implementing-soar-playbook-with-palo-alto-xsoar

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-soar-playbook-with-palo-alto-xsoar
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summary

Implement automated incident response playbooks in Cortex XSOAR to orchestrate security workflows across SOC tools and reduce manual response time.

skill.md
name
implementing-soar-playbook-with-palo-alto-xsoar
description
Implement automated incident response playbooks in Cortex XSOAR to orchestrate security workflows across SOC tools and reduce manual response time.
domain
cybersecurity
subdomain
soc-operations
tags
- xsoar - soar - palo-alto - playbook - automation - incident-response - orchestration - cortex
mitre_attack
- T1566 - T1204 - T1078
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- DE.CM-01 - DE.AE-02 - RS.MA-01 - DE.AE-06

Implementing SOAR Playbook with Palo Alto XSOAR

Overview

Cortex XSOAR (formerly Demisto) is Palo Alto Networks' Security Orchestration, Automation, and Response platform. Playbooks are the core automation engine in XSOAR, enabling SOC teams to automate repetitive incident response tasks. XSOAR provides 900+ prebuilt integration packs, 87 common playbooks, and a visual drag-and-drop editor for building custom workflows. Organizations using SOAR automation reduce mean time to respond (MTTR) by 80% on average.

When to Use

  • When deploying or configuring implementing soar playbook with palo alto xsoar capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Cortex XSOAR deployed (version 8.x or later, or XSOAR hosted)
  • Administrative access for playbook creation
  • Integration packs installed for relevant security tools
  • Incident types and layouts configured
  • API access to external tools (SIEM, EDR, TI platforms, ticketing)

Playbook Architecture

XSOAR Component Hierarchy

Incident Type (e.g., Phishing)
    |
    v
Incident Layout (UI display configuration)
    |
    v
Pre-Processing Rules (auto-classification, deduplication)
    |
    v
Playbook (automation logic)
    |-- Sub-Playbooks (modular reusable workflows)
    |-- Tasks (individual automation steps)
    |-- Conditional Tasks (decision branches)
    |-- Scripts (custom Python/JavaScript)
    |-- Integrations (external tool commands)
    |
    v
War Room (investigation timeline)
    |
    v
Closing Report

Playbook Task Types

Task TypePurposeExample
StandardExecute a command!ip ip=8.8.8.8
ConditionalBranch logicIf severity > high, escalate
ManualRequire analyst inputApprove containment action
Section HeaderOrganize workflow"Enrichment Phase"
Data CollectionGather external dataAsk user for additional details
TimerWait for condition/timeWait 5 minutes then check

Building a Phishing Response Playbook

Step 1: Define Incident Type

incident_type: Phishing
playbook: Phishing Investigation - Full
severity_mapping:
  - condition: email contains executable attachment
    severity: high
  - condition: email from external domain with link
    severity: medium
  - condition: email reported by user
    severity: low
layout: Phishing Layout
sla: 60 minutes

Step 2: Playbook YAML Structure

id: phishing-investigation-full
version: -1
name: Phishing Investigation - Full
description: Automated phishing email investigation with enrichment, analysis, and response
starttaskid: "0"
tasks:
  "0":
    id: "0"
    taskid: start
    type: start
    nexttasks:
      '#none#':
      - "1"
  "1":
    id: "1"
    taskid: extract-indicators
    type: regular
    task:
      name: Extract Indicators from Email
      script: ParseEmailFiles
    nexttasks:
      '#none#':
      - "2"
      - "3"
      - "4"
  "2":
    id: "2"
    taskid: enrich-urls
    type: playbook
    task:
      name: URL Enrichment
      playbookName: URL Enrichment - Generic v2
  "3":
    id: "3"
    taskid: enrich-files
    type: playbook
    task:
      name: File Enrichment
      playbookName: File Enrichment - Generic v2
  "4":
    id: "4"
    taskid: enrich-ips
    type: playbook
    task:
      name: IP Enrichment
      playbookName: IP Enrichment - Generic v2
  "5":
    id: "5"
    taskid: determine-verdict
    type: condition
    task:
      name: Is Email Malicious?
    conditions:
      - label: "yes"
        condition:
          - - operator: isEqualString
              left: DBotScore.Score
              right: "3"
      - label: "no"
    nexttasks:
      "yes":
      - "6"
      "no":
      - "9"
  "6":
    id: "6"
    taskid: block-sender
    type: regular
    task:
      name: Block Sender Domain
      script: '|||o365-mail-block-sender'
    scriptarguments:
      sender_address: ${incident.emailfrom}
  "7":
    id: "7"
    taskid: search-mailboxes
    type: regular
    task:
      name: Search and Delete from All Mailboxes
      script: '|||o365-mail-purge-compliance-search'
    scriptarguments:
      query: "from:${incident.emailfrom} subject:${incident.emailsubject}"
  "8":
    id: "8"
    taskid: notify-user
    type: regular
    task:
      name: Notify Reporting User
      script: '|||send-mail'
    scriptarguments:
      to: ${incident.reporter}
      subject: "Phishing Report Confirmed - Action Taken"
      body: "The email you reported has been confirmed as malicious and removed."
  "9":
    id: "9"
    taskid: close-incident
    type: regular
    task:
      name: Close Incident
      script: closeInvestigation

Step 3: Integration Commands

Email Analysis

!ParseEmailFiles entryid=${File.EntryID}
!rasterize url=${URL.Data} type=png

Threat Intelligence Enrichment

!url url=${URL.Data}
!file file=${File.SHA256}
!ip ip=${IP.Address}
!domain domain=${Domain.Name}

Containment Actions

!o365-mail-block-sender sender=${incident.emailfrom}
!o365-mail-purge-compliance-search query="from:${incident.emailfrom}"
!pan-os-block-ip ip=${IP.Address} log_forwarding="default"
!cortex-xdr-isolate-endpoint endpoint_id=${Endpoint.ID}

Ticketing Integration

!jira-create-issue summary="Phishing Incident - ${incident.id}" type="Incident" priority="High"
!servicenow-create-ticket short_description="Security Incident" urgency="2"

Common SOC Playbook Templates

1. Malware Investigation Playbook

Trigger: Malware alert from EDR
Steps:
  1. Extract file hash, process details, host info
  2. Enrich hash via VirusTotal, Hybrid Analysis
  3. Check if file is on allowlist
  4. If malicious:
     a. Isolate endpoint via EDR
     b. Block hash on all endpoints
     c. Search for hash across environment
     d. Create incident ticket
  5. If clean: Close as false positive

2. Account Compromise Playbook

Trigger: Impossible travel or suspicious login alert
Steps:
  1. Get user details from Active Directory
  2. Get login history for past 30 days
  3. Check for impossible travel (geo-distance vs time)
  4. Check for known VPN/proxy IP
  5. If compromised:
     a. Disable AD account
     b. Revoke all OAuth tokens
     c. Reset MFA
     d. Notify user's manager
     e. Search for lateral movement
  6. If false positive: Document and close

3. DDoS Mitigation Playbook

Trigger: Network anomaly alert
Steps:
  1. Verify traffic spike from network monitoring
  2. Identify source IPs and geolocation
  3. Check if source IPs are known botnets
  4. Implement rate limiting on WAF
  5. If sustained attack:
     a. Enable upstream DDoS protection
     b. Activate CDN scrubbing
     c. Notify ISP if needed
  6. Monitor and document

Custom XSOAR Scripts

Python Automation Script Example

# XSOAR Automation Script: CalculateRiskScore
def calculate_risk_score():
    """Calculate composite risk score for an incident."""
    severity = demisto.incident().get('severity', 0)
    indicator_count = len(demisto.get(demisto.context(), 'DBotScore', []))
    malicious_count = len([
        i for i in demisto.get(demisto.context(), 'DBotScore', [])
        if i.get('Score', 0) == 3
    ])

    base_score = severity * 20
    indicator_boost = min(indicator_count * 5, 25)
    malicious_boost = malicious_count * 15

    risk_score = min(100, base_score + indicator_boost + malicious_boost)

    return_results(CommandResults(
        outputs_prefix='RiskScore',
        outputs={'Score': risk_score, 'Level': 'Critical' if risk_score > 80 else 'High' if risk_score > 60 else 'Medium'},
        readable_output=f'Risk Score: {risk_score}/100'
    ))

calculate_risk_score()

Playbook Performance Metrics

MetricBefore SOARAfter SOARImprovement
Phishing MTTR45 min5 min89% reduction
Malware MTTR60 min8 min87% reduction
Account Compromise MTTR30 min4 min87% reduction
Alerts Handled per Shift50200+300% increase
False Positive Handling10 min30 sec95% reduction

References

how to use implementing-soar-playbook-with-palo-alto-xsoar

How to use implementing-soar-playbook-with-palo-alto-xsoar on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add implementing-soar-playbook-with-palo-alto-xsoar
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-soar-playbook-with-palo-alto-xsoar

The skills CLI fetches implementing-soar-playbook-with-palo-alto-xsoar from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-soar-playbook-with-palo-alto-xsoar

Reload or restart Cursor to activate implementing-soar-playbook-with-palo-alto-xsoar. Access the skill through slash commands (e.g., /implementing-soar-playbook-with-palo-alto-xsoar) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.572 reviews
  • Shikha Mishra· Dec 28, 2024

    We added implementing-soar-playbook-with-palo-alto-xsoar from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Valentina Robinson· Dec 28, 2024

    implementing-soar-playbook-with-palo-alto-xsoar fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ganesh Mohane· Dec 24, 2024

    Registry listing for implementing-soar-playbook-with-palo-alto-xsoar matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Hiroshi Bhatia· Dec 12, 2024

    implementing-soar-playbook-with-palo-alto-xsoar has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Zara Gupta· Dec 8, 2024

    Useful defaults in implementing-soar-playbook-with-palo-alto-xsoar — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aisha Ghosh· Dec 4, 2024

    We added implementing-soar-playbook-with-palo-alto-xsoar from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chinedu Khanna· Nov 27, 2024

    I recommend implementing-soar-playbook-with-palo-alto-xsoar for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Zara Thompson· Nov 23, 2024

    implementing-soar-playbook-with-palo-alto-xsoar fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Nov 19, 2024

    implementing-soar-playbook-with-palo-alto-xsoar fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Mateo Mensah· Nov 19, 2024

    We added implementing-soar-playbook-with-palo-alto-xsoar from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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