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:
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 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:
audit/audit-policy.yaml
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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.
Audit backends persist audit events to an external storage. Kube-apiserver out of the box provides three backends:
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 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 rotatedWebhook 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.
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.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.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.
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.
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.
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 whitelist of stages to record.
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.
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.
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.
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.
install fluentd, fluent-plugin-forest and fluent-plugin-rewrite-tag-filter in the kube-apiserver node
Note: Fluent-plugin-forest and fluent-plugin-rewrite-tag-filter are plugins for fluentd. You can get details about plugin installation from fluentd plugin-management.
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
start fluentd
$ fluentd -c /etc/fluentd/config -vv
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
check audits for different namespaces in /var/log/audit-*.log
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.
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
start logstash
$ bin/logstash -f /etc/logstash/config --path.settings /etc/logstash/
create a kubeconfig file for kube-apiserver webhook audit backend
$ cat <<EOF > /etc/kubernetes/audit-webhook-kubeconfig
apiVersion: v1
clusters:
- cluster:
server: http://<ip_of_logstash>:8888
name: logstash
contexts:
- context:
cluster: logstash
user: ""
name: default-context
current-context: default-context
kind: Config
preferences: {}
users: []
EOF
start kube-apiserver with the following options:
--audit-policy-file=/etc/kubernetes/audit-policy.yaml --audit-webhook-config-file=/etc/kubernetes/audit-webhook-kubeconfig
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.
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