Do not assume an AI-made image, icon, sound, or animation is either forbidden or free to use. First identify the exact file and its history, then establish what source material and permissions can be documented, check the application’s own policy, and replace the asset when that evidence is insufficient. Preserve the replacement’s licensing record and verify that it still works in every supported build, theme, and package.
Why unclear provenance is a release problem
An asset’s apparent AI origin answers only one question: how it may have been produced. It does not establish who owns any included material, whether the output is protected by copyright, whether the project has permission to distribute it, or whether a transparency disclosure is required in a particular jurisdiction. Those questions must be handled separately.
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For a Linux application, the relevant rules can come from several places at once: the application’s contribution and licensing policy, the terms of the generation tool, licenses covering source material, distribution obligations, and rules that apply to the deployment jurisdiction. Linux is an operating-system family, not a single licensing authority. Guidance written for the Linux kernel does not automatically govern a desktop application, a command-line utility, or a Flatpak package.
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If you cannot identify the file, its source, the tool terms, or the rights granted for distribution, you cannot responsibly declare the asset public domain, permissively licensed, or infringing from the filename or its visual appearance. The practical response is a documented review and, when the uncertainty remains material, a replacement with evidence that can travel with the release.
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Keep four questions separate
| Question | What it asks | What answers it |
|---|---|---|
| Origin | Was the file made by a person, a generative system, or a mixture of sources? | Version history, design files, generation records, contributor notes, and other project records. |
| Copyrightability | What legal protection, if any, applies to the output or to human contributions? | The applicable law and facts in the relevant jurisdiction. This is not determined by an AI label. |
| Permission to use | May this project copy, modify, package, and distribute the file? | A license, written permission, public-domain dedication, or another defensible legal basis, including terms for any third-party material. |
| Disclosure | Must the project or deployer identify the content as AI-generated or manipulated? | The project policy and the law applicable to the product, actor, content type, and deployment date. |
Metadata can help answer the first question, but a metadata field does not grant rights. An AI detector can produce a signal, not conclusive proof of origin. Treat both as evidence to evaluate rather than as a clearance certificate.
A repeatable provenance and replacement workflow
1. Inventory the exact files
Start with a finite list, not a general suspicion that “some artwork may be AI.” Search the repository and build outputs for raster images, SVGs, icons, fonts, audio, video, 3D files, and animation data that are shipped or loaded at runtime.
- Record the repository path, filename, file type, dimensions, color profile, and relevant theme or locale variants.
- Calculate a current hash when the project already uses hashes, or record one in a temporary review sheet so that later changes are unambiguous. For example,
sha256sum path/to/asset.pngrecords the bytes being reviewed. - Map each file to the code, resource manifest, installer rule, package recipe, or documentation that uses it. A file that is present but never distributed has a different risk profile from one embedded in every release.
- Use version-control history to find the commit, pull request, release, or contributor who introduced the file. Commands such as
git log --follow -- path/to/asset.svgandgit blame -- path/to/asset.svgare ways to locate that history; they do not prove ownership.
Keep the original bytes in a restricted review branch or archive while the decision is pending. Do not overwrite the only copy before you have recorded what was evaluated.
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2. Search the project’s own records
Look in pull-request descriptions, issue threads, design repositories, contributor notes, release checklists, asset manifests, and commit messages. Useful facts include the human creator, the generation service and model version, the generation date, prompts, reference images, stock sources, edits made after generation, and any written permission.
Inspect embedded metadata where appropriate. Tools such as exiftool can reveal a creator field, software name, or licensing note, while file and image editors can confirm format and dimensions. Absence of metadata is not evidence that a file is unrestricted; many export pipelines remove metadata.
If the record says only “generated with AI” and supplies no source or terms, classify provenance as unresolved. Do not convert that gap into a claim that the file is infringing or free to use. It means the project cannot yet show a reliable basis for distribution.
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3. Check the application’s policy and the tool’s terms
Read the actual application project’s contribution guide, license policy, asset rules, and release checklist. Then read the generation tool’s terms that applied when the file was created, including restrictions on commercial use, redistribution, training data, attribution, output ownership, and termination. Terms can differ by account, model, region, and date, so preserve a copy or stable reference in the review record.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsThe Linux Foundation’s Guidance Regarding Use of Generative AI Tools for Open Source Software Development states: “Code or other content generated in whole or in part using AI tools can be contributed to Linux Foundation projects.” The same guidance expects contributors to check that tool terms do not conflict with project licensing or policy, and to address permission, notices, and applicable license information for included third-party material. That is guidance for Linux Foundation projects, not a universal license for every Linux application.
Some projects impose stricter rules, require disclosure in a change record, or prohibit particular tools. Follow the application’s own maintainers and release process even when a broader organization permits AI-assisted contributions.
4. Investigate identifiable third-party material
Examine the file for recognizable logos, characters, photographs, typefaces, samples, interface elements, or other material that appears to predate the generation event. Search the project records for the referenced source and determine whether its owner granted permission compatible with your distribution model.
- Record the source identity and the exact license or permission language.
- Check whether modification, redistribution, sublicensing, and commercial or bundled distribution are allowed.
- Preserve required attribution, copyright notices, source-offer text, and other conditions in the location the license requires.
- Keep evidence for material that was removed, masked, or replaced during editing; an unedited source can still matter to the rights analysis.
A generator’s output policy cannot automatically waive the rights of a photographer, illustrator, musician, trademark owner, or other third party whose material appears in the output.
5. Decide whether to keep, replace, commission, or pause
Make a written disposition for each file. Retention is defensible only when the project can document a basis for the intended use and satisfy its policy. Replacement is prudent when the source or permission cannot be established, when the tool terms conflict with the application license, or when the file creates an avoidable disclosure or reputational issue.
| Disposition | Use it when | Required record |
|---|---|---|
| Keep after review | Origin, relevant source material, permission or license, and policy compatibility are documented. | Review decision, evidence locations, notices, and any disclosure determination. |
| Replace with a documented alternative | Provenance or permission remains open, or the existing terms cannot meet the app’s distribution needs. | Original file hash, reason for removal, replacement source, creator, terms, and test results. |
| Commission or create a replacement | The project needs a distinctive design and can obtain written terms from the human creator or contributors. | Agreement or contribution record covering ownership, license, attribution, and permitted modifications. |
| Pause distribution for review | The asset is central to a release and the unresolved issue could create significant legal, contractual, or reputational exposure. | Escalation owner, questions presented, affected releases, and interim mitigation. |
Escalate to the project’s maintainers or qualified open-source and copyright counsel when the consequences justify it. This is risk management, not a universal legal conclusion about every AI output.
How to choose a replacement
Compare candidates against the same criteria rather than choosing solely on visual similarity. A replacement that looks right but cannot be redistributed is not a successful replacement.
| Criterion | Questions to answer |
|---|---|
| Source and creator | Can the project name the creator, repository, commissioning agreement, or other origin? |
| License compatibility | Does the license or permission allow the app’s packaging, modification, and distribution model? |
| Attribution and notices | Where must notices, credits, or source information appear? |
| Third-party content | Does the asset include photographs, trademarks, samples, or other material with separate terms? |
| Technical fit | Does it support the required format, resolution, color space, animation, accessibility contrast, and light or dark theme? |
| Evidence retention | Can the project preserve the license, permission, hash, and review decision in its normal release records? |
Prefer a source whose terms are explicit and durable. If a license requires attribution, decide before merging exactly where the notice will live: an in-app credits screen, a bundled notices file, package documentation, or another location allowed by that license.
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Prepare a focused change
- Create a branch dedicated to the asset change and record the old and new hashes in the change description.
- Remove the old file from every generated-resource list, installer rule, package manifest, cache, and documentation reference. Search by filename and by the resource identifier used in code.
- Add the replacement in the project’s native format where possible. Keep source artwork separately if the project normally stores editable sources, and document the export command or settings.
- Update attribution and license files at the same time as the binary change. Do not defer notices to a later release.
- Preserve stable resource names only when that avoids an unnecessary code change and does not obscure the provenance record. If a rename improves clarity, update all callers and packaging rules together.
Check visual, accessibility, and format behavior
- Render every supported scale factor, density, and window size. Raster assets can blur when an intended high-resolution variant is missing.
- Test light, dark, high-contrast, and monochrome themes if the application supports them.
- Check transparency, premultiplied alpha, color profiles, animation timing, audio sample rate, and fallback behavior for unsupported formats.
- Confirm that meaningful images have appropriate accessible names or descriptions and that decorative images remain hidden from assistive technology according to the toolkit’s conventions.
- Build the same packages users receive, not only a developer checkout. Verify that the replacement is included in source archives, binary packages, container images, and sandbox bundles as applicable.
Review and release
Keep the diff reviewable: show the resource reference change, the replacement file, the notice update, and the provenance record in one change or in clearly linked changes. A reviewer should be able to answer what was removed, why it was removed, what replaced it, and under which terms the new file is distributed.
Run the project’s normal unit, integration, packaging, and visual checks. These tests are release-engineering safeguards; they do not themselves establish copyright permission. Record failures such as missing-resource warnings, incorrect install paths, broken theme lookups, oversized packages, or license-file omissions and fix them before release.
Document the decision for future maintainers
Put the record where contributors already look: an asset manifest, licensing directory, change log, or release metadata. At minimum include:
- the exact path and hash of the reviewed and replacement files;
- the source location, creator if known, creation or acquisition date, and generation details when relevant;
- the license, written permission, public-domain dedication, or other stated basis for use;
- required attribution, notices, and links or source-offer instructions required by the terms;
- the project policy checked, the reviewer, the decision date, and unresolved limitations;
- the formats, themes, packages, and versions tested.
If the project uses SPDX identifiers or a software bill of materials, follow its established conventions. SPDX is a standard for communicating provenance and licensing information; an SPDX field is useful evidence and machine-readable metadata, but it is not a substitute for permission or proof of origin. Do not invent an identifier when the applicable license is unknown; record the uncertainty and escalate it instead.
Linux-specific policy boundaries
The Linux kernel’s current AI Coding Assistants guidance addresses kernel contributions, including GPL-2.0-only compatibility, appropriate SPDX identifiers, and a prohibition on AI agents adding Signed-off-by tags. Those requirements are kernel-specific. A Linux application should not claim that every asset must meet kernel rules, nor should it ignore its own project policy because the software runs on Linux.
Other open-source foundations and projects may publish their own generative-tooling guidance. The controlling question is always: which project is accepting the contribution, what license governs that project, and what distribution obligations apply to this particular asset?
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Copyrightability and transparency are different issues
The U.S. Copyright Office’s Copyright and Artificial Intelligence work includes Part 2 of its report, published January 29, 2025, on copyrightability of generative-AI outputs. That publication describes the Office’s analysis; it is not a case-specific ruling about an asset in your application. Human selection, arrangement, editing, and other contributions can raise separate questions from the status of raw generated material.
In the European Union, Article 50 transparency obligations for specified AI-generated or manipulated content apply from August 2, 2026, according to European Commission information. The Commission describes machine-readable marking and detection obligations for providers and disclosure obligations for deployers in specified contexts. Its FAQ describes a transitional period until December 2, 2026 for certain systems placed on the market before August 2, 2026. Applicability depends on the system, actor, content, and deployment; check the current Commission guidance for the actual product.
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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →The Commission has said its Code of Practice adequately covers the relevant obligations while also stating that following the code is not conclusive evidence of compliance. These transparency rules do not decide whether your project has copyright permission to ship an image, icon, or sound. Handle disclosure and licensing as two separate checklist items.
What an AI detector can and cannot tell you
Visual artifacts, file metadata, watermark checks, and automated detectors may help prioritize files for investigation. None can reliably reconstruct the complete chain of source material, prompts, edits, tool terms, and permissions. A detector’s “AI” or “human” result is therefore not a rights determination.
When provenance cannot be established, describe the status precisely: “origin and permission not documented as of the review date.” That statement is more useful than labeling the asset illegal, public domain, or definitely AI-generated without evidence. It also gives maintainers a clear trigger to revisit the decision if new records appear.
Worked example: replacing an uncertain application icon
Suppose a contributor submits a 512-pixel PNG named app-icon.png. A commit message says “new AI icon,” but there is no prompt, model record, source image, license, or attribution. The icon appears in the desktop launcher, a website screenshot, and a monochrome panel variant.
- Inventory all variants, record their hashes, and map each use in resource files and packaging rules.
- Inspect the commit, pull request, design files, and contributor notes. Ask the contributor for the generation record and any source-material permissions.
- Check the application’s contribution policy and the tool terms that applied at creation. Look for recognizable third-party logos or characters.
- If the contributor can document compatible permission and required notices, retain the icon and add that evidence to the asset manifest.
- If the evidence remains unavailable, commission or select a replacement with a documented creator and license. Update the full-color and monochrome variants together.
- Run launcher, desktop-environment, high-contrast, packaging, and clean-install checks. Record the replacement hashes, license notice, reviewer, and decision date.
The result is not a claim that every AI-generated icon is unusable. It is a traceable decision for this icon, this application, and this distribution.
When to involve maintainers or counsel
Ask project maintainers to decide when the policy is ambiguous, the asset is central to branding, or the project has a formal approval process. Obtain qualified legal review when a recognizable third-party work may be embedded, a contributor disputes ownership, distribution is commercial or worldwide, contractual warranties are required, or the cost of a takedown would be significant. Provide counsel with the file hash, history, tool terms, source-material analysis, intended distribution, and the exact questions; a vague request to “check if AI art is legal” omits the facts needed for a useful answer.
Quick Recap
Release checklist
- Every suspect asset has an exact path, hash, and list of uses.
- Repository history and project records were checked.
- Tool terms, project policy, and third-party source material were reviewed.
- Permission, attribution, and notice requirements are recorded or explicitly unresolved.
- The disposition—keep, replace, commission, or pause—is written and reviewable.
- Replacement files meet format, accessibility, theme, and packaging requirements.
- SPDX or other metadata follows the project’s established conventions without pretending to grant rights.
- Any disclosure question is evaluated separately under the applicable jurisdiction and deployment date.
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