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Auditing

Kubernetes auditing provides a security-relevant chronological set of records documenting the sequence of activities that have affected system by individual users, administrators or other components of the system. It allows cluster administrator to answer the following questions:

  • what happened?
  • when did it happen?
  • who initiated it?
  • on what did it happen?
  • where was it observed?
  • from where was it initiated?
  • to where was it going?

Kube-apiserver performs auditing. Each request on each stage of its execution generates an event, which is then pre-processed according to a certain policy and written to a backend. The policy determines what's recorded and the backends persist the records. The current backend implementations include logs files and webhooks.

Each request can be recorded with an associated "stage". The known stages are:

  • RequestReceived - The stage for events generated as soon as the audit handler receives the request, and before it is delegated down the handler chain.
  • ResponseStarted - Once the response headers are sent, but before the response body is sent. This stage is only generated for long-running requests (e.g. watch).
  • ResponseComplete - The response body has been completed and no more bytes will be sent.
  • Panic - Events generated when a panic occurred.
Note: The audit logging feature increases the memory consumption of the API server because some context required for auditing is stored for each request. Additionally, memory consumption depends on the audit logging configuration.

Audit Policy

Audit policy defines rules about what events should be recorded and what data they should include. The audit policy object structure is defined in the audit.k8s.io API group. When an event is processed, it's compared against the list of rules in order. The first matching rule sets the "audit level" of the event. The known audit levels are:

  • None - don't log events that match this rule.
  • Metadata - log request metadata (requesting user, timestamp, resource, verb, etc.) but not request or response body.
  • Request - log event metadata and request body but not response body. This does not apply for non-resource requests.
  • RequestResponse - log event metadata, request and response bodies. This does not apply for non-resource requests.

You can pass a file with the policy to kube-apiserver using the --audit-policy-file flag. If the flag is omitted, no events are logged. Note that the rules field must be provided in the audit policy file. A policy with no (0) rules is treated as illegal.

Below is an example audit policy file:

apiVersion: audit.k8s.io/v1 # This is required.
kind: Policy
# Don't generate audit events for all requests in RequestReceived stage.
omitStages:
  - "RequestReceived"
rules:
  # Log pod changes at RequestResponse level
  - level: RequestResponse
    resources:
    - group: ""
      # Resource "pods" doesn't match requests to any subresource of pods,
      # which is consistent with the RBAC policy.
      resources: ["pods"]
  # Log "pods/log", "pods/status" at Metadata level
  - level: Metadata
    resources:
    - group: ""
      resources: ["pods/log", "pods/status"]

  # Don't log requests to a configmap called "controller-leader"
  - level: None
    resources:
    - group: ""
      resources: ["configmaps"]
      resourceNames: ["controller-leader"]

  # Don't log watch requests by the "system:kube-proxy" on endpoints or services
  - level: None
    users: ["system:kube-proxy"]
    verbs: ["watch"]
    resources:
    - group: "" # core API group
      resources: ["endpoints", "services"]

  # Don't log authenticated requests to certain non-resource URL paths.
  - level: None
    userGroups: ["system:authenticated"]
    nonResourceURLs:
    - "/api*" # Wildcard matching.
    - "/version"

  # Log the request body of configmap changes in kube-system.
  - level: Request
    resources:
    - group: "" # core API group
      resources: ["configmaps"]
    # This rule only applies to resources in the "kube-system" namespace.
    # The empty string "" can be used to select non-namespaced resources.
    namespaces: ["kube-system"]

  # Log configmap and secret changes in all other namespaces at the Metadata level.
  - level: Metadata
    resources:
    - group: "" # core API group
      resources: ["secrets", "configmaps"]

  # Log all other resources in core and extensions at the Request level.
  - level: Request
    resources:
    - group: "" # core API group
    - group: "extensions" # Version of group should NOT be included.

  # A catch-all rule to log all other requests at the Metadata level.
  - level: Metadata
    # Long-running requests like watches that fall under this rule will not
    # generate an audit event in RequestReceived.
    omitStages:
      - "RequestReceived"

You can use a minimal audit policy file to log all requests at the Metadata level:

# Log all requests at the Metadata level.
apiVersion: audit.k8s.io/v1
kind: Policy
rules:
- level: Metadata

The audit profile used by GCE should be used as reference by admins constructing their own audit profiles. You can check the configure-helper.sh script, which generates the audit policy file. You can see most of the audit policy file by looking directly at the script.

Audit backends

Audit backends persist audit events to an external storage. Kube-apiserver out of the box provides three backends:

  • Log backend, which writes events to a disk
  • Webhook backend, which sends events to an external API
  • Dynamic backend, which configures webhook backends through an AuditSink API object.

In all cases, audit events structure is defined by the API in the audit.k8s.io API group. The current version of the API is v1.

Note:

In case of patches, request body is a JSON array with patch operations, not a JSON object with an appropriate Kubernetes API object. For example, the following request body is a valid patch request to /apis/batch/v1/namespaces/some-namespace/jobs/some-job-name.

[
  {
    "op": "replace",
    "path": "/spec/parallelism",
    "value": 0
  },
  {
    "op": "remove",
    "path": "/spec/template/spec/containers/0/terminationMessagePolicy"
  }
]

Log backend

Log backend writes audit events to a file in JSON format. You can configure log audit backend using the following kube-apiserver flags:

  • --audit-log-path specifies the log file path that log backend uses to write audit events. Not specifying this flag disables log backend. - means standard out
  • --audit-log-maxage defined the maximum number of days to retain old audit log files
  • --audit-log-maxbackup defines the maximum number of audit log files to retain
  • --audit-log-maxsize defines the maximum size in megabytes of the audit log file before it gets rotated

In case kube-apiserver is configured as a Pod,remember to mount the hostPath to the location of the policy file and log file. For example, --audit-policy-file=/etc/kubernetes/audit-policy.yaml --audit-log-path=/var/log/audit.log then mount the volumes:

volumeMounts:
  - mountPath: /etc/kubernetes/audit-policy.yaml
    name: audit
    readOnly: true
  - mountPath: /var/log/audit.log
    name: audit-log
    readOnly: false

finally the hostPath:

- name: audit
  hostPath:
    path: /etc/kubernetes/audit-policy.yaml
    type: File

- name: audit-log
  hostPath:
    path: /var/log/audit.log
    type: FileOrCreate

Webhook backend

Webhook backend sends audit events to a remote API, which is assumed to be the same API as kube-apiserver exposes. You can configure webhook audit backend using the following kube-apiserver flags:

  • --audit-webhook-config-file specifies the path to a file with a webhook configuration. Webhook configuration is effectively a kubeconfig.
  • --audit-webhook-initial-backoff specifies the amount of time to wait after the first failed request before retrying. Subsequent requests are retried with exponential backoff.

The webhook config file uses the kubeconfig format to specify the remote address of the service and credentials used to connect to it.

In v1.13 webhook backends can be configured dynamically.

Batching

Both log and webhook backends support batching. Using webhook as an example, here's the list of available flags. To get the same flag for log backend, replace webhook with log in the flag name. By default, batching is enabled in webhook and disabled in log. Similarly, by default throttling is enabled in webhook and disabled in log.

  • --audit-webhook-mode defines the buffering strategy. One of the following:
    • batch - buffer events and asynchronously process them in batches. This is the default.
    • blocking - block API server responses on processing each individual event.
    • blocking-strict - Same as blocking, but when there is a failure during audit logging at RequestReceived stage, the whole request to apiserver will fail.

The following flags are used only in the batch mode.

  • --audit-webhook-batch-buffer-size defines the number of events to buffer before batching. If the rate of incoming events overflows the buffer, events are dropped.
  • --audit-webhook-batch-max-size defines the maximum number of events in one batch.
  • --audit-webhook-batch-max-wait defines the maximum amount of time to wait before unconditionally batching events in the queue.
  • --audit-webhook-batch-throttle-qps defines the maximum average number of batches generated per second.
  • --audit-webhook-batch-throttle-burst defines the maximum number of batches generated at the same moment if the allowed QPS was underutilized previously.

Parameter tuning

Parameters should be set to accommodate the load on the apiserver.

For example, if kube-apiserver receives 100 requests each second, and each request is audited only on ResponseStarted and ResponseComplete stages, you should account for ~200 audit events being generated each second. Assuming that there are up to 100 events in a batch, you should set throttling level at least 2 QPS. Assuming that the backend can take up to 5 seconds to write events, you should set the buffer size to hold up to 5 seconds of events, i.e. 10 batches, i.e. 1000 events.

In most cases however, the default parameters should be sufficient and you don't have to worry about setting them manually. You can look at the following Prometheus metrics exposed by kube-apiserver and in the logs to monitor the state of the auditing subsystem.

  • apiserver_audit_event_total metric contains the total number of audit events exported.
  • apiserver_audit_error_total metric contains the total number of events dropped due to an error during exporting.

Truncate

Both log and webhook backends support truncating. As an example, the following is the list of flags available for the log backend:

  • audit-log-truncate-enabled whether event and batch truncating is enabled.
  • audit-log-truncate-max-batch-size maximum size in bytes of the batch sent to the underlying backend.
  • audit-log-truncate-max-event-size maximum size in bytes of the audit event sent to the underlying backend.

By default truncate is disabled in both webhook and log, a cluster administrator should set audit-log-truncate-enabled or audit-webhook-truncate-enabled to enable the feature.

Dynamic backend

FEATURE STATE: Kubernetes v1.13 [alpha]

In Kubernetes version 1.13, you can configure dynamic audit webhook backends AuditSink API objects.

To enable dynamic auditing you must set the following apiserver flags:

  • --audit-dynamic-configuration: the primary switch. When the feature is at GA, the only required flag.
  • --feature-gates=DynamicAuditing=true: feature gate at alpha and beta.
  • --runtime-config=auditregistration.k8s.io/v1alpha1=true: enable API.

When enabled, an AuditSink object can be provisioned:

apiVersion: auditregistration.k8s.io/v1alpha1
kind: AuditSink
metadata:
  name: mysink
spec:
  policy:
    level: Metadata
    stages:
    - ResponseComplete
  webhook:
    throttle:
      qps: 10
      burst: 15
    clientConfig:
      url: "https://audit.app"

For the complete API definition, see AuditSink. Multiple objects will exist as independent solutions. The name of an AuditSink object must be a valid DNS subdomain name.

Existing static backends that you configure with runtime flags are not affected by this feature. However, the dynamic backends share the truncate options of the static webhook. If webhook truncate options are set with runtime flags, they are applied to all dynamic backends.

Policy

The AuditSink policy differs from the legacy audit runtime policy. This is because the API object serves different use cases. The policy will continue to evolve to serve more use cases.

The level field applies the given audit level to all requests. The stages field is now a list of allowed stages to record.

Contacting the webhook

Once the API server has determined a request should be sent to a audit sink webhook, it needs to know how to contact the webhook. This is specified in the clientConfig stanza of the webhook configuration.

Audit sink webhooks can either be called via a URL or a service reference, and can optionally include a custom CA bundle to use to verify the TLS connection.

URL

url gives the location of the webhook, in standard URL form (scheme://host:port/path).

The host should not refer to a service running in the cluster; use a service reference by specifying the service field instead. The host might be resolved via external DNS in some apiservers (i.e., kube-apiserver cannot resolve in-cluster DNS as that would be a layering violation). host may also be an IP address.

Please note that using localhost or 127.0.0.1 as a host is risky unless you take great care to run this webhook on all hosts which run an apiserver which might need to make calls to this webhook. Such installs are likely to be non-portable, i.e., not easy to turn up in a new cluster.

The scheme must be "https"; the URL must begin with "https://".

Attempting to use a user or basic auth (for example "user:password@") is not allowed. Fragments ("#...") and query parameters ("?...") are also not allowed.

Here is an example of a webhook configured to call a URL (and expects the TLS certificate to be verified using system trust roots, so does not specify a caBundle):

apiVersion: auditregistration.k8s.io/v1alpha1
kind: AuditSink
...
spec:
  webhook:
    clientConfig:
      url: "https://my-webhook.example.com:9443/my-webhook-path"
Service Reference

The service stanza inside clientConfig is a reference to the service for a audit sink webhook. If the webhook is running within the cluster, then you should use service instead of url. The service namespace and name are required. The port is optional and defaults to 443. The path is optional and defaults to "/".

Here is an example of a webhook that is configured to call a service on port "1234" at the subpath "/my-path", and to verify the TLS connection against the ServerName my-service-name.my-service-namespace.svc using a custom CA bundle.

apiVersion: auditregistration.k8s.io/v1alpha1
kind: AuditSink
...
spec:
  webhook:
    clientConfig:
      service:
        namespace: my-service-namespace
        name: my-service-name
        path: /my-path
        port: 1234
      caBundle: "Ci0tLS0tQk...<base64-encoded PEM bundle>...tLS0K"

Security

Administrators should be aware that allowing write access to this feature grants read access to all cluster data. Access should be treated as a cluster-admin level privilege.

Performance

Currently, this feature has performance implications for the apiserver in the form of increased cpu and memory usage. This should be nominal for a small number of sinks, and performance impact testing will be done to understand its scope before the API progresses to beta.

Setup for multiple API servers

If you're extending the Kubernetes API with the aggregation layer, you can also set up audit logging for the aggregated apiserver. To do this, pass the configuration options in the same format as described above to the aggregated apiserver and set up the log ingesting pipeline to pick up audit logs. Different apiservers can have different audit configurations and different audit policies.

Log Collector Examples

Use fluentd to collect and distribute audit events from log file

Fluentd is an open source data collector for unified logging layer. In this example, we will use fluentd to split audit events by different namespaces.

Note: The fluent-plugin-forest and fluent-plugin-rewrite-tag-filter are plugins for fluentd. You can get details about plugin installation from fluentd plugin-management.

  1. Install fluentd, fluent-plugin-forest and fluent-plugin-rewrite-tag-filter in the kube-apiserver node

  2. Create a config file for fluentd

    cat <<'EOF' > /etc/fluentd/config
# fluentd conf runs in the same host with kube-apiserver
<source>
    @type tail
    # audit log path of kube-apiserver
    path /var/log/kube-audit
    pos_file /var/log/audit.pos
    format json
    time_key time
    time_format %Y-%m-%dT%H:%M:%S.%N%z
    tag audit
</source>

<filter audit>
    #https://github.com/fluent/fluent-plugin-rewrite-tag-filter/issues/13
    @type record_transformer
    enable_ruby
    <record>
     namespace ${record["objectRef"].nil? ? "none":(record["objectRef"]["namespace"].nil? ? "none":record["objectRef"]["namespace"])}
    </record>
</filter>

<match audit>
    # route audit according to namespace element in context
    @type rewrite_tag_filter
    <rule>
        key namespace
        pattern /^(.+)/
        tag ${tag}.$1
    </rule>
</match>

<filter audit.**>
   @type record_transformer
   remove_keys namespace
</filter>

<match audit.**>
    @type forest
    subtype file
    remove_prefix audit
    <template>
        time_slice_format %Y%m%d%H
        compress gz
        path /var/log/audit-${tag}.*.log
        format json
        include_time_key true
    </template>
</match>
EOF

  3. Start fluentd

    fluentd -c /etc/fluentd/config  -vv

  4. Start kube-apiserver with the following options:

    --audit-policy-file=/etc/kubernetes/audit-policy.yaml --audit-log-path=/var/log/kube-audit --audit-log-format=json

  5. Check audits for different namespaces in /var/log/audit-*.log

Use logstash to collect and distribute audit events from webhook backend

Logstash is an open source, server-side data processing tool. In this example, we will use logstash to collect audit events from webhook backend, and save events of different users into different files.

  1. install logstash

  2. create config file for logstash

    cat <<EOF > /etc/logstash/config
input{
    http{
        #TODO, figure out a way to use kubeconfig file to authenticate to logstash
        #https://www.elastic.co/guide/en/logstash/current/plugins-inputs-http.html#plugins-inputs-http-ssl
        port=>8888
    }
}
filter{
    split{
        # Webhook audit backend sends several events together with EventList
        # split each event here.
        field=>[items]
        # We only need event subelement, remove others.
        remove_field=>[headers, metadata, apiVersion, "@timestamp", kind, "@version", host]
    }
    mutate{
        rename => {items=>event}
    }
}
output{
    file{
        # Audit events from different users will be saved into different files.
        path=>"/var/log/kube-audit-%{[event][user][username]}/audit"
    }
}
EOF

  3. start logstash

    bin/logstash -f /etc/logstash/config --path.settings /etc/logstash/

  4. create a kubeconfig file for kube-apiserver webhook audit backend

     cat <<EOF > /etc/kubernetes/audit-webhook-kubeconfig
 apiVersion: v1
 kind: Config
 clusters:
 - cluster:
     server: http://<ip_of_logstash>:8888
   name: logstash
 contexts:
 - context:
     cluster: logstash
     user: ""
   name: default-context
 current-context: default-context
 preferences: {}
 users: []
 EOF

  5. start kube-apiserver with the following options:

    --audit-policy-file=/etc/kubernetes/audit-policy.yaml --audit-webhook-config-file=/etc/kubernetes/audit-webhook-kubeconfig

  6. check audits in logstash node's directories /var/log/kube-audit-*/audit

Note that in addition to file output plugin, logstash has a variety of outputs that let users route data where they want. For example, users can emit audit events to elasticsearch plugin which supports full-text search and analytics.

What's next

Learn about Mutating webhook auditing annotations.