root.
Expanding artifact coverage
- Location historyAvailable July 2026
- Browsing historyAvailable July 2026
- App usage historyAvailable August 2026
- Third-party chat apps (WhatsApp, Signal, Telegram, Messenger)Planned
- Email accounts and messagesPlanned
- iOS device supportPlanned
Persona Studio
Persona-driven scenarios
Every Loadout scenario is persona-driven. Each persona is configured for region, geofence radius, characteristics, and behaviors, so the artifacts on the device tell a coherent story.
Configure
Set a persona's region, geofence radius, timeframe, characteristics, and behaviors.
Author
Add your own media, contacts, text and picture messages, and call logs.
Generate
Generate coherent activity from persona characteristics using on-premise open-weight models. Airgap-friendly, with no external calls.
Localize
Author region-aware personas with localized place and time metadata. Multi-language authoring is on the roadmap.
Generation runs on-premise with
Ollama
Llama
Mistral
Trademarks are the property of their respective owners.
Screenshots
Loadout in operation
Persona authoring
123- 1Pick an archetype
- 2Set the region and timeframe
- 3Generate the persona
Connect
Device connection and status
Author
Persona authoring and configuration
Batch
Batch provisioning across devices
Read-back verification
Gate A read-back verification results
How it works
Four-step lifecycle
01
Author
Compose a region-aware persona with controlled artifact counts, geofences, and time windows.
02
Provision
Install all five artifact types on the device in a single operation.
03
Verify
Loadout reads every artifact back from the device and diffs it against the documented manifest. Zero failures required.
04
Remove
Clean teardown between exercises. Every injected artifact is tracked, removed, and verified by read-back.
Hybrid provisioning
Loadout supports unrooted, lab-owned devices through a hybrid method: contacts, call logs, and photos are provisioned over ADB, and text and picture messages are written by an on-device companion app. This delivers all five artifact types without rooting the device.
Program of Record
Train for the tools you field
Loadout writes each artifact into the device's native Android content providers, so Program-of-Record forensic tools parse it through their standard extraction workflows. Trainees practice the same extraction process they use in the field, against openly-synthetic artifacts that each carry a documented ground-truth manifest.
Tool-ready artifacts
Contacts, call logs, text and picture messages, and photos land in the real on-device providers, so forensic tools used in the field, such as MSAB XRY and Magnet GrayKey, can parse them through their normal extraction process.
Parse fidelity, checked
Before a device reaches a trainee, Loadout checks artifact parseability with ALEAPP, an open-source forensic parser that reads the same on-device schemas the field tools rely on. ALEAPP serves as an open proxy for Program-of-Record parsing; validation against the field tools themselves is a separate step.
MSAB, XRY, Magnet, and GrayKey are trademarks of their respective owners. ALEAPP is an independent open-source project. Loadout is not affiliated with, endorsed by, or integrated with these products.
Operator surfaces
Interfaces and connections
Interfaces
- Desktop DashboardAvailable now
- Command-line interfaceAvailable now
- Android companion appAvailable now
- Hosted APIAvailable July 2026
Connections
- Direct USBAvailable now
- Wi-Fi / wireless ADBAvailable now
- WebUSB in-browserAvailable July 2026
Trust and safety
Responsible use, by design
Loadout is built for controlled training environments. Every design decision prioritizes transparency, containment, and clean removal. The following principles are hard-coded into the product, not optional settings.
Openly-synthetic by design
Every artifact is openly-synthetic scenario data. A documented ground-truth manifest ships with each persona package, recording exactly what was placed, where, and when.
Training devices only
Loadout targets lab-owned training devices managed by the instructor cadre. It is not designed for, and must not be used on, third-party, evidentiary, or personal devices.
Clean teardown
Clean teardown between exercises. Loadout records every artifact it injects in a ground-truth ledger and removes it when an exercise ends, so scenario data does not carry into the next exercise. Removal is verified by read-back.
Accessible by standard
The site is built to conform to Section 508 and WCAG 2.1 AA, verified on every build. The desktop Dashboard and operator tooling are engineered to the same standard; conformance is self-assessed, and a VPAT is available on request.
Loadout is intended for use on training devices within lab-owned, instructor-controlled environments. It is not for use on evidentiary, personal, or third-party devices. Any use outside a supervised training context is outside the intended scope of the product.
Deployment
Deployment options
Loadout runs on an operator workstation, fully offline and airgap-friendly, and deploys as hardened containers or to AWS GovCloud for local, remote, and cloud environments.
- Local, offline operationAvailable now
- Python core, no proprietary runtimeAvailable now
- Containerized images for local, remote, and cloudAvailable now
- Hardened container images built on Platform One IronBank base imagesAvailable now
- Cloud deployment for AWS GovCloud (containers and serverless)Available now
Built with
Python
Docker- AWS GovCloud
- Platform One IronBank
Trademarks are the property of their respective owners. Their appearance indicates technical compatibility or base-image lineage only, and does not imply endorsement, partnership, or approval.
Contact
Request a capability briefing
Loadout is delivered through an Accelera Solutions engagement, not as a self-serve product. To discuss your training requirements, request a capability briefing and a member of the team will follow up.
Request a capability briefingbywith