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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchYes—but only when you deliberately grant access and verify what that grant permits. A private repository is not automatically visible to an AI security scanner. An owner or administrator must authorize an app, token, deploy key, or another integration. Safety then depends on the repositories selected, permissions granted, whether the scanner clones or stores code, what content is sent to an AI service, retention and deletion terms, and whether the tool can write back to GitHub.
Evaluate the specific product, scan mode, plan, and settings rather than trusting a label such as “read-only.” Start with the smallest repository scope and permission set that can perform the scan, document the configuration, and remove access when the integration is no longer needed.
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What “safe access” means for a private repository
“Safe” is a configuration decision, not an inherent property of AI scanning. A scanner may need to inspect source files, manifests, lockfiles, build instructions, or infrastructure definitions. To do that, you grant it a credential or install an integration. The resulting access is limited by two boundaries: what the app or token is allowed to do, and what the installing user or organization is allowed to do.
For GitHub Apps, GitHub explains that installation grants the permissions requested by the app, while the installer chooses which repositories the app can access. The app can act only within the overlap between its granted permissions and the installer’s own access. Authorization and installation are separate flows, so approving an authorization prompt does not by itself mean every repository in an organization is available to the app. See GitHub’s explanation of GitHub Apps and its authorization guidance.
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A safe connection therefore has a clear purpose, a narrowly defined scope, understandable data handling, and a way to monitor or revoke the access. If you cannot determine those four things, do not connect the repository yet.
How private-repository access is granted
GitHub App installation
An app installation normally presents the organization or account that will install the app, the permissions being requested, and a repository choice. Depending on the app and organization policy, you may be able to select all repositories or only specific repositories. Choosing only the repositories required for the scan prevents unrelated projects from becoming part of the tool’s reachable surface.
Installation does not give the app more authority than the installer possesses. An administrator who can see one private repository cannot use the installation to expose repositories outside that authority. Conversely, installing an app with broad organization access can make many repositories available if the app’s permissions and the installation selection allow it.
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Some scanners use an OAuth authorization, a personal or organization token, a CI secret, or a deploy key instead of a GitHub App. These mechanisms differ in how precisely they can be restricted and how easily they can be audited. A long-lived credential should be treated as a sensitive access path: it may continue working after an employee changes role or leaves the organization.
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GitHub’s repository-role guidance notes that a deploy-key holder can retain access according to the key’s configured read or write capability, even after that holder is removed from the organization. Inventory deploy keys, machine users, CI secrets, and personal tokens alongside installed apps; do not assume removing a person removes every credential they created.
Use least privilege, not a broad default
GitHub recommends requesting the minimum app permissions needed for a task. Installation tokens can be further limited by repository and permission. Before clicking an approval button, compare every requested permission with the scanner’s stated function and remove anything unnecessary. GitHub’s best-practices documentation explains the least-privilege approach.
| Capability to inspect | Why a scanner might request it | Question to ask before granting it |
|---|---|---|
| Repository contents | Reading source, manifests, lockfiles, and configuration for analysis | Does it need read access to every selected repository, or only a particular project? |
| Pull requests and issues | Posting findings, opening a remediation request, or commenting on code | Can findings be delivered without write access, and is commenting enabled by default? |
| Actions, workflows, or checks | Running scans in CI or publishing status checks | Can the integration alter workflow files or only report a status? |
| Security events or code-scanning results | Reading existing alerts or synchronizing results | Which endpoints are read-only, and which ones upload or modify results? |
| Administration or organization settings | Managing installations or policy-level configuration | Why is an administrative permission necessary for this scan, and can an administrator perform that step separately? |
Permission names and availability vary by integration. Record the exact names shown on the installation screen rather than relying on a vendor’s general description.
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GitHub describes repository security and analysis features as performing read-only analysis in the relevant settings. That does not mean every code-scanning integration is read-only. GitHub’s code-scanning API documentation lists separate requirements for different endpoints; submitting SARIF results, for example, is a write operation.
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Write access can take several forms:
- Uploading SARIF or other scan results.
- Creating, updating, or dismissing alerts.
- Posting pull-request comments or check-run status.
- Opening branches or pull requests for suggested fixes.
- Changing workflow files or other repository configuration.
A tool can be safe to use with write permissions, but the decision should be explicit. Ask which writes are possible, whether they are optional, and whether a separate approval is required for fixes. Treat “read-only analysis” as a description of one feature, not a universal promise covering every API call or product mode.
Availability is also separate from access. GitHub’s security-and-analysis settings and its security quickstart note that some features for private repositories require qualifying organization or enterprise plans. A third-party tool may be technically capable of receiving access even when a native GitHub feature is unavailable on your plan.
What happens to source code during a scan?
“The results do not contain source code” is not the same as “the service never accessed or stored source code.” A scanner may clone a repository, keep a working copy while analysis runs, cache files for later jobs, or send selected excerpts to another service. These behaviors must be checked for the exact product, feature, region, and plan.
| Documented example | What the documentation says | What you still need to verify |
|---|---|---|
| Snyk Go Modules full source analysis | Snyk states that this feature accesses and stores Git repository contents to build a dependency graph. It also says scan results contain pointers to positions and identification metadata rather than original source code. | Whether your selected Snyk product and analysis mode use the same handling, how long working data is retained, where it is processed, and how deletion works. A source-free result does not prove that source was never stored during analysis. See Snyk’s data-handling documentation. |
| Semgrep Managed Scans | Semgrep says Managed Scans clone the repository at the beginning of every scan. | How clones are protected and deleted, whether caches remain, and which repositories and branches are included in your configuration. |
| Semgrep AI-powered detection, triage, and remediation | Semgrep’s pricing page says that, when these AI features are opted into, part of the file containing a finding is processed by a model. | Whether the feature is enabled for your plan, what excerpt is transmitted, the model provider and processing location, retention, and whether prompts or outputs are used for service improvement. See Semgrep’s current plan description. |
These examples illustrate why “AI scanner” is too broad a category for a single privacy conclusion. Scan mode, optional AI functions, and plan settings can change the data path. The available documentation does not establish one cross-vendor retention schedule, so obtain the current contractual and product terms rather than inferring retention from a read-only label or a scan-result format.
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Questions to answer before connecting a repository
- Identify the exact product and feature. Record the vendor, plan, scan mode, branch scope, and any AI-powered detection, triage, or remediation option. A dependency scan and a full source analysis may have different handling.
- Capture the installation request. Save the organization permissions, repository permissions, and requested repositories shown by GitHub. If the screen is unclear, stop and ask the vendor for a permission-by-permission explanation.
- Select only necessary repositories. Use a selected-repository option when available. Exclude production code, regulated data, customer-specific repositories, or unrelated experiments unless the scan genuinely requires them.
- Separate read and write functions. Determine whether the integration can upload SARIF, manage alerts, comment on pull requests, alter workflows, create branches, or apply fixes. Disable optional write features until they are needed and approved.
- Map the data lifecycle. Ask whether the service clones, caches, stores, indexes, or backs up source; which files are transmitted; which subprocessors or AI providers receive excerpts; the processing regions; retention periods; deletion triggers; and incident-notification obligations.
- Check organizational controls. Confirm that the repository’s data classification, customer contracts, export rules, and internal security policy permit the selected service and processing locations. Private visibility alone does not answer those questions.
- Plan removal before installation. Decide who reviews the integration, how often access is rechecked, and how tokens, deploy keys, and app installations will be revoked when the project ends.
How to limit a GitHub App to selected private repositories
Labels differ slightly between apps and GitHub account types, but the control sequence is consistent:
- Open the scanner’s official installation or authorization link while signed in to the GitHub organization that owns the repository.
- Read the requested organization and repository permissions. Expand details instead of accepting a summary such as “access your code.”
- When GitHub offers the repository choice, select the option for only selected repositories, then choose the specific private repositories required for the scan.
- Review the resulting list and remove test, archived, or unrelated repositories. Check whether newly created repositories will be included automatically or require a separate selection.
- Complete the installation or authorization, then record the app name, installer, selected repositories, permissions, enabled scan modes, and date.
- Run a deliberately small test against a non-sensitive repository or branch when the product supports it. Confirm that the scanner produces the expected result without unexpected comments, workflow edits, or additional repository access.
- After rollout, use GitHub’s controls for reviewing and modifying installed apps to inspect, change, suspend, or remove access. The relevant guidance is in GitHub’s installed-app documentation.
If the scanner requires a token rather than an app, apply the same principle: create a dedicated credential with the narrowest repository and operation scope, store it in the organization’s secret manager, set an expiration where supported, and revoke it when the scan is retired.
How AI processing changes the review
Traditional rule matching may analyze files inside the scanner’s execution environment. An AI-assisted feature can add another transfer: a code excerpt, finding context, prompt, or generated remediation may be sent to a model service. The relevant question is not simply whether the scanner uses AI, but which feature uses it and what exact content leaves the scanning boundary.
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Ask these questions in writing:
- Is AI processing optional, opt-in, or enabled by default for the selected plan?
- Is an entire file sent, or only a bounded excerpt around a finding?
- Are secrets, comments, generated files, or test fixtures filtered before transmission?
- Does the model provider retain prompts or outputs, use them for training, or permit human review?
- Are data residency, subprocessors, deletion, and breach-notification commitments defined in current terms?
- Can administrators disable AI processing while keeping non-AI scanning enabled?
Do not place credentials, production secrets, private keys, customer records, or regulated data in a repository merely because a scanner is trusted. Secret scanning and repository controls reduce exposure but do not replace normal secret-management practices.
Warning signs and safer responses
| Warning sign | Safer response |
|---|---|
| The app requests organization-wide repository access for a single-project scan. | Ask for selected-repository installation or use a separate organization/project boundary. |
| “Read-only” appears, but the permission list includes pull-request, workflow, or administration writes. | Identify the exact write operation and disable it unless the workflow requires it. |
| Documentation describes cloning or source storage but gives no deletion process. | Request current retention and deletion terms; do not infer them from the scan result. |
| AI remediation is bundled into the scan without a clear setting. | Turn off AI features until transmission, provider, and retention details are documented. |
| A deploy key or token has no owner, expiry, or review date. | Assign an owner, restrict its scope, rotate it, and schedule a removal review. |
| The vendor cannot identify subprocessors or processing regions. | Escalate to your security and legal reviewers before granting private-code access. |
Ongoing review after the first scan
Access that was appropriate during a pilot can become excessive as repositories, teams, and features change. Review installed apps and credentials on a schedule appropriate to your organization’s risk, and whenever the scanner changes plan, scan mode, AI provider, or requested permissions.
- Compare the current installation permissions with the original record.
- Remove repositories that no longer need scanning.
- Check whether new repositories were added automatically.
- Review comments, pull requests, workflow changes, SARIF uploads, and alert-management activity.
- Rotate or revoke tokens and deploy keys that lack a current business purpose.
- Suspend or uninstall the app when the project ends, then verify that associated credentials and CI secrets are also removed.
A scanner is safest when its access is temporary or continuously justified, its data path is documented, and its write capabilities are intentionally enabled rather than inherited from a broad default.
Bottom line for teams deciding today
AI security scanners can safely access private repositories, but the answer is conditional. Grant access only after confirming the exact repositories, permissions, code-handling behavior, AI transfers, retention terms, and write actions for the selected product configuration. Start narrow, test safely, monitor the installation, and revoke every access path that no longer serves a defined scanning purpose.
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