Detection rules › Elastic

GKE API Request Impersonating Privileged Identity

Status
production
Severity
high
Time window
6m
Author
Elastic
Source
github.com/elastic/detection-rules

Detects GKE API requests where a caller is impersonating a privileged cluster identity such as system:kube-controller-manager, system:admin, system:anonymous, or a kube-system service account. These identities have broad cluster-wide permissions including unrestricted access to secrets, the ability to create tokens for any service account, schedule pods on any node, and modify RBAC. Impersonating system:kube-controller-manager grants access to secrets across namespaces and service account token minting for lateral movement.

Known false positives

  • Break-glass admin tooling, security scanners, or approved controllers that legitimately use impersonation against privileged targets may match. Map expected callers and expand client.user.email exclusions as needed.

MITRE ATT&CK coverage

TacticTechniques
Privilege Escalation
Stealth

Rule body

[metadata]
creation_date = "2026/07/13"
integration = ["gcp"]
maturity = "production"
updated_date = "2026/07/13"

[rule]
author = ["Elastic"]
description = """
Detects GKE API requests where a caller is impersonating a privileged cluster identity such as
system:kube-controller-manager, system:admin, system:anonymous, or a kube-system service account. These identities have
broad cluster-wide permissions including unrestricted access to secrets, the ability to create tokens for any service
account, schedule pods on any node, and modify RBAC. Impersonating system:kube-controller-manager grants access to
secrets across namespaces and service account token minting for lateral movement.
"""
false_positives = [
    """
    Break-glass admin tooling, security scanners, or approved controllers that legitimately use impersonation against
    privileged targets may match. Map expected callers and expand client.user.email exclusions as needed.
    """,
]
from = "now-6m"
index = ["logs-gcp.audit-*"]
language = "kuery"
license = "Elastic License v2"
name = "GKE API Request Impersonating Privileged Identity"
note = """## Triage and analysis

### Investigating GKE API Request Impersonating Privileged Identity

Compare the real actor (`client.user.email`, `source.ip`, `user_agent.original`) with the impersonated identity in
`gcp.audit.authentication_info.authority_selector` (Cloud Audit `authenticationInfo.authoritySelector`). Confirm
whether impersonation is authorized for that principal and target identity.

### Possible investigation steps

- Review `event.action` and `gcp.audit.resource_name` for the scope of the operation performed while impersonating.
- Determine whether the real user or service account should have `impersonate` rights against the target user or group;
  inspect RBAC bindings and any recent changes.
- Correlate with adjacent audit activity (secrets, TokenRequest, RBAC writes, CSR approval) from the same source
  identity.
- Hunt for repeated impersonation across namespaces or rapid pivoting after the event.

### False positive analysis

- Approved admin or scanner workflows that intentionally use `kubectl --as` against privileged targets may match.
  Allowlist those identities after review.

### Response and remediation

- Revoke or tighten `impersonate` permissions for unexpected identities; rotate credentials for any account that may
  have abused impersonation.
- If unauthorized, treat as cluster-wide credential risk: review secrets exposure, issued tokens, and RBAC drift.

"""
setup = """
The GCP Fleet integration with GKE audit logs enabled is required. Kubernetes impersonation (`kubectl --as`) maps to
`gcp.audit.authentication_info.authority_selector` in Fleet.
"""
references = [
    "https://kubernetes.io/docs/reference/access-authn-authz/authentication/#user-impersonation",
    "https://kubernetes.io/docs/reference/access-authn-authz/user-impersonation/",
]
risk_score = 73
rule_id = "00c2a946-bbe8-4345-941d-9ea13da91600"
severity = "high"
tags = [
    "Domain: Cloud",
    "Domain: Kubernetes",
    "Data Source: GCP",
    "Data Source: Google Cloud Platform",
    "Use Case: Threat Detection",
    "Tactic: Privilege Escalation",
    "Tactic: Defense Evasion",
    "Resources: Investigation Guide",
]
timestamp_override = "event.ingested"
type = "query"

query = '''
data_stream.dataset:gcp.audit and service.name:"k8s.io" and event.outcome:success and
gcp.audit.authentication_info.authority_selector:(
  "admin" or "cluster-admin" or "kubernetes-admin" or "system:admin" or "system:anonymous" or
  "system:apiserver" or "system:kube-controller-manager" or "system:kube-proxy" or
  "system:kube-scheduler" or "system:volume-scheduler" or
  system\:node\:* or system\:serviceaccount\:kube-system\:*
) and
not client.user.email:(
  "system:kube-controller-manager" or
  "system:kube-scheduler" or
  system\:node\:* or
  system\:serviceaccount\:kube-system\:*
)
'''

[[rule.threat]]
framework = "MITRE ATT&CK"

[[rule.threat.technique]]
id = "T1134"
name = "Access Token Manipulation"
reference = "https://attack.mitre.org/techniques/T1134/"

[rule.threat.tactic]
id = "TA0004"
name = "Privilege Escalation"
reference = "https://attack.mitre.org/tactics/TA0004/"

[[rule.threat]]
framework = "MITRE ATT&CK"

[[rule.threat.technique]]
id = "T1134"
name = "Access Token Manipulation"
reference = "https://attack.mitre.org/techniques/T1134/"

[rule.threat.tactic]
id = "TA0005"
name = "Defense Evasion"
reference = "https://attack.mitre.org/tactics/TA0005/"

[rule.investigation_fields]
field_names = [
    "@timestamp",
    "client.user.email",
    "source.ip",
    "user_agent.original",
    "event.action",
    "event.outcome",
    "gcp.audit.authentication_info.authority_selector",
    "gcp.audit.resource_name",
    "data_stream.namespace",
]

Stages and Predicates

Stage 1: query

data_stream.dataset:gcp.audit and service.name:"k8s.io" and event.outcome:success and
gcp.audit.authentication_info.authority_selector:(
  "admin" or "cluster-admin" or "kubernetes-admin" or "system:admin" or "system:anonymous" or
  "system:apiserver" or "system:kube-controller-manager" or "system:kube-proxy" or
  "system:kube-scheduler" or "system:volume-scheduler" or
  system\:node\:* or system\:serviceaccount\:kube-system\:*
) and
not client.user.email:(
  "system:kube-controller-manager" or
  "system:kube-scheduler" or
  system\:node\:* or
  system\:serviceaccount\:kube-system\:*
)

Exclusions

The rule actively suppresses these predicates.

FieldKindExcluded valuesSearch
client.user.emaileqsystem:kube-controller-managerexcludes:client.user.email field:"client.user.email" value:"system:kube-controller-manager"
client.user.emaileqsystem:kube-schedulerexcludes:client.user.email field:"client.user.email" value:"system:kube-scheduler"
client.user.emailstarts_withsystem:node:excludes:client.user.email field:"client.user.email" value:"system:node:"
client.user.emailstarts_withsystem:serviceaccount:kube-system:excludes:client.user.email field:"client.user.email" value:"system:serviceaccount:kube-system:"

Indicators

These rows show field, operator, and value matches.

FieldKindValuesSearch
data_stream.dataseteq
  • gcp.audit
field:"data_stream.dataset" kind:eq value:"gcp.audit"
event.outcomeeq
  • success
field:"event.outcome" kind:eq value:"success"
gcp.audit.authentication_info.authority_selectoreq
  • admin
  • cluster-admin
  • kubernetes-admin
  • system:admin
  • system:anonymous
  • system:apiserver
  • system:kube-controller-manager
  • system:kube-proxy
  • system:kube-scheduler
  • system:volume-scheduler
field:"gcp.audit.authentication_info.authority_selector" kind:eq
gcp.audit.authentication_info.authority_selectorwildcard
  • system:node:*
  • system:serviceaccount:kube-system:*
field:"gcp.audit.authentication_info.authority_selector" kind:wildcard
service.nameeq
  • k8s.io
field:"ServiceName" kind:eq value:"k8s.io"