Anthropic Multiple Authentication Failures

  1[metadata]
  2creation_date = "2026/09/12"
  3integration = ["anthropic"]
  4maturity = "production"
  5updated_date = "2026/09/21"
  6
  7[rule]
  8author = ["Elastic"]
  9description = """
 10Detects at least five failed Anthropic authentication events for the same user email within one hour.
 11Failures are matched by authentication category and failure outcome (for example magic-link or SSO login
 12failures). That pattern fits repeated guessing, stale magic link abuse, or automated login attempts against
 13one account.
 14"""
 15false_positives = [
 16    """
 17    A user repeatedly clicking an expired or invalid magic link from the same browser session can produce several
 18    failures before requesting a new link or signing in successfully.
 19    """,
 20    """
 21    IdP or SSO cutover testing against a pilot account can generate a short burst of failed attempts for one email
 22    during maintenance windows.
 23    """,
 24]
 25from = "now-60m"
 26interval = "15m"
 27language = "esql"
 28license = "Elastic License v2"
 29name = "Anthropic Multiple Authentication Failures"
 30note = """## Triage and analysis
 31
 32### Investigating Anthropic Multiple Authentication Failures
 33
 34One mailbox produced a burst of authentication failures (magic-link, SSO, or other auth failures) within an hour.
 35Use IP diversity on the alert to separate focused retries from distributed automation.
 36
 37Escalate when many distinct IPs hit one email, failures precede a successful login from an unfamiliar IP, or SSO /
 38magic-link second-factor weakening sits nearby. Close as FP for expired magic-link retries from one IP/UA or IdP
 39pilot testing with a ticket.
 40
 41#### Possible investigation steps
 42
 43- Read `Esql.event_count`, `Esql.event_action_values`, `Esql.source_ip_values`, and
 44  `Esql.source_ip_distinct_count`.
 45- Low IP diversity → one device/egress (typos, expired links, focused guessing). High diversity → distributed
 46  automation or proxy rotation — higher priority.
 47- Inspect UA / actor-type values for automation. Search for successful `magic_link_login_succeeded` /
 48  `sso_login_succeeded` for the same email or IPs in the window.
 49- Correlate with **Anthropic SSO Disabled or Connection Removed** or magic-link second-factor disablement when
 50  org-scoped admin events are present.
 51
 52### False positive analysis
 53
 54- Expired magic-link click storms from one IP and named IdP cutover tests are common FPs.
 55
 56### Response and remediation
 57
 58- On suspected stuffing/takeover: invalidate sessions, reset credentials/MFA, and review successful logins from new
 59  IPs. If failures precede a successful unfamiliar login, expand to data access and admin changes.
 60"""
 61references = [
 62    "https://platform.claude.com/docs/en/api/compliance/activities/list",
 63]
 64risk_score = 47
 65rule_id = "25647990-cc37-430c-9a4e-2793bb5445f5"
 66severity = "medium"
 67tags = [
 68    "Domain: GenAI",
 69    "Domain: Identity",
 70    "Platform: Anthropic",
 71    "Data Source: Anthropic Audit Logs",
 72    "Use Case: Identity and Access Audit",
 73    "Use Case: Threat Detection",
 74    "Use Case: UEBA",
 75    "Resources: Investigation Guide",
 76    "Rule Type: ES|QL",
 77    "Tactic: Credential Access",
 78]
 79timestamp_override = "event.ingested"
 80type = "esql"
 81
 82query = '''
 83from logs-anthropic.audit-*
 84| where
 85    data_stream.dataset == "anthropic.audit" and
 86    mv_contains(event.category, "authentication") and
 87    event.outcome == "failure" and
 88    user.email is not null
 89| stats
 90    Esql.event_count = count(*),
 91    Esql.event_id_values = values(event.id),
 92    Esql.event_action_values = values(event.action),
 93    Esql.source_ip_values = values(source.ip),
 94    Esql.source_ip_distinct_count = count_distinct(source.ip),
 95    Esql.user_agent_original_values = values(user_agent.original),
 96    Esql.anthropic_audit_actor_type_values = values(anthropic.audit.actor.type),
 97    Esql.timestamp_first_seen = min(@timestamp),
 98    Esql.timestamp_last_seen = max(@timestamp)
 99  by user.email
100| where Esql.event_count >= 5
101| keep user.email, Esql.*
102'''
103
104
105[[rule.threat]]
106framework = "MITRE ATT&CK"
107[[rule.threat.technique]]
108id = "T1110"
109name = "Brute Force"
110reference = "https://attack.mitre.org/techniques/T1110/"
111
112
113[rule.threat.tactic]
114id = "TA0006"
115name = "Credential Access"
116reference = "https://attack.mitre.org/tactics/TA0006/"
117
118[rule.alert_suppression]
119group_by = ["user.email"]
120duration = {value = 1, unit = "h"}
121missing_fields_strategy = "suppress"
122
123[rule.investigation_fields]
124field_names = [
125    "user.email",
126    "Esql.event_count",
127    "Esql.event_id_values",
128    "Esql.event_action_values",
129    "Esql.source_ip_values",
130    "Esql.source_ip_distinct_count",
131    "Esql.user_agent_original_values",
132    "Esql.anthropic_audit_actor_type_values",
133    "Esql.timestamp_first_seen",
134    "Esql.timestamp_last_seen",
135]