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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsAssume an AI coding-assistant credential may be stolen when independent evidence agrees: a secret-scanning alert or exposed key, token use you do not recognize, unfamiliar source IP addresses, unexpected repository or workflow changes, suspicious code or files, data-exfiltration signs, or API usage and spending that you cannot explain. One failed request, an outage, or a familiar-looking login is not proof by itself.
Handle this as an incident-triage problem. Preserve evidence first, correlate activity across identity, source-control, workflow and billing records, then revoke and rotate the credential while you investigate scope. The sequence below works for an API key, personal access token, OAuth credential, IDE login session, organization secret, or a short-lived cloud token.
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What counts as convincing evidence?
No single indicator can reliably distinguish theft from a misconfigured tool or an automated job. Confidence rises when signals from different systems point to the same credential, time window and account.
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| Signal | What it can indicate | What to verify | Important caveat |
|---|---|---|---|
Secret-scanning alert or a key found in code, logs, an .env file or a public repository |
The secret was exposed and could have been copied. | Identify the exact token, repository, commit, log line, exposure time and permissions. | Exposure proves disclosure, not that somebody used the credential. |
| Unfamiliar token or login activity | Someone else may have authenticated with the credential or account. | Match the event to a user, token name, device, job and timestamp. | Automation and shared development environments can create activity that looks unfamiliar. |
| Unknown source IP addresses | The credential may have been used from an unexpected network. | Check provider audit records, runner or proxy ranges and the UTC time. | Cloud runners, VPNs and corporate egress can make many users share an address. |
| Unexpected commits, pull requests, workflow runs, repository creation or visibility changes | An attacker may be attempting code injection, persistence or data access. | Inspect the actor, changed files, workflow permissions, secrets referenced and downstream network calls. | Scheduled jobs and bots can legitimately create activity; confirm the triggering configuration. |
| Unexplained model requests, API volume or charges | A copied key may be used outside your normal workload. | Compare project, model, endpoint, time, quantity and spend with deployment records. | Retries, a runaway script or a changed prompt can also increase usage. |
GitHub warns that a credential compromise can enable malicious code injection and, from there, data exfiltration. Treat repository and workflow changes as security evidence even when no source file was deleted.
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Preserve evidence before changing anything
Revoking a token is important, but doing it before recording what happened can erase the context needed to determine scope. Save evidence in a restricted incident folder and write down all times in UTC.
- Export logs and alerts. Download audit-log entries, secret-scanning alerts, usage records, billing events and security notifications. Record the provider, account, organization, project, token name or identifier, event ID and retention period.
- Capture screens. Take screenshots of suspicious sign-ins, IP addresses, repository events, workflow runs, permission changes and alert details. Include the browser time and the visible account or organization.
- Copy affected artifacts. Save suspicious files, workflow definitions, pull requests, commits, build logs and command output before cleanup. Preserve the original content and calculate a hash if your incident process supports it.
- Build a first timeline. Record when the secret was created, first exposed, first suspiciously used, discovered and contained. Add repositories, environments, accounts and token scopes.
- Do not tip off an intruder unnecessarily. Avoid editing or deleting suspicious workflows and files until a responder has captured them. If an active attack is causing harm, containment takes priority, but document the action and its time.
Opening a support ticket does not preserve logs or extend their retention. Export what you can while records are still available.
Check whether the credential was exposed
Search every place a secret can appear
Start with the exact token value, a safe fingerprint, its name and distinctive prefixes. Search source repositories, forks, pull requests, issues, build artifacts, package archives, container layers, deployment manifests, editor settings, shell history, local configuration, CI logs and shared documents. Include ignored files and deleted branches where your tooling can search them. Review both current files and version history; removing a line from the latest commit does not remove it from an earlier commit, a fork or a cache.
Search local and organization-level .env files, IDE settings and environment-variable stores. A credential copied into a diagnostic log can be exposed even when the source repository is private. Restrict the evidence copy itself because it contains sensitive material.
Classify the credential
Write down whether the exposed item is an API key, personal access token, OAuth refresh token, IDE session credential, repository secret, organization secret or cloud federation token. Note its owner, scopes, projects, creation date, expiration, last-used time and whether it can create other credentials. A broad organization token has a larger blast radius than a key restricted to one project.
Interpret a secret-scanning alert correctly
A secret-scanning alert means a pattern resembling a credential was found, or a provider confirmed a secret. Confirm the exact value and location, then determine whether it was valid during the exposure window. A revoked or expired value can still reveal how an attacker entered another system, so retain the alert and investigate related credentials. Conversely, a false-positive pattern should be closed only after the file content and provider validation have been checked.
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Correlate identity and audit records
Search actions made with the suspected credential
Use the provider’s audit interface or exported logs to search by token, actor, application, project and time range. Look for authentication, repository reads and writes, key-management actions, permission changes, model requests, organization administration and settings changes. Group events into sessions rather than judging one event in isolation.
Check source IP and network context
When IP disclosure is available, compare each address with your office egress, VPN, home network, cloud runner, build service and known vendor ranges. Geolocation is only a clue; an address in the expected country can still belong to an unauthorized user, while a foreign address may be a legitimate corporate gateway. Look for a new address immediately followed by high-volume requests or administrative changes.
Review account security history and active sessions
Inspect sign-ins, password changes, multifactor-authentication events, newly authorized applications, recovery settings and active browser or IDE sessions. A stolen API key may be used without a new interactive login, while a compromised account can issue replacement keys. Record session identifiers and device details before terminating them.
Ask the credential owner and the team that owns the automation whether a deployment, runner migration, VPN change or scheduled task explains the event. Require a concrete match to a job and timestamp rather than accepting “that is probably the build system.”
Inspect repositories and workflows for impact
Review code and configuration changes
Compare suspicious commits with the last known-good revision. Pay particular attention to dependency files, install scripts, build steps, Dockerfiles, editor tasks, pre-commit hooks and scripts that read environment variables or send data to a new endpoint. Search for obfuscated commands, encoded payloads, unusual network destinations, newly added users and changes that disable tests or security checks.
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Examine pull requests and branch controls
Check who opened, approved, merged or closed each pull request. Look for new branches, force-pushes, modified branch protection, changed CODEOWNERS rules, disabled required reviews and newly granted repository roles. An attacker may create a harmless-looking change first to test access, then alter a workflow in a later commit.
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Audit workflow runs and secrets
List workflow runs in the suspicious period, including manually dispatched, scheduled and reusable workflows. For each run, record the triggering actor, commit, runner, permissions, logs, artifacts and external URLs contacted. Determine whether the workflow could read repository, organization or cloud secrets. A successful run that only performed a normal build is different from a run that uploaded environment variables or installed an unreviewed script.
Check repository and visibility administration
Look for repositories created, transferred, archived, renamed or made public; teams added; deploy keys issued; webhooks changed; and access granted to unfamiliar applications. Compare these events with the organization’s change calendar. Unexpected visibility changes deserve immediate containment because they can expose unrelated secrets.
Use API usage and billing as corroboration
Open the provider’s usage, quota and billing views for the affected account and project. Compare request counts, models, endpoints, regions, response sizes and timestamps with deployment logs. A sudden increase outside working hours, requests from a new project, or charges that cannot be tied to a release strengthens the case for misuse.
Separate ordinary cost growth from credential theft. A retry loop, a larger codebase, a model upgrade or a newly enabled feature can raise usage without an attacker. Correlate the increase with token identity, source IP and request purpose. Preserve invoices and raw usage exports because dashboards may aggregate away the detail you need.
After containment, set spend thresholds and alerts. Use separate keys for projects or features so one leak cannot authorize every workload. The smaller each key’s permission and budget, the easier it is to distinguish a legitimate service from an unauthorized consumer.
Understand long-lived keys versus short-lived cloud tokens
Cloud platforms distinguish persistent API keys from short-lived federation or session tokens. A long-lived key may remain usable until explicitly revoked; a temporary token may expire quickly but still provide significant access during its lifetime. Investigate both classes in the same incident.
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List the issuer, audience, subject, scopes, creation and expiration times, exchange mechanism and workload identity for every token. If a short-lived token was minted repeatedly, inspect the identity or service account that issued it. Revoking a persistent key does not explain or invalidate every temporary token, and revoking a temporary token does not remove the underlying long-lived key. Track each credential separately in the timeline.
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Once initial evidence is captured, stop further use while keeping the investigation focused.
- Revoke or delete the exposed token or API key. Use the narrowest revocation control available and record the exact time, actor and result. If the provider supports disabling before deletion, preserve the identifier for investigation.
- Terminate active sessions. Log out browser, IDE and command-line sessions associated with the affected account. Revoke unfamiliar OAuth grants and device sessions.
- Change an exposed or reused password. Use a new password that was never used elsewhere. Require multifactor authentication again and review recovery methods.
- Block immediate persistence. Disable unfamiliar webhooks, deploy keys, applications, service accounts, workflow schedules and newly granted roles after preserving their configuration.
- Protect connected systems. If the token could reach a cloud account, package registry, database, issue tracker or deployment service, apply that system’s revocation and emergency controls as well.
Containment should not stop at the first key. Assume related secrets may have been copied if they were present in the same file, log, runner or repository.
Rotate and repair every copy
- Generate replacements. Create new credentials with the minimum scopes, a short expiration where practical and ownership tied to a project or service rather than an individual.
- Update secret stores. Replace values in repository, organization, environment, CI/CD, container, deployment and local-development stores. Confirm which version each workload actually reads.
- Remove the exposed value. Delete it from current files, logs, artifacts and documentation. Purge it from history and caches using your source-control procedure, but retain a protected forensic copy when policy permits.
- Redeploy and verify. Restart services or jobs that cache credentials. Make a controlled test request with the replacement and confirm the revoked value fails.
- Rotate adjacent credentials. If the exposed process could read signing keys, cloud tokens, package credentials or database passwords, rotate those as well. Record the dependency so another system is not left running on the compromised value.
Determine scope, persistence and data access
Inventory affected assets
Enumerate every repository, organization, project, account, runner, environment and integration that could read the credential. Include forks, mirrors, archived repositories and personal workspaces. Mark each asset as confirmed affected, potentially affected or checked with no evidence.
Look for persistence
Search for new administrators, team memberships, deploy keys, personal access tokens, OAuth applications, webhooks, scheduled workflows, modified runner images and altered branch protections. Check whether an attacker created a second credential after obtaining the first. Persistence can survive the original key’s revocation.
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Identify repositories read, files downloaded, prompts or source code submitted, artifacts created and external destinations contacted. Review database, object-storage and network logs where the assistant credential could have reached them. If personal, confidential or regulated data may have left the approved boundary, involve privacy, legal and security stakeholders promptly.
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Document what is not proven
Separate confirmed events from hypotheses. “Key appeared in a public commit at 14:03 UTC” is confirmed exposure; “an attacker downloaded the repository” requires access or network evidence. This distinction prevents both underreaction and unsupported claims.
Provider-specific response guidance
OpenAI accounts and API keys
OpenAI’s account-security guidance directs users who suspect compromise to change the password, log out all sessions, delete affected API keys, review API usage and security history, and contact Support. Use environment variables or repository secrets instead of embedding keys in shipped applications. Scan automatically before publication, rotate keys periodically, separate keys by project or feature and configure spend thresholds. OpenAI states that keys detected on the public internet or in an app store are disabled immediately, so a sudden failure may be the result of protective action rather than proof of theft.
GitHub repositories and organizations
GitHub’s incident workflow is organized around assess and validate, contain, investigate, remediate, document and harden. Revoke compromised credentials, rotate related secrets, inspect persistence and record affected repositories, workflows and accounts. Enterprise teams should prepare audit-log streaming, API-request event streaming and source-IP disclosure where available, with retention and responder access defined before an incident. Review commits, pull requests, workflow runs and visibility changes because compromised credentials can be used for code injection and exfiltration.
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- Shared runners: many jobs can appear from one IP, and a runner migration can change the address without changing the owner.
- VPN or proxy egress: the visible location may belong to a gateway rather than the developer’s device.
- Scheduled automation: nightly jobs can create commits, requests or workflow runs outside office hours.
- Credential reuse: a developer may have copied a key into a second project, making legitimate activity look unfamiliar.
- Expired or disabled keys: an authentication error can reflect provider protection, expiration or a deployment that still holds the old value.
- Billing aggregation: dashboards may combine several projects or retries, hiding the request that caused the increase.
These explanations are leads to test, not reasons to close an alert. Match the event to an owner, job, token and timestamp before declaring it benign.
Controls that reduce the next incident’s blast radius
- Require multifactor authentication for every account that can issue or use credentials; a compatible FIDO2 security key can provide an additional physical factor where the provider and account policy support it.
- Use narrowly scoped, separate credentials for each project, environment and integration. Prefer short expiration periods for automation that can renew safely.
- Store secrets in environment or managed secret stores and repository secrets, never in shipped applications, source files, screenshots or logs.
- Enable secret scanning on repositories and push protection where available. Add pre-commit and CI checks so a leaked value is blocked before publication.
- Stream audit and API-request logs to protected storage, set retention that matches your incident needs and grant responders access in advance.
- Set usage, quota and spend alerts with a human escalation path. A small unexpected request is easier to investigate than an invoice received weeks later.
- Review active sessions, OAuth grants, deploy keys, webhooks, workflow permissions and organization members on a regular schedule.
- Practice a tabletop response: who exports logs, who revokes keys, who owns repository triage, who communicates with the provider and who evaluates privacy impact.
Incident record checklist
Close the investigation only after the record answers these questions:
- Which credential, account, project and scopes were involved?
- Where and when was it exposed or first suspected?
- Which audit, identity, repository, workflow and usage events corroborate or contradict misuse?
- Which IP addresses, actors, devices and automated jobs were involved?
- Which repositories, files, workflows, secrets and external systems were reachable?
- When were the credential and related secrets revoked, rotated and verified?
- Were persistence mechanisms removed and access permissions reduced?
- Could confidential, personal or regulated data have been accessed or exported?
- Which alerts, retention settings, ownership rules or procedures will be changed?
The practical test is correlation: an exposed or suspicious credential plus matching unauthorized activity is a strong compromise case; an isolated error is not. Preserve the record, contain promptly, rotate every connected secret and investigate code, workflows, sessions and data access before returning the account to normal use.
Quick Recap
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