iTX TechnologiesStorage tools

FlashMaster

Decode memory part numbers and explore Flash IDs and chip data in your browser.

Actively maintained

Full and Nano include the engine for offline lookups; Pico requires a remote service. Market data and other online content remain network-dependent.

Concept illustration
Brand
iTX Technologies
Platforms / runtime
  • Web
Technologies
  • Vue
  • JavaScript
  • Web Workers

About the project

A part number, a short package marking, or a string of Flash ID bytes is often only the starting point for identifying a memory chip. You first need to determine the memory type and find the relevant naming rules. FlashMaster brings these lookups into one browser workbench for engineers, repair technicians, and hardware enthusiasts who need to check chip information.

Powered by fdnext, it turns part-number rules and database records into readable specifications. You can use the web application, choose an offline file, or connect it to a service you host. Its job is to interpret supplied part numbers and identifiers; it does not run read or write tests on connected hardware.

  1. Part numbers and IDs

    Decode memory part numbers and NAND Flash IDs into structured specifications.

  2. Chip-data search

    Search by part number, FBGA code, package marking, or Flash ID.

  3. Browser workbench

    Copy results, switch languages and themes, or use an offline edition with the engine included.

Start with the identifier you have

With a complete part number, start by decoding it. If you have only a partial number, an FBGA code, or a package marking, search for candidates and inspect the relevant entries. Use the ID lookup for a NAND Flash ID. Part numbers and IDs provide different kinds of information and should not be treated as interchangeable.

Results are organized into compact field groups so you can inspect parameters and related information together. Copy a brief summary or the full result when keeping records or discussing a chip with a colleague. Keep the original query alongside the copied information so it can be checked again later, rather than retaining only an isolated capacity figure.

Match offline use to your environment

Start with the web application, which can be installed on your device in supported browsers. After a successful first visit and caching of the required resources, the embedded engine can handle offline lookups. Offline caching requires a standard production build served over HTTPS or localhost. Try a lookup with the network disconnected after installation to check that the resources are ready.

For a workstation without network access, choose a single-file HTML edition that includes the engine and try it offline in the target browser before relying on it. A standard web build requires a web server; it is not equivalent to the single-file edition you can open directly. Remote queries and other network-dependent content do not become offline features simply because the local engine is available.

Choose an edition that fits

Downloads lead to GitHub Releases; consult the release page for the files available. First decide whether decoding should happen locally or on a server, then consider whether you need additional online content. Teams can also host the static web application themselves or connect the frontend to a centrally maintained fdnext service.

  • Full

    The full single-file application includes the decoding engine. Its market-data content still needs a network connection.

  • Nano

    Keeps local decoding while removing market-data features and analytics code for a leaner offline setup.

  • Pico

    Does not include the engine. Queries always go to a remote HTTP service, which must be reachable.

Use results in the right context

Coverage depends on the rules and resources in the version you use. Recognizing a part number does not mean every field is available. Where information is missing or several candidates remain, check the complete marking and the original specifications. A lookup result is not a test of a chip’s authenticity, health, or measured performance.

Research background

ETHEREALM RESEARCH

FlashMaster and fdnext: from engine to workbench

Explore how FlashMaster turns chip decoding and search into a usable interface, and the choices behind its online, embedded, and offline editions.

The article uses data as of June 28, 2026, covering capabilities and future directions at that time. Consult the project documentation for current functionality.

Read research background (Chinese) (opens in a new tab)