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Yes. An air-gapped AI system can be updated safely, but the gap does not make imported files trustworthy. Treat every model, software, configuration, and supporting-artifact change as a controlled release: verify its provenance and integrity, inspect and test it before production, authorize the change, and preserve a tested way back to the last known-good version.
Why an air gap does not make updates risk-free
An air gap blocks ordinary network connections; it does not remove the need to bring changes across the boundary. Imported packages, removable media, and physical access create supply-chain and change-control risks. A compromised or unsuitable artifact can still enter an isolated environment if the transfer and approval process is weak.
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NIST recommends automatically verifying hashes or signatures for vendor-supplied software installations and updates where feasible. Its software supply-chain guidance was updated November 1, 2024. A matching hash shows that a file matches the trusted reference you checked; it does not prove that the publisher or software is benign.
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Change access also matters. NIST SP 800-171 Rev. 3 calls for defining, documenting, approving, and enforcing physical and logical access restrictions associated with system changes. The exact controls depend on the system’s authorization boundary, security policy, and applicable contractual or regulatory requirements.
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What belongs in an AI update
Do not treat “the model” as a single file. Identify every component that will change, including whichever of these apply:
- Model weights and model version.
- Tokenizer, prompts, configuration, or other model-supporting artifacts.
- Inference runtime, libraries, and dependencies.
- Drivers, firmware, and operating-system or security patches.
- Evaluation data, policy settings, and deployment scripts affected by the release.
Ask the supplier for the package, release notes, version identifiers, signature or checksum, and available dependency or software-bill-of-materials (SBOM) information. CISA and G7 partners published supplemental minimum-element guidance for AI SBOMs on May 12, 2026; the release describes SBOMs as an aid to transparency and risk-informed supply-chain decisions, not a complete or mandatory update procedure. Read the CISA release.
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A controlled offline update sequence
- Define and authorize the change. List the components and versions in scope, the reason for the update, the affected system, and the people authorized to approve and perform it. Follow the system’s established change process; restrict change access to qualified, authorized personnel.
- Acquire release materials through an approved process. Obtain the package and its release documentation from an approved source on the connected side. Keep the package identity and version tied to the vendor’s release information. Do not substitute a file merely because its name or version string looks right.
- Verify the package and control the transfer. Check the vendor’s signature or checksum against a trusted reference obtained through an approved channel, and record the result. Transfer the verified materials using media or another mechanism approved for the facility and classification. If using a USB drive, its custody must be controlled and the package still independently validated; the drive itself does not make an update safe.
- Inspect in a secure staging area. Do not run an imported pretrained model immediately in the operational environment. Inspect it in a secure development or staging zone first, as recommended in the joint government guidance Deploying AI Systems Securely. Keep staging distinct from production and apply the organization’s approved handling rules.
- Test the exact release candidate. Check compatibility and functionality, then assess accuracy, robustness, security-relevant behavior, and vulnerabilities as appropriate for the system’s use. Include adversarial testing where relevant. Test rollback as well as installation so recovery is practical, not just documented.
- Deploy in an authorized change window. Preserve the prior known-good model, configuration, and related artifacts. Deploy only the tested release, then monitor its behavior against acceptance checks. If those checks fail or the update appears compromised, use the recovery plan to return to the known-good release.
- Close the change record. Record the source, package identity and version, verification evidence, test results, approver, deployment time, and recovery reference. Update the system component inventory after the update, as required by the inventory guidance in NIST SP 800-171 Rev. 3.
Re-evaluate model changes, not just software patches
A security patch to the runtime and a change to model weights can have different effects, so test the release according to what changed. For model modifications, the joint government guidance recommends testing robustness, accuracy, and vulnerabilities. The UK Department for Science, Innovation and Technology’s Code of Practice for the Cyber Security of AI says operators should rerun evaluations on released models intended for use and communicate plans to update models accessibly. It also advises treating major AI-system updates like a new model version for security testing and evaluation.
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That is particularly important when an update may change outputs, supported use cases, safety behavior, or exposure to attacks. Keep evaluation results tied to the exact candidate version so approval applies to the artifact that will actually be deployed, rather than a similar earlier build.
Choose a transfer method that fits the boundary
The cited guidance does not establish one transfer medium or universal workflow for every air-gapped system. Select an organization-approved method against the controls that matter for the particular environment:
- Can the source and signing reference be trusted and independently checked?
- Can custody and handling of transfer media be controlled and audited?
- Does the method comply with facility, classification, and system-authorization rules?
- Can the artifact be inspected and tested before it reaches production?
- Can the system recover within an acceptable time if deployment fails?
- Are update latency and operational burden manageable, and does the supplier document release provenance and support the process?
NIST SP 800-171 Rev. 3 includes media libraries and access restrictions among possible change controls, but the implementation choice belongs to the organization. For release or archive keys, the joint government AI guidance identifies a secure vault or hardware security module (HSM) as a way to protect keys; it is an option for organizations whose needs justify it, not a universal requirement. The same guidance recommends version control, retaining encrypted release copies in a tamper-proof location, and maintaining rollback capability.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What verification can and cannot establish
A valid signature or matching checksum gives evidence that the received artifact corresponds to a trusted reference. It does not replace source approval, inspection, testing, access controls, or change authorization. Nor does the guidance cited here promise a particular reduction in risk or guarantee that an update is safe. The responsible standard is a documented process that checks the artifact, tests its effects, limits who can introduce it, and provides a recoverable deployment path.
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