Anthropic Session Reuse Impossible Travel

Detects successful Anthropic audit activity for the same user email from source IP addresses whose query-time geo-locations (via IP_LOCATION) span at least two countries, are separated by at least 500 km, and imply travel faster than 800 km/h within a short (~15-minute) lookback. Unlike login-only impossible travel, this rule covers any successful user-actor activity and can surface session cookie replay or concurrent session reuse when no new authentication events appear.

Rule type: esql
Rule indices:

Rule Severity: high
Risk Score: 73
Runs every: 5m
Searches indices from: now-16m
Maximum alerts per execution: 100
References:

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: Credential Access
  • Tactic: Initial Access
  • Mitre Atlas: AML.T0012

Version: 1
Rule authors:

  • Elastic

Rule license: Elastic License v2

Successful user_actor activity for the same email spans distant countries too quickly for travel. Unlike login-only impossible travel, this covers any successful audit action — useful when cookie replay or concurrent sessions produce distant activity without a matching login.

A-B-A returns may not alert; sort raw Timeline events. No nearby magic_link_login_succeeded / sso_login_succeeded with distant successful non-login actions strengthens a session-reuse hypothesis.

Escalate when countries differ, UAs diverge (browser vs curl/python), login events are absent, or admin/export actions appear on the distant IP. Close as FP for documented dual-homed VPN/cloud egress with consistent corporate UAs.

  • Use Esql.country_count, distance/speed, and Esql.event_action_values to see whether the distant hop was privileged (exports, role changes) vs routine chat views.
  • Timeline-sort events; compare IP, geo, UA, and action. Concurrent browser + tooling on far-apart cloud egress often explains FP; identical session cookies across continents without login does not.
  • Check for nearby logins. Absence + privileged distant actions → treat as cookie replay until proven otherwise.
  • Pair with Anthropic Impossible Travel Login / auth-failure rules when takeover is suspected.
  • Split-tunnel / dual-homed clients (browser + API tooling) and VPN geo noise are the main FPs — require ASN/UA corroboration.
  • On suspected replay/compromise: revoke sessions, reset credentials/MFA, hunt concurrent sessions, and review compliance/export and role changes for the same user.email after the distant events.
from logs-anthropic.audit-*
| where
    data_stream.dataset == "anthropic.audit" and
    event.outcome == "success" and
    anthropic.audit.actor.type == "user_actor" 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.country_count = count_distinct(geo.country_name),
    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 and Esql.country_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 >= 500 and Esql.travel_kmh >= 800
| keep user.email, Esql.*

Framework: MITRE ATT&CK

Framework: MITRE ATT&CK