smithery.ai

triage-suspicious-login

Triage suspicious login alerts like impossible travel, untrusted location, or multiple failures. Use when investigating authentication anomalies. Analyzes user history, source IP reputation, login patterns, and determines if escalation is needed.

First seen Mar 20, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,059 B
  • docs SUMMARY.md 277 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Suspicious Login Triage Skill

Guide initial triage of suspicious login alerts (impossible travel, untrusted location, multiple failed logins) for Tier 1 SOC Analysts.

Inputs

  • CASE_ID - SOAR case ID containing the alert(s)
  • ALERTGROUPIDENTIFIERS - Alert group identifiers from the case
  • (Optional) USER_ID - The user ID if known upfront
  • (Optional) SOURCE_IP - The source IP if known upfront

Workflow

Step 1: Get Case Context

secops-soar.get_case_full_details(case_id=CASE_ID)

Step 2: Extract Key Entities

secops-soar.list_events_by_alert(case_id=CASE_ID, alert_id=ALERT_ID)

Parse events to extract:

  • USER_ID - The user account
  • SOURCE_IP - The login source IP
  • HOSTNAME - The target/source hostname (if available)

Step 3: User Context (SIEM)

secops-mcp.lookup_entity(entity_value=USER_ID)

Record: Recent activity, first/last seen, related alerts.

Step 4: Source IP Enrichment

Use /enrich-ioc with IOC_TYPE="IP Address":

  • GTI reputation and geolocation
  • SIEM entity summary
  • IOC match status

Step 5: Hostname Context (if available)

secops-mcp.lookup_entity(entity_value=HOSTNAME)

Step 6: Recent Login Activity

Search for login patterns over the last 96 hours:

secops-mcp.search_security_events(
    text='metadata.event_type IN ("USER_LOGIN", "AUTH_ATTEMPT") AND principal.user.userid = "USER_ID"',
    hours_back=96
)

Analyze for:

  • Logins from unusual IPs
  • Successful logins after failures
  • Geographic anomalies (impossible travel)
  • Concurrent sessions from different locations

Step 7: Check Related Cases

Use /find-relevant-case with search terms: [USERID, SOURCEIP, HOSTNAME]

Step 8: (Optional) Identity Provider Check

If IDP tools available (e.g., Okta):

  • Account status
  • MFA enrollment
  • Recent legitimate logins
  • Password change history

Step 9: Synthesize & Document

Use /document-in-case with findings summary:

Suspicious Login Triage for USER_ID from SOURCE_IP:
- User SIEM Summary: [...]
- Source IP GTI: [reputation, geo]
- Login Pattern: [normal/anomalous]
- Related Cases: [...]
- Recommendation: [Close as FP | Escalate to Tier 2]

Required Outputs

After completing this skill, you MUST report these outputs:

Output Description
LOGIN_VERDICT Assessment: legitimate, suspicious, or malicious
ANOMALY_INDICATORS What made the login suspicious (impossible travel, new device, etc.)
RELATED_ACTIVITY Other suspicious activity from user or source IP
RISK_SCORE Numerical risk assessment (0-100) based on findings

Decision Matrix

Finding Recommendation
Known VPN/corporate IP + normal pattern Close as FP
User confirmed travel + MFA used Close as Benign TP
Malicious IP reputation Escalate
Impossible travel + no MFA Escalate urgently
Multiple failures then success from new IP Escalate
Pattern matches user's normal behavior Close as FP

Key Patterns to Detect

Impossible Travel:

  • Login from NYC, then London 30 mins later
  • Check if VPN or cloud service could explain

Credential Stuffing:

  • Many failures across multiple accounts from same IP
  • Success after many failures

Account Takeover:

  • Login from new device/location
  • Followed by password change or MFA modification

Lateral Movement:

  • Same user logging into many systems rapidly
  • Unusual service account activity