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Start by identifying the exact vulnerability and exposure window. Obtain the vendor advisory, vulnerability identifier, affected GitLab releases, the versions actually running, your deployment type (GitLab.com, Self-Managed, or Dedicated), internet exposure, and patch or mitigation times. Without those facts, a request that looks unusual cannot be reliably classified as an exploit attempt.
Then preserve logs and audit records before changing accounts or systems. Investigate in sequence: application and authentication logs, audit events, identities and privileges, repositories and CI/CD, project exposure and downloads, and—on Self-Managed—host and network telemetry. Treat every suspicious event as a lead until its timing, advisory indicators, identity, and resulting activity correlate.
1. Establish the vulnerability and the investigation window
The title of an incident report is not enough to define what to search for. Record these facts in the case file before querying GitLab:
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- The vulnerability identifier and the complete vendor advisory.
- Affected releases, the version running on each instance, and the first patched or mitigated version.
- Deployment type: GitLab.com, GitLab Self-Managed, or GitLab Dedicated.
- Whether the instance or relevant endpoints were reachable from the internet, through a proxy, or only internally.
- The time patching, mitigation, firewall changes, or other exposure-reducing actions occurred.
- The earliest and latest times during which the vulnerable code could have been reached.
The specific vulnerability, affected releases, and indicators are not identified by this article’s title. Do not invent a request signature or assume that a generic error proves code execution. Use the advisory’s affected components and indicators to define searches, then account for clock differences among GitLab, operating-system, proxy, and network systems.
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2. Preserve evidence before cleanup
Evidence can disappear when you rotate logs, revoke tokens, delete a runner, reset an account, or rebuild a host. Preserve first, contain in a controlled way, and record every action.
Create an evidence set
- GitLab application, authentication, and audit records.
- CI/CD pipeline and job logs, including artifacts and runner records.
- Reverse-proxy, load-balancer, web-application-firewall, and network-flow records that cover the exposure window.
- Operating-system, container, Kubernetes, cloud, database, and endpoint records for Self-Managed infrastructure.
- Configuration snapshots showing users, memberships, visibility, protected branches, variables, hooks, OAuth applications, and runners.
GitLab recommends saving relevant evidence to a write-once location and routing logs to an independent write-only datastore. Ordinary external storage is not automatically immutable: use retention and access controls that prevent investigators or a compromised administrator from silently altering the original records. Keep hashes or equivalent integrity records where your incident process requires them.
Maintain a decision timeline
For each event, record the source timestamp and normalized time, the collector, the user or service identity, source IP, project or group, token or runner identifier, and the action taken. Add the exact time a suspected account was blocked, credentials were reset, tokens were revoked, secrets were rotated, or a host was isolated. This prevents a containment action from being mistaken for attacker behavior and shows which evidence was available before remediation.
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3. Match evidence to the GitLab deployment
GitLab’s useful telemetry differs by offering, tier, configuration, and retention. Sign-in audit events are available on all tiers; broader audit-event coverage is listed by GitLab for Premium and Ultimate. Self-Managed operators also control system logs and the infrastructure below GitLab.
| Evidence source | What it can show | Important qualification |
|---|---|---|
| Application logs | Requests, errors, and attempts to exploit known vulnerabilities | GitLab specifically describes vulnerability-exploit attempts as recorded in application logs for GitLab Self-Managed. |
| Audit events | Sign-ins, authentication changes, permission and membership changes, project or group settings, and other administrative actions | Event availability depends on offering, tier, configuration, and retention. |
| CI/CD job logs | Commands run by jobs, secret exposure, unusual pipelines, and artifact creation | Retention and masking settings determine what remains visible. |
| Self-Managed host and network records | Process execution, files, outbound connections, proxy requests, and activity on the underlying infrastructure | Self-Managed operators are responsible for collecting and protecting this telemetry. |
| GitLab.com or Dedicated service records | GitLab-side events exposed through the service’s audit and account interfaces | You do not receive the same host-level evidence available to a Self-Managed operator; use the provider’s incident and support channels for service-side investigation. |
Do not copy a Self-Managed log path into a GitLab.com investigation. Conversely, do not assume that an audit event proves what happened on a Self-Managed host; correlate both layers.
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4. Search application logs for exploitation attempts
GitLab’s Security Operations guidance says: “Attempts to exploit known vulnerabilities in GitLab Self-Managed, recorded in application logs.” This makes application logs a primary place to test the advisory’s indicators on Self-Managed installations.
Build an advisory-driven search
- Translate the advisory into the affected endpoint, method, parameter, component, authentication requirement, and time range. Use the exact indicators supplied by GitLab for that vulnerability.
- Search the application logs covering the entire potentially vulnerable window, including a buffer for clock skew and delayed ingestion.
- Join candidate requests to reverse-proxy and network records so you can verify source addresses, forwarded addresses, response status, bytes, and request timing.
- Check whether the request reached a vulnerable component and whether it was followed by authentication, token, repository, pipeline, or host activity.
- Preserve matching records and their surrounding context before rotating or filtering the logs.
A generic HTTP error, scanner probe, blocked request, or isolated suspicious parameter is not proof that code executed. A candidate becomes more significant when it matches the advisory, occurs during exposure, reaches the affected component, and is followed by changes or execution that the same identity, address, token, runner, or host can explain.
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After checking requests, inspect identities for persistence and privilege escalation. Start with the earliest suspicious time and compare activity before and after it.
Authentication and account activity
- Sign-ins from new or implausible locations, addresses, user agents, or times.
- New users, disabled users becoming active, changed email addresses, and altered notification settings.
- Administrator actions that were not expected for the operator’s role or maintenance schedule.
- Two-factor authentication enrollment, removal, recovery-code use, or policy changes.
- OAuth applications added or granted new scopes, including applications that remain after the incident.
- SAML configuration or identity-provider changes.
Credentials that can provide persistence
- Personal, group, and project access tokens, including newly created tokens, scope changes, and unusual use.
- Deploy tokens and deploy keys added to projects or groups.
- SSH and GPG keys added, replaced, or removed.
- Service accounts, bot users, and runner registration tokens.
For every credential, record its owner, scopes, creation and last-use times, source addresses, projects or groups reached, and whether it could read or write production systems. A token created after a suspicious request is a strong lead, but it still needs correlation with the account, source, and resulting activity.
6. Inspect repositories, merge controls, and CI/CD
Code execution in the GitLab service can be followed by repository or pipeline changes designed to steal secrets, create persistence, or alter delivered software. Review changes in chronological order rather than looking only at the current state.
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Repository and approval checks
- Unexpected commits, branches, tags, merge requests, force-pushes, or deletions.
- Changes to protected branches, protected tags, merge-request approval rules, or required reviewers.
- New or modified webhooks, server hooks, integrations, and project or group access.
- Source changes that invoke shells, download tools, alter build scripts, or read credential files.
Inspect the code called by each suspicious file, not just the visible diff. GitLab warns that suspicious modifications can expose secrets. Compare changes with the author identity, access token, source address, pipeline, runner, and normal release process.
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- Pipelines started outside the normal branch, merge, schedule, or deployment pattern.
- Jobs that run unusual commands, contact unfamiliar hosts, archive environment variables, or alter runner configuration.
- New runners, changed runner tags, altered executor settings, and runners shared with projects that should be isolated.
- CI/CD variables whose values, masking, protection, or scope changed.
- Artifacts that contain credentials, source archives, unexpected binaries, or unusually large data.
- Job logs showing commands that were not present in the reviewed commit.
Preserve the job log and artifact metadata before deleting a pipeline or runner. If a secret may have been printed or embedded in an artifact, treat it as exposed even when the log is later masked.
7. Check project and group exposure, downloads, and exfiltration
Review configuration and access events that could make private material visible or help an attacker remove it.
- Project or group visibility changes, especially private-to-internal or private-to-public transitions.
- Changes to group membership, project membership, sharing links, and inherited permissions.
- Merge-request approval settings and protected-branch rules weakened or removed.
- Repository, project, group, or artifact exports and downloads outside the normal workflow.
- Bursts of repository clones, archive downloads, package downloads, or artifact downloads.
- Unexpected deploy credentials, hooks, webhooks, or integrations that send data to an external endpoint.
- Project or group deletion, restoration, transfer, or renaming that obscures history.
Use audit-event filters by target type when they narrow the search to a project, group, user, token, or setting. Compare download volume and timing with release activity and known automation; a large transfer by a legitimate build system may be expected, while a smaller transfer from a new account may be more informative.
8. Use the Audit Events API without losing the time window
The Audit Events API supports created_after and created_before ISO-8601 filters, plus entity type and entity ID filters. The instance endpoint requires administrator authentication and permits a maximum 30-day window per query. Investigations covering more than 30 days must use multiple bounded queries whose boundaries are recorded.
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- Choose an ISO-8601 start and end time based on the exposure window and a documented clock buffer.
- Query a period of 30 days or less, adding entity filters when you know the user, project, group, or other target.
- Save the raw response, request parameters, retrieval time, and administrator identity in the evidence store.
- Repeat for adjacent periods until the entire window is covered. Use non-overlapping boundaries or document any overlap so events are not double-counted.
- Normalize event timestamps and correlate each event with application, proxy, CI/CD, host, and network records.
API availability and event detail are tiered. A missing event can mean that the event type was not available, was not retained, was outside the selected entity scope, or was never generated; it is not by itself evidence that no activity occurred.
9. Find the audit log on Self-Managed installations
Confirm the deployment method before opening a path. For Linux package installations, GitLab documents the audit log at /var/log/gitlab/gitlab-rails/audit_json.log. For self-compiled installations, it is /home/git/gitlab/log/audit_json.log. In Helm deployments, the log is exposed on Sidekiq and Webservice pods under subcomponent="audit_json".
Group and project setting changes and membership changes are recorded with target_details. Collect the relevant files or pod output with timestamps and preserve the original records. Paths, pod names, rotation policies, and retention differ by installation, so verify them against the running deployment rather than assuming one path applies everywhere.
10. Correlate events and determine scope
Build a relationship map instead of treating each log line as an isolated incident. For every candidate, align:
- Timestamp and time-zone conversion.
- User, service account, token, SSH key, OAuth application, or runner.
- Source IP, forwarded IP, user agent, proxy request, and network connection.
- Instance, group, project, repository, branch, pipeline, job, artifact, and runner.
- Host, container, pod, process, file, outbound destination, and cloud identity for Self-Managed.
Scope is the set of systems and credentials that can be connected by these facts. Include projects touched by a compromised token, groups that inherited changed permissions, runners that executed altered jobs, and secrets available to those jobs. For Self-Managed, GitLab’s guidance places responsibility for the underlying infrastructure with the operator, so inspect host and network telemetry alongside GitLab records. A GitLab-side event cannot rule out activity performed directly on the host.
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11. Interpret suspicious signals carefully
Use three questions for each lead:
- Does it match the advisory? The request or change should involve the affected component or a credible follow-on action.
- Did it occur during exposure? Timing must overlap the vulnerable version and reachable window, allowing for clock differences.
- What did it cause? Look for a resulting account, credential, repository, pipeline, configuration, host, or network event.
An exploit attempt can be recorded without successful code execution. Conversely, the absence of a matching request does not prove safety when logs are incomplete, rotated, filtered, or collected after the fact. State confidence explicitly: confirmed, probable, possible, or unsubstantiated, and list the evidence supporting that assessment.
12. Contain and remediate a confirmed compromise
Containment should be proportionate to the evidence and coordinated with service owners so that rotating a production credential does not cause an avoidable outage.
- Block or suspend a suspected compromised user and preserve the account’s audit history.
- Reset credentials the account could access, including personal, group, project, deploy, SSH, GPG, runner, and automation credentials.
- Revoke suspicious access tokens, OAuth grants, deploy keys, hooks, webhooks, and runner registrations.
- Rotate secrets exposed through repositories, job logs, artifacts, variables, or host processes. Prioritize credentials that can change production systems.
- Restore unauthorized memberships, visibility, protected-branch rules, approval settings, variables, hooks, and integrations with their owners.
- Quarantine altered runners, hosts, containers, or images and preserve forensic copies before rebuilding.
- Patch or update every affected GitLab installation and verify that the mitigation is active.
- Continue monitoring for reuse of revoked credentials, recreated accounts, new tokens, repeated requests, and delayed exfiltration.
Document the exact exposure and revocation time for each credential. If unauthorized code or configuration was committed, have the responsible owners validate the restored state and review downstream releases, packages, and deployments.
13. Make the next investigation faster
GitLab recommends centralizing events in a SIEM or other log-analysis platform, streaming them when available or collecting them on a schedule, and routing records to independent write-once storage. Define retention that exceeds the longest plausible vulnerability window and test that records can be searched by time, user, source address, project, token, and runner.
GitLab also maintains the open-source TLDR detection framework. Its detections describe required log sources, sample events, Sigma rules or raw queries, and response guidance. Adapt those detections to the telemetry your deployment actually retains; a rule cannot recover a log source that was never collected.
Finally, rehearse the workflow: identify the advisory, preserve evidence, query bounded windows, correlate identities and infrastructure, rotate credentials with owners, and record every decision. That preparation is what turns a suspicious request into a defensible incident determination.
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