Obsidian AI Security: Check Plugins and Data Leaving Your Vault
An AI plugin or connected assistant adds a new access path to your Obsidian notes. Check what it can read, where information goes, and who approved that sharing before using real project material.
Updated 5 min read
Obsidian AI security depends on the complete route from your local notes to the plugin, assistant, and any outside service processing them. Keeping a vault on your device does not mean information stays there once you add software that can read files and make network requests.
Review each connection before giving it real work. fenbs can retain your approved sharing rules and the project context cleared for connected assistants, while your original notes stay in the place you choose. It does not inspect or control an Obsidian plugin.
What changes when AI can access your notes?
A local note and a request sent to an AI service have different exposure. Obsidian’s storage documentation (opens in a new tab) describes a vault as a folder of plain text files on your local file system. An additional tool can introduce its own reading, copying, indexing, or transmission behavior.
Draw the route in ordinary words: selected note, plugin, provider, response, saved output. Add any intermediate service the plugin uses. Do not assume that selecting one paragraph establishes what software can access in the background; verify the implementation and configuration.
The neighboring guides cover plugin choices, AI setup, building an Obsidian AI brain, exporting notes for AI, and cost questions. Here, the decision is whether a specific connection is acceptable for a specific set of notes and actions.
Does a community plugin have limited permissions?
Do not assume it does. Obsidian’s plugin security guidance (opens in a new tab) says it cannot reliably restrict plugins to particular permission levels; plugins inherit the app’s access. Its examples include accessing files, connecting to the internet, and installing additional programs.
Restricted mode prevents community plugins from running. Turning it off is a trust decision about the software you install. A plugin’s description of a narrow purpose is useful information, but it is not proof that the application enforces an equally narrow permission boundary.
For sensitive work, review the plugin’s source or have someone qualified assess it. Check the author, the update route, network destinations, and any extra software it requires. Obsidian itself recommends an independent security audit before using a community plugin with sensitive data.
A separate test vault helps keep your evaluation organized. It does not, by itself, confine a plugin’s access to that folder. The broader AI assistant security guide explains why instructions and technical access need separate checks.
Which information might leave the vault?
Inspect the features you intend to use and the features enabled by default. A chat command, whole-vault search, attachment reader, and background indexing option can have different data flows. A provider choice in one settings screen may not describe every component involved.
| Area | Question to resolve | Evidence to keep |
|---|---|---|
| Input selection | Does it send a selection, full notes, linked notes, or attachments? | Documentation and a test using invented notes. |
| Background work | Does it build a search index or process notes without a chat request? | Enabled settings and observed behavior. |
| Destinations | Does information go directly to your provider or through another service? | Named services and documented network routes. |
| Outputs | Where are prompts, responses, and generated notes saved? | Storage settings and deletion instructions. |
| Credentials | How is the provider credential stored, and who can use it? | The documented storage method and your account controls. |
Treat unanswered questions as unresolved approval conditions. “We could not find a retention statement” is a useful finding; “it probably deletes everything” is a guess. Preserve links to the evidence and the configuration reviewed so someone else can repeat the assessment.
Whose privacy terms apply to an AI request?
Obsidian’s privacy policy (opens in a new tab) explains its own apps and services, including the distinction between local app data and optional services. Do not extend that policy into a promise about a community plugin author or an outside AI provider.
Read the terms for the actual service receiving the request and the account route you use. Establish whether submitted information may be used for training, how long it is retained, who can access it, and what deletion covers. Check any intermediary separately; a provider’s answer does not automatically describe the plugin’s own service.
Local processing also needs review. Verify that the chosen setup performs the relevant work locally, then examine file access, logs, and other network behavior. A local model can reduce one transfer route without answering every security question about the surrounding software.
Keep the conclusion specific: “Approved for public research notes using this configuration” is more useful than “Obsidian AI is secure.” The access review guide provides a wider structure for documenting that bounded decision.
How can you test the setup before real work?
Use invented notes with recognizable phrases, a harmless attachment, and a link between two pages. Exercise each feature you plan to approve. Compare the visible behavior with the documentation; have a qualified reviewer inspect requests when sensitive information or broad permissions make that necessary.
- List the permitted task and information before opening the test. Decide what successful behavior would look like.
- Try a selection-only request and a broader search separately. Check what the feature says it reads and sends.
- Review whether generated responses contain material outside the intended selection or introduce unsupported claims.
- Test a stop condition, such as a request to include an unapproved attachment, and review the available access controls.
- Record what you observed, what remains uncertain, and who can approve use with real notes.
The NIST AI Risk Management Framework (opens in a new tab) is voluntary guidance for managing AI risks. A practical application here is to make the use case, evidence, and remaining uncertainty visible before someone accepts the risk.
What sharing rules should survive the review?
Record the approved content types, allowed services, excluded material, required reviewer, and reasons to reopen the decision. A plugin update, new provider, or request to process a more sensitive collection should trigger another look. Approval for public reading notes should not silently expand to employee records or client files.
For example, a design studio might approve an assistant for published project references while keeping private client notes out. The assistant needs the approved project summary and the sharing boundary, not the studio’s entire vault. Use fenbs Decisions and rules to keep that human-approved boundary available to its connected assistants.
Share approved context with a clear boundary
Keep the sharing decision, its owner, and unresolved review tasks together in fenbs. Add only the project context cleared for those assistants, then ask them to read the rules before using it. fenbs does not connect directly to Obsidian or enforce a plugin’s network behavior.
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How to do this with fenbs
- Create a free account, free for one person with no credit card, and add the project that needs approved AI context.
- Record the person’s sharing decision in Decisions and rules, including permitted material, excluded information, and the configuration reviewed.
- Add cleared project facts as AI context notes and create tasks for unanswered access or data-handling questions. Keep sensitive source material out of the shared record.
- Use the integration guide for your supported assistant to connect it to fenbs. Ask it to read the rules and explain which project information it may use before continuing.
- Save progress and record lessons when a review finds a problem. Ask the responsible person to decide any change to the approved boundary.
fenbs fits the decision and handoff record. If you need automatic monitoring of plugin traffic, device isolation, or controls that prevent a file from leaving your computer, use the appropriate security tools and qualified review. More AI governance guides cover the people and review process around those controls.