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Triage Suspicious Login

Community
dandye
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.

Overview

Publisherdandye
Repositoryai-runbooks
Skill nametriage-suspicious-login
Stars
126
Forks
34
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dandye on GitHub. Read the source before you install it.

Installation

Install the Triage Suspicious Login AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dandye/ai-runbooks.git /tmp/ai-runbooks
mkdir -p .claude/skills
cp -r /tmp/ai-runbooks/skills/triage-suspicious-login .claude/skills/triage-suspicious-login
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Triage Suspicious Login in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Triage Suspicious Login on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Triage Suspicious Login is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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)
  • ALERT_GROUP_IDENTIFIERS - 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: [USER_ID, SOURCE_IP, 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:

OutputDescription
LOGIN_VERDICTAssessment: legitimate, suspicious, or malicious
ANOMALY_INDICATORSWhat made the login suspicious (impossible travel, new device, etc.)
RELATED_ACTIVITYOther suspicious activity from user or source IP
RISK_SCORENumerical risk assessment (0-100) based on findings

Decision Matrix

FindingRecommendation
Known VPN/corporate IP + normal patternClose as FP
User confirmed travel + MFA usedClose as Benign TP
Malicious IP reputationEscalate
Impossible travel + no MFAEscalate urgently
Multiple failures then success from new IPEscalate
Pattern matches user's normal behaviorClose 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

Frequently asked questions

What does the Triage Suspicious Login AI skill do?

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.

Why use Triage Suspicious Login on TypingMind?

Because you install it once and use it with any model. Triage Suspicious Login is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Triage Suspicious Login in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dandye/ai-runbooks/tree/main/skills/triage-suspicious-login. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Triage Suspicious Login?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Triage Suspicious Login?

As many as you like. As long as a model supports skills, you can use Triage Suspicious Login with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Triage Suspicious Login AI skill free?

Yes. It is published on GitHub by dandye under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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