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Building your own Android keyboard can give you control over its code and data flows, but it does not make text entry inherently private: a keyboard must handle what you type and may read nearby text to support editing. The privacy difference depends on what the particular keyboard stores, logs, or sends—and those claims need to be checked against the actual build.
What an Android keyboard can access
An Android keyboard is an app that provides an input method service. The service extends InputMethodService, declares itself in the app manifest, and presents an input view; it may also show a candidate view for suggestions. When you type in another app, the keyboard communicates with that app through Android’s InputConnection API. That connection can provide text before or after the cursor, which enables ordinary editing functions such as moving through or correcting text.
This is a sensitive trust boundary, not evidence that every keyboard can freely read every piece of data on a device. The API access serves text entry and editing; what a keyboard does with the text it handles depends on its implementation. Android’s guide also tells developers to handle password fields carefully: hide password text in both the input and candidates views, and do not store passwords. See Android’s guide to creating an input method.
Does Gboard collect what I type?
The available evidence does not support the blanket claim that Gboard sends every typed word to Google. A 2022 dissertation by Kamil Przepiorowski at Trinity College Dublin examined network traffic and reverse-engineered telemetry in particular versions of Gboard, SwiftKey, and AnySoftKeyboard. For the Gboard and SwiftKey versions studied, it reported timestamped usage metadata—including the app in which the keyboard was used, input method, language, word length, entry and deletion counts, and timing—with identifiers that could link data to a handset. The study did not observe the actual typed content or the frequency of individual characters being transmitted.
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That result is bounded by the versions and methods examined; the dissertation says its reverse engineering of Gboard was not exhaustive. It is not a current audit of every release or a guarantee about all traffic. The dissertation is available from Trinity College Dublin.
Separately, Google researchers described Gboard’s federated-learning design in a June 2023 technical paper. They said raw training data, such as typing content, can remain on a device while model updates are produced using secure aggregation and differential privacy techniques. The paper also says users can configure machine-learning use in Gboard settings. This is Google’s account of its model-training mechanisms, not a comprehensive independent audit of all Gboard traffic, telemetry, or current versions. Read the 2023 paper on Gboard’s federated learning.
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Taken together, these sources answer different questions: the dissertation reports what its authors observed in specific versions, while Google’s paper explains a stated privacy design for model training. Neither establishes what every current Gboard build sends in every situation.
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A custom keyboard can put you in control of the keyboard’s source code, dependencies, storage choices, and network features. If its intended functions can run locally, you can design it without analytics or network access. You can also decide whether to keep a personal dictionary on-device, how long to retain text in memory, and whether any diagnostic systems could capture sensitive input.
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But writing the keyboard yourself is not proof that it is offline, that it never retains text, or that all dependencies behave as expected. Those are properties to verify in the specific app and build. And a locally running keyboard still handles sensitive text as part of its core job.
Design for less data from the start
Begin with an inventory of every place text or related information could go. Include text read around the cursor, temporary in-memory state, personal dictionaries, logs, crash reports, third-party libraries, and any network requests. For each feature, ask whether it needs that data and whether it can work without sending it elsewhere.
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- Minimize collection. Avoid collecting text, identifiers, and usage metrics unless a feature genuinely requires them.
- Keep local features local. If prediction, autocorrect, or dictionary functions are meant to work offline, avoid adding sync or network behavior that is not necessary to deliver them.
- Protect sensitive fields. Do not display or retain password text in input or candidate views.
- Keep diagnostics clear of input. Ensure logging and crash reporting cannot capture text supplied by another app.
- Explain any collection. If metrics are necessary, tell users what is collected and why, and seek informed consent.
The Android Open Source Project’s privacy guidance says, “If at all possible, don’t collect metrics.” When metrics are necessary, it recommends explicit, informed, meaningful consent; collecting only what is needed for reliability; avoiding identifiable or potentially sensitive data; and aggregating and anonymizing where possible. It also says, “Apps or system services shouldn’t log data provided from third-party apps that might include sensitive information.” The guidance was last updated September 30, 2026. See the AOSP privacy and security best practices.
How to check a keyboard’s privacy claims
Source code, a privacy disclosure, and observed network behavior each reveal different things. Reviewing code can show intended behavior, but does not by itself establish what a published build does. Watching network traffic can show observed connections during the test, but cannot prove that no data is ever collected under other conditions. For a meaningful check, examine the specific app build and device rather than relying on a general claim.
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- Inspect the manifest. Check the declared input-method service, permissions, and any other services or components.
- Review dependencies and SDKs. Identify libraries that may add analytics, crash reporting, dictionary sync, or networking.
- Search the code. Look for logging, telemetry, crash-reporting calls, network requests, and code that persists text or cursor context.
- Review local retention. Determine what is kept in memory or stored on-device, including dictionary entries and diagnostic data.
- Read the privacy disclosure. Compare its statements with the app’s features and implementation.
- Observe network behavior on the build you use. Capture traffic in relevant use cases and note the device, app version, and conditions. Treat the result as an observation of those tests, not proof of universal absence.
How to choose between keyboards
“Open source” tells you that source code is available; by itself, it does not establish that the installed build matches that source, that its dependencies are harmless, or that the app has been independently checked. A 2022 study reported no observed telemetry collection or sharing by the version of AnySoftKeyboard it examined. Przepiorowski’s dissertation summarized that finding as: “AnySoftKeyboard, the open-source alternative which was studied, does not collect or share any data at all.” The qualification matters: it is a finding about the studied app and method, not a guarantee about later releases.
Whether you are considering a commercial keyboard, an open-source one, or your own build, compare the properties that affect your use:
- Whether typed text itself leaves the device.
- Whether metadata or identifiers are transmitted.
- Which features work offline.
- Prediction and autocorrect quality for your languages.
- Language and layout support.
- How password fields are handled.
- How often the keyboard is maintained and updated.
- Whether source and build processes are reproducible.
- Whether privacy claims have been independently checked, and what versions and behaviors that check covered.
How to build a custom Android keyboard
Android’s official input-method guide is the practical starting point. It covers the service, manifest declarations, input and candidate views, and communication with the focused app. Building a working keyboard is separate from establishing its privacy: the data inventory and verification steps above are still necessary for any implementation.
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