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Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Deploy Claude as a governed service, not merely a developer tool. Start by classifying the data users may send, selecting an approved processing route, enforcing identity and network boundaries, defining retention and logging, and testing the complete workflow before production. Claude Code can execute locally while sending prompts and model responses to a model service, so its network path and data handling belong in your enterprise threat model.
The right design depends on your residency, regulatory, identity, audit and feature requirements. You can call Anthropic directly, use Claude through Amazon Bedrock or Google Vertex AI, or place an internally approved gateway in front of the model service. Each option shifts responsibilities rather than removing them.
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What a secure Claude deployment must control
Security is a chain of decisions across six areas:
- Data flow: what leaves a workstation or application, which provider processes it, and where the request is routed.
- Retention: whether prompts, completions, telemetry and local sessions are stored, for how long, and under which contract.
- Identity and authorization: how employees, service accounts and administrators authenticate and what each can do.
- Network boundaries: proxies, firewall allowlists, private routing where available, and protection of credentials.
- Auditability: which user, model, request, response and administrative events are recorded and who can review them.
- Model lifecycle: how you approve versions, detect deprecations, test replacements and migrate without breaking controls.
Encryption in transit is documented for Claude services, but encryption alone does not answer residency, retention, access or incident-response questions. Treat the service path, account configuration and contract as one security control set.
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Claude Code runs commands and tools on the local machine, yet prompts and model outputs are sent to the selected model service. A repository, terminal transcript, file excerpt or secret included in a prompt can therefore leave the workstation. Local execution should not be mistaken for local-only processing.
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Before enabling the tool, map:
- which files and directories it can read;
- which shell commands, scripts and network tools it can invoke;
- which prompts, tool results and outputs are transmitted;
- where local session data is stored and how it is deleted;
- which proxy, DNS and firewall path carries the traffic; and
- which service account or user identity is charged and audited.
Claude Code documentation describes configurable local session storage and permission controls. Use those settings to reduce workstation exposure, but retain central identity, endpoint management and data-loss-prevention controls as separate layers.
Choose the service path
Compare the alternatives against the workload’s actual requirements. Feature availability, model identifiers, regions, retention options and administrative controls can differ by provider, account and date.
| Service path | Where requests are processed | Potential strengths | Questions that remain your responsibility |
|---|---|---|---|
| Direct Anthropic API | Anthropic’s service, subject to the account and contract | Direct access to Anthropic features and APIs; fewer intermediary components to operate | Which regions and retention terms apply to your account? Is zero data retention (ZDR) available for the specific model and use? Which workforce identity and audit controls are included? |
| Amazon Bedrock | A selected cloud region and its associated service path | Regional endpoints and invocation logging are documented; existing cloud identity, network and logging controls may be integrated | Is the required Claude model and feature set available in the target region? What does the cloud log, for how long, and who can access it? Which Anthropic terms apply? |
| Google Vertex AI | Google Cloud’s service path, subject to selected location and account configuration | Can fit organizations that already standardize on Google Cloud identity, policy and operations | Confirm current region, model, feature, retention and audit support for the intended workload; do not assume cloud controls eliminate provider or contractual obligations. |
| Approved internal gateway | Your gateway plus the downstream model provider | Central authentication, usage tracking, budgets, rate limits, model routing and a common policy layer | Who patches and operates the gateway? Where are request logs stored? How are provider credentials protected? Has the gateway been independently assessed? |
A cloud route can simplify regional routing and reuse existing controls, but it does not automatically make data compliant or private. Confirm the complete request path and every system that can retain content.
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Create a data inventory before issuing credentials. Include source code, internal documents, credentials, personal data, customer records, production logs and regulated information. Classify each category by confidentiality, residency and permitted processing location.
Define retention requirements
Write down whether prompts and completions may be retained, whether administrators need searchable history, and when records must be deleted. Separate provider-side retention from local Claude Code session files, gateway logs, cloud invocation logs and backups. Ask for written terms covering each layer.
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Check residency and transfer constraints
Identify the country or cloud region in which requests must be processed and where logs may reside. A regional endpoint can control routing for a particular platform, but verify the actual model, account, failover behavior and telemetry destinations. Document any cross-border transfer and obtain legal approval where required.
Handle regulated healthcare data carefully
Anthropic’s documented healthcare coverage requires an executed business associate agreement (BAA) and zero data retention for the described Claude Code use. A general product label does not establish compliance. Confirm that your account, model, features and configuration fall within the BAA and ZDR scope, and have counsel verify the implementation before sending protected health information.
Step 2: approve the provider and contract
For each service path, obtain current terms for data use, retention, subprocessors, incident notification, regional processing, deletion and model-improvement eligibility. Do not infer plan entitlements from a different edition or an older document.
- Record the exact account, model family and region covered by the approval.
- Confirm whether customer content is used for training or other service improvement under your terms.
- Verify ZDR availability for the model and workload; it may be limited by endpoint, feature or account.
- Define who can request provider support and what content may be disclosed during troubleshooting.
- Attach the provider’s commitments to your vendor-risk record and renewal review.
“Does Claude train on our data?” has no single answer independent of account and contract. Obtain the current provider terms that govern your chosen route and preserve them with the deployment record.
Step 3: configure network boundaries for Claude Code
Anthropic documents corporate HTTP and HTTPS proxy support and identifies these destinations for the documented Claude Code setup:
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Permit only the destinations required by your approved version and inspect whether security telemetry is allowed by policy.
Proxy configuration procedure
- Provide the approved proxy through your enterprise configuration or environment variables, not by embedding credentials in scripts or source control.
- Apply outbound firewall rules that allow the documented HTTPS destinations and block unapproved model endpoints.
- Use a test workstation to verify DNS resolution, TLS negotiation, authentication and request completion through the proxy.
- Confirm that proxy logs do not capture full prompts or secrets unless your retention and access policy explicitly allows it.
- Record the proxy owner, certificate authority, change process and emergency rollback method.
Claude Code documentation lists two important limitations: SOCKS proxies are not supported and NO_PROXY is not supported. Test these constraints rather than assuming a generic developer proxy configuration will work. If your network requires either feature, redesign the path or use an approved service integration instead of bypassing controls.
Step 4: establish identity and permissions
Use the currently supported identity and administration controls for the exact subscription and deployment. The available materials do not establish the present availability or configuration of SSO, SCIM, granular roles or organization-wide audit events for every plan, so verify each capability in current Enterprise documentation and your contract.
Workforce access
- Require centrally managed accounts rather than shared API keys.
- Enforce your organization’s authentication, offboarding and privileged-access policies.
- Separate developer, application, security-reviewer and administrator roles.
- Grant Claude Code access only to approved repositories, directories and command classes.
- Rotate credentials on a defined schedule and immediately after suspected exposure.
Application access
Give each application its own credential or workload identity. Scope permissions to the required model and environment, and keep development, test and production credentials separate. Store secrets in an approved vault or cloud secret manager; never place them in shell history, configuration committed to a repository or proxy URLs.
Step 5: decide whether to operate a gateway
A gateway can provide one policy point for authentication, usage measurement, budgets, rate controls, request logging and model routing. It can also normalize provider APIs and make it easier to disable a model or account during an incident.
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Gateway controls to specify
- Authentication: map workforce or workload identities to short-lived provider credentials.
- Authorization: restrict models, tools, repositories, data classes and environments by policy.
- Content handling: redact secrets or personal data before logging; define prompt and completion retention separately from metadata.
- Cost controls: enforce per-user, team and application budgets, rate limits and alert thresholds.
- Routing: document fallback models and ensure a fallback does not violate residency or regulatory rules.
- Operations: patch the gateway, monitor dependencies, rotate keys and rehearse failure and rollback.
Anthropic explicitly states that it does not endorse, maintain or audit LiteLLM. If you choose any third-party gateway, assess it as a separate security-sensitive system: review its code or assurance reports, deployment topology, logging, dependencies, patch process and access to provider credentials. A gateway adds control only when your organization can operate it securely.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Step 6: design logging and audit evidence
Decide in advance which events must be reconstructable after an incident. At minimum, capture:
- the human or workload identity;
- application, environment and repository;
- provider, region, model identifier and gateway route;
- request and response timestamps, status and token or usage metadata;
- policy decisions, denials, tool invocations and administrative changes; and
- credential, model and configuration changes.
Do not automatically store full prompts and completions. They may contain secrets or regulated data. If content logging is necessary for a controlled use case, encrypt it, restrict access, set a short documented retention period and include it in legal discovery and deletion procedures.
Amazon Bedrock documentation describes invocation logging for prompts and completions. Confirm whether it is enabled, where those logs are delivered, which administrators can read them and how long they persist. Apply the same questions to Vertex AI, Anthropic endpoints and any gateway.
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Step 7: pilot with representative but controlled workloads
Run a pilot that reflects real repositories, document types, proxy behavior and failure conditions without exposing production secrets. Use synthetic or scrubbed data where possible.
- Validate data flow: observe outbound connections and confirm that traffic uses the approved provider, region and proxy.
- Test permissions: attempt access to approved and prohibited files, commands, repositories and models.
- Test retention: verify local session deletion, provider settings, gateway logs, cloud invocation logs and backup behavior.
- Test identity: disable a user, revoke a key and confirm access stops promptly across every layer.
- Test logging: correlate a known request from user identity through gateway or cloud logs to the model response.
- Test incidents: rotate a credential, block an endpoint, disable a model and restore service using the documented runbook.
- Measure usability: record latency, error modes, proxy compatibility and the support burden before broad rollout.
Keep evidence from these tests with the security review. Re-run the relevant checks after provider, model, proxy, gateway or identity changes.
Common deployment failures and fixes
| Symptom | Likely cause | Corrective action |
|---|---|---|
| Claude Code cannot connect behind the corporate network | Unsupported proxy type, missing allowlist entry, TLS interception issue or incorrect credentials | Use the documented HTTP/HTTPS proxy path, allow the required destinations, validate certificates and test without SOCKS or NO_PROXY assumptions. |
| Users believe no data leaves their laptops | Local execution confused with local inference | Show the outbound request path, classify transmitted content and enforce repository and secret-access controls. |
| Audit records contain sensitive prompts | Full-content logging enabled by default in a gateway or cloud service | Disable content capture where possible; otherwise redact, encrypt, restrict and shorten retention. |
| Requests are processed in an unexpected location | Region, failover route or model availability changed | Pin and monitor the approved route, verify current regional support and block unapproved fallback paths. |
| A replacement model breaks an application | Model identifier or behavior changed without a compatibility test | Maintain an inventory, test candidate replacements, stage migration and monitor retirement notices. |
| Offboarded staff retain access | Shared keys, stale provisioning or gateway accounts outside central identity | Use individual or workload identities, automate deprovisioning and rotate shared credentials immediately. |
Maintain a model and configuration lifecycle
Model IDs and availability change. Keep an inventory containing each model identifier, provider, region, application owner, data classification, approved features and retirement date. Audit API usage to find deprecated models, then test replacements with representative prompts, tool calls, latency limits and safety policies before migration.
Use a staged process: approve the replacement, run it in a non-production environment, compare outputs against acceptance tests, update routing and documentation, then migrate with rollback available. Treat model changes as production changes even when the API endpoint remains the same.
Enterprise deployment checklist
- Data classes, prohibited content and residency requirements are documented.
- Provider, region, model and contract terms are approved for the workload.
- Training-use, retention and ZDR terms are confirmed for the exact account and feature.
- Healthcare workloads have the required BAA and documented ZDR configuration.
- Claude Code runs through the approved HTTP/HTTPS proxy and firewall allowlist.
- SOCKS and
NO_PROXYdependencies have been eliminated or addressed through a supported design. - Workforce and workload identities are individual, scoped and revocable.
- Local sessions, gateway logs and cloud invocation logs have explicit retention and access rules.
- Gateway security, if used, has its own architecture review and operating owner.
- Outbound traffic, permissions, deletion, offboarding and incident response passed a pilot.
- Model inventory, deprecation monitoring and replacement tests are part of change management.
How to make the final decision
Choose the simplest service path that satisfies your non-negotiable controls. Direct API access may reduce operational components; Bedrock or Vertex AI may fit existing cloud identity and regional controls; an internal gateway may be justified when centralized policy, budgets and routing outweigh its maintenance burden. None of these choices removes the need to verify retention, residency, identity, logs, feature support and contractual scope. Approve production only after the complete data path has been demonstrated and the organization can revoke access, investigate activity and migrate models without losing control.
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