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Anthropic Impossible Travel Login
Detects successful Anthropic magic link or SSO sign-ins for the same user email from source IP addresses whose query-time geo-locations (via IP_LOCATION) are separated by at least 1,000 km, with implied travel faster than 800 km/h, within a 24-hour window. That pattern can indicate account sharing, VPN or proxy egress mismatches, or an adversary authenticating from a geography far from the legitimate user's baseline.
Detection Query
from logs-anthropic.audit-*
| where
data_stream.dataset == "anthropic.audit" and
mv_contains(event.category, "authentication") and
event.outcome == "success" and
event.action in ("magic_link_login_succeeded", "sso_login_succeeded") and
user.email is not null and
source.ip is not null
| IP_LOCATION geo = source.ip with { "properties": ["country_name", "city_name", "location"] }
| eval
Esql.source_geo_lat = st_y(geo.location),
Esql.source_geo_lon = st_x(geo.location)
| where Esql.source_geo_lat is not null and Esql.source_geo_lon is not null
| stats
Esql.first_lat = first(Esql.source_geo_lat, @timestamp),
Esql.first_lon = first(Esql.source_geo_lon, @timestamp),
Esql.last_lat = last(Esql.source_geo_lat, @timestamp),
Esql.last_lon = last(Esql.source_geo_lon, @timestamp),
Esql.event_count = count(*),
Esql.event_id_values = values(event.id),
Esql.event_action_values = values(event.action),
Esql.source_ip_values = values(source.ip),
Esql.source_geo_country_name_values = values(geo.country_name),
Esql.source_geo_city_name_values = values(geo.city_name),
Esql.user_agent_original_values = values(user_agent.original),
Esql.anthropic_audit_actor_type_values = values(anthropic.audit.actor.type),
Esql.timestamp_first_seen = min(@timestamp),
Esql.timestamp_last_seen = max(@timestamp)
by user.email
| where Esql.event_count >= 2
| eval
Esql.p1 = to_geopoint(concat("POINT(", to_string(Esql.first_lon), " ", to_string(Esql.first_lat), ")")),
Esql.p2 = to_geopoint(concat("POINT(", to_string(Esql.last_lon), " ", to_string(Esql.last_lat), ")"))
| eval
Esql.distance_km = round(st_distance(Esql.p1, Esql.p2) / 1000.0, 0),
Esql.window_minutes = date_diff("minute", Esql.timestamp_first_seen, Esql.timestamp_last_seen),
Esql.travel_kmh = case(Esql.window_minutes > 0, round(Esql.distance_km * 60.0 / Esql.window_minutes, 0), null)
| where Esql.distance_km >= 1000 and Esql.travel_kmh >= 800
| keep user.email, Esql.*
Author
Elastic
Created
2026/09/15
Data Sources
Anthropic Audit Logs
Tags
Domain: GenAIDomain: IdentityPlatform: AnthropicData Source: Anthropic Audit LogsUse Case: Identity and Access AuditUse Case: Threat DetectionResources: Investigation GuideRule Type: ES|QLTactic: Initial AccessMitre Atlas: AML.T0012
Raw Content
[metadata]
creation_date = "2026/09/15"
integration = ["anthropic"]
maturity = "production"
min_stack_comments = "ES|QL IP_LOCATION requires 9.5.0+. FIRST/LAST aggregations and st_distance require 9.4.0+."
min_stack_version = "9.5.0"
updated_date = "2026/09/25"
[rule]
author = ["Elastic"]
description = """
Detects successful Anthropic magic link or SSO sign-ins for the same user email from source IP addresses whose
query-time geo-locations (via IP_LOCATION) are separated by at least 1,000 km, with implied travel faster than 800 km/h,
within a 24-hour window. That pattern can indicate account sharing, VPN or proxy egress mismatches, or an adversary
authenticating from a geography far from the legitimate user's baseline.
"""
false_positives = [
"""
Users on VPN or proxy egress that geo-resolves through a region distant from the user's physical location. Mobile
clients on cellular networks that peer through regional hubs may geo-resolve differently than the user's location.
""",
]
from = "now-24h"
interval = "1h"
language = "esql"
license = "Elastic License v2"
name = "Anthropic Impossible Travel Login"
note = """## Triage and analysis
### Investigating Anthropic Impossible Travel Login
Two successful magic-link or SSO sign-ins for the same `user.email` appear too far apart, too quickly, to be physical
travel. That can be account sharing, VPN/proxy geo mismatch, or adversary authentication from a distant egress.
Note: an A-B-A return to the first location may not alert (first/last coords can be close) — always sort raw Timeline
auth events before concluding.
Unauthorized / escalate when the distant IP/UA is unfamiliar, the user denies travel/VPN use, or failures / SSO
weakening sit nearby. Close as FP when the user confirms known travel, split home/office VPN, or geo DB noise with
matching corporate ASN/UA.
#### Possible investigation steps
- Read `Esql.distance_km`, `Esql.travel_kmh`, `Esql.window_minutes`, and the geo/IP value lists — high speed with a
country change is stronger than a same-region VPN hop.
- Timeline-sort successful logins; compare each `source.ip`, geo, and `user_agent.original`. A browser→curl/python
shift on the distant hop is higher priority than two similar corporate browsers.
- Pair with **Anthropic Multiple Authentication Failures** or SSO / magic-link second-factor changes when takeover is
plausible.
- Ask the user only after geo/UA triage: expected travel or VPN egress vs unrecognized location.
### False positive analysis
- VPN pools and anycast/satellite geo misplacements commonly inflate implied speed — corroborate ASN and UA first.
### Response and remediation
- On suspected compromise: revoke sessions, reset credentials/MFA, and review admin or data-access activity after the
distant sign-in.
"""
references = ["https://platform.claude.com/docs/en/api/compliance/activities/list"]
risk_score = 73
rule_id = "e89e4744-039e-4290-9835-63ea42fe531e"
severity = "high"
tags = [
"Domain: GenAI",
"Domain: Identity",
"Platform: Anthropic",
"Data Source: Anthropic Audit Logs",
"Use Case: Identity and Access Audit",
"Use Case: Threat Detection",
"Resources: Investigation Guide",
"Rule Type: ES|QL",
"Tactic: Initial Access",
"Mitre Atlas: AML.T0012",
]
timestamp_override = "event.ingested"
type = "esql"
query = '''
from logs-anthropic.audit-*
| where
data_stream.dataset == "anthropic.audit" and
mv_contains(event.category, "authentication") and
event.outcome == "success" and
event.action in ("magic_link_login_succeeded", "sso_login_succeeded") and
user.email is not null and
source.ip is not null
| IP_LOCATION geo = source.ip with { "properties": ["country_name", "city_name", "location"] }
| eval
Esql.source_geo_lat = st_y(geo.location),
Esql.source_geo_lon = st_x(geo.location)
| where Esql.source_geo_lat is not null and Esql.source_geo_lon is not null
| stats
Esql.first_lat = first(Esql.source_geo_lat, @timestamp),
Esql.first_lon = first(Esql.source_geo_lon, @timestamp),
Esql.last_lat = last(Esql.source_geo_lat, @timestamp),
Esql.last_lon = last(Esql.source_geo_lon, @timestamp),
Esql.event_count = count(*),
Esql.event_id_values = values(event.id),
Esql.event_action_values = values(event.action),
Esql.source_ip_values = values(source.ip),
Esql.source_geo_country_name_values = values(geo.country_name),
Esql.source_geo_city_name_values = values(geo.city_name),
Esql.user_agent_original_values = values(user_agent.original),
Esql.anthropic_audit_actor_type_values = values(anthropic.audit.actor.type),
Esql.timestamp_first_seen = min(@timestamp),
Esql.timestamp_last_seen = max(@timestamp)
by user.email
| where Esql.event_count >= 2
| eval
Esql.p1 = to_geopoint(concat("POINT(", to_string(Esql.first_lon), " ", to_string(Esql.first_lat), ")")),
Esql.p2 = to_geopoint(concat("POINT(", to_string(Esql.last_lon), " ", to_string(Esql.last_lat), ")"))
| eval
Esql.distance_km = round(st_distance(Esql.p1, Esql.p2) / 1000.0, 0),
Esql.window_minutes = date_diff("minute", Esql.timestamp_first_seen, Esql.timestamp_last_seen),
Esql.travel_kmh = case(Esql.window_minutes > 0, round(Esql.distance_km * 60.0 / Esql.window_minutes, 0), null)
| where Esql.distance_km >= 1000 and Esql.travel_kmh >= 800
| keep user.email, Esql.*
'''
[[rule.threat]]
framework = "MITRE ATT&CK"
[[rule.threat.technique]]
id = "T1078"
name = "Valid Accounts"
reference = "https://attack.mitre.org/techniques/T1078/"
[[rule.threat.technique.subtechnique]]
id = "T1078.004"
name = "Cloud Accounts"
reference = "https://attack.mitre.org/techniques/T1078/004/"
[rule.threat.tactic]
id = "TA0001"
name = "Initial Access"
reference = "https://attack.mitre.org/tactics/TA0001/"
[[rule.threat_mappings]]
framework = "MITRE ATLAS"
version = "2026.08"
[[rule.threat_mappings.threat]]
framework = "MITRE ATLAS"
[[rule.threat_mappings.threat.technique]]
id = "AML.T0012"
name = "Valid Accounts"
reference = "https://atlas.mitre.org/techniques/AML.T0012/"
[rule.threat_mappings.threat.tactic]
id = "AML.TA0004"
name = "Initial Access"
reference = "https://atlas.mitre.org/tactics/AML.TA0004/"
[rule.alert_suppression]
group_by = ["user.email"]
missing_fields_strategy = "suppress"
[rule.investigation_fields]
field_names = [
"user.email",
"Esql.distance_km",
"Esql.travel_kmh",
"Esql.window_minutes",
"Esql.event_count",
"Esql.event_id_values",
"Esql.event_action_values",
"Esql.source_ip_values",
"Esql.source_geo_country_name_values",
"Esql.source_geo_city_name_values",
"Esql.first_lat",
"Esql.first_lon",
"Esql.last_lat",
"Esql.last_lon",
"Esql.user_agent_original_values",
"Esql.anthropic_audit_actor_type_values",
"Esql.timestamp_first_seen",
"Esql.timestamp_last_seen",
]
[rule.alert_suppression.duration]
unit = "h"
value = 24