Agent skill

Implementing Ticketing System For Incidents

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Implements an integrated incident ticketing system connecting SIEM alerts to ServiceNow, Jira, or TheHive for structured incident tracking, SLA management, escalation workflows, and compliance…

Apache-2.0Auto-check passedSecurity

Install Implementing Ticketing System For Incidents

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-ticketing-system-for-incidents -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-ticketing-system-for-incidents --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-ticketing-system-for-incidents .claude/skills/implementing-ticketing-system-for-incidents && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implementing-ticketing-system-for-incidents
GitHub stars
34k
Token cost
~4.1k tokens
SKILL.md length
406 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Implements an integrated incident ticketing system connecting SIEM alerts to ServiceNow, Jira, or TheHive for structured incident tracking, SLA management, escalation workflows, and compliance…

  • Works in 5 steps: Define Incident Classification Taxonomy → Automate Ticket Creation from SIEM → Configure TheHive for Security-Focused… → …
  • SOC teams need formalized incident lifecycle management with automated ticket creation
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Implementing Ticketing System For Incidents is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Implements an integrated incident ticketing system connecting SIEM alerts to ServiceNow, Jira, or TheHive for structured incident tracking, SLA management, escalation workflows, and compliance documentation. Use when SOC teams need formalized incident lifecycle management with automated ticket creation, assignment routing, and resolution tracking.

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Security operations. It works with ServiceNow and Jira. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • SOC teams need formalized incident lifecycle management with automated ticket creation
  • Assignment routing
  • Resolution tracking

Example prompts

  • “Use the implementing-ticketing-system-for-incidents skill to implement an integrated incident ticketing system connecting SIEM alerts to ServiceNow…”
  • “/implementing-ticketing-system-for-incidents”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Define Incident Classification Taxonomy
  2. Automate Ticket Creation from SIEM
  3. Configure TheHive for Security-Focused Ticketing
  4. Implement SLA Tracking and Escalation
  5. Build Reporting and Metrics

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implementing Ticketing System For Incidents loads about 4.1k tokens when it runs, and up to ~4.7k if it reads all its reference files. Until then it costs about 98 tokens; SKILL.md has 406 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 406 words, ~4,093 tokens.

Download SKILL.mdSave it as .claude/skills/implementing-ticketing-system-for-incidents/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
implementing-ticketing-system-for-incidents
description
Implements an integrated incident ticketing system connecting SIEM alerts to ServiceNow, Jira, or TheHive for structured incident tracking, SLA management, escalation workflows, and compliance documentation. Use when SOC teams need formalized incident lifecycle management with automated ticket creation, assignment routing, and resolution tracking.
domain
cybersecurity
subdomain
soc-operations
tags
soc, ticketing, servicenow, jira, thehive, incident-management, sla, workflow
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
DE.CM-01, DE.AE-02, RS.MA-01, DE.AE-06
mitre_attack
T1078, T1685.002, T1685.005, T1566

Implementing Ticketing System for Incidents

When to Use

Use this skill when:

  • SOC teams need to formalize incident tracking beyond SIEM notable event management
  • Compliance requirements mandate documented incident lifecycle with timestamps and audit trails
  • Multi-team coordination requires ticket-based workflows with assignment and escalation
  • SLA tracking needs automated measurement of response and resolution times
  • Post-incident reviews require structured data for trend analysis and reporting

Do not use for individual alert triage — ticketing is for confirmed incidents requiring multi-step investigation and remediation, not every SIEM alert.

Prerequisites

  • Ticketing platform: ServiceNow ITSM, Jira Service Management, or TheHive
  • SIEM integration capability (REST API, webhook, or SOAR connector)
  • Incident classification taxonomy (categories, severity levels, escalation paths)
  • On-call rotation schedule for analyst assignment
  • SLA definitions aligned to incident severity

Workflow

Step 1: Define Incident Classification Taxonomy

Establish standardized incident categories and severity:

yaml
incident_taxonomy:
  categories:
    - malware_infection
    - phishing_campaign
    - unauthorized_access
    - data_exfiltration
    - denial_of_service
    - ransomware
    - insider_threat
    - vulnerability_exploitation
    - account_compromise
    - policy_violation

  severity_levels:
    critical:
      definition: "Active data breach, ransomware, or business-critical system compromise"
      response_sla: 15 minutes
      resolution_sla: 4 hours
      escalation: immediate to Tier 3 + CISO notification
      examples: ["Active ransomware", "Domain admin compromise", "Customer data breach"]

    high:
      definition: "Confirmed compromise of business systems or multiple user accounts"
      response_sla: 30 minutes
      resolution_sla: 8 hours
      escalation: Tier 2 immediate, Tier 3 if unresolved in 2 hours
      examples: ["Malware with C2", "Lateral movement detected", "Phishing with credential theft"]

    medium:
      definition: "Confirmed security event requiring investigation and remediation"
      response_sla: 2 hours
      resolution_sla: 24 hours
      escalation: Tier 2 within 4 hours
      examples: ["Single phishing click", "Unauthorized software", "Policy violation"]

    low:
      definition: "Minor security event with limited impact"
      response_sla: 8 hours
      resolution_sla: 72 hours
      escalation: Tier 1 standard queue
      examples: ["Scan attempt", "Failed brute force (no compromise)", "Info disclosure"]
Step 2: Automate Ticket Creation from SIEM

ServiceNow Integration via REST API:

python
import requests
import json
from datetime import datetime

class IncidentTicketManager:
    def __init__(self, snow_url, snow_user, snow_password):
        self.snow_url = snow_url
        self.auth = (snow_user, snow_password)
        self.headers = {
            "Content-Type": "application/json",
            "Accept": "application/json"
        }

    def create_incident(self, alert_data):
        """Create ServiceNow incident from SIEM alert"""
        severity_map = {
            "critical": "1",
            "high": "2",
            "medium": "3",
            "low": "4"
        }

        payload = {
            "short_description": f"[SEC] {alert_data['rule_name']} — {alert_data['src']}",
            "description": self._build_description(alert_data),
            "category": "Security",
            "subcategory": alert_data.get("category", "Investigation"),
            "urgency": severity_map.get(alert_data["severity"], "3"),
            "impact": severity_map.get(alert_data["severity"], "3"),
            "assignment_group": self._get_assignment_group(alert_data["severity"]),
            "caller_id": "soc_automation",
            "u_siem_event_id": alert_data.get("notable_id", ""),
            "u_mitre_technique": alert_data.get("mitre_technique", ""),
            "u_affected_hosts": ", ".join(alert_data.get("affected_hosts", [])),
            "u_iocs": json.dumps(alert_data.get("iocs", {}))
        }

        response = requests.post(
            f"{self.snow_url}/api/now/table/incident",
            auth=self.auth,
            headers=self.headers,
            json=payload
        )
        result = response.json()["result"]
        return {
            "ticket_number": result["number"],
            "sys_id": result["sys_id"],
            "state": result["state"]
        }

    def _build_description(self, alert_data):
        return f"""
SECURITY INCIDENT — Auto-generated from SIEM
================================================
Alert Rule:       {alert_data['rule_name']}
SIEM Event ID:    {alert_data.get('notable_id', 'N/A')}
Detection Time:   {alert_data['detection_time']}
Severity:         {alert_data['severity'].upper()}
MITRE ATT&CK:    {alert_data.get('mitre_technique', 'N/A')}

Source:           {alert_data.get('src', 'N/A')}
Destination:      {alert_data.get('dest', 'N/A')}
User:             {alert_data.get('user', 'N/A')}

Initial Context:
{alert_data.get('description', 'See SIEM for details.')}

IOCs:
{json.dumps(alert_data.get('iocs', {}), indent=2)}
"""

    def _get_assignment_group(self, severity):
        if severity in ("critical", "high"):
            return "SOC Tier 2"
        return "SOC Tier 1"

    def update_incident(self, ticket_number, updates):
        """Update an existing incident"""
        # First get sys_id from ticket number
        response = requests.get(
            f"{self.snow_url}/api/now/table/incident",
            auth=self.auth,
            headers=self.headers,
            params={"sysparm_query": f"number={ticket_number}", "sysparm_limit": 1}
        )
        sys_id = response.json()["result"][0]["sys_id"]

        # Update
        response = requests.patch(
            f"{self.snow_url}/api/now/table/incident/{sys_id}",
            auth=self.auth,
            headers=self.headers,
            json=updates
        )
        return response.json()["result"]

    def add_work_note(self, ticket_number, note):
        """Add investigation note to incident"""
        self.update_incident(ticket_number, {"work_notes": note})

    def escalate_incident(self, ticket_number, reason):
        """Escalate to next tier"""
        self.update_incident(ticket_number, {
            "assignment_group": "SOC Tier 3",
            "urgency": "1",
            "work_notes": f"ESCALATED: {reason}"
        })

    def resolve_incident(self, ticket_number, resolution):
        """Resolve and close incident"""
        self.update_incident(ticket_number, {
            "state": "6",  # Resolved
            "close_code": "Resolved",
            "close_notes": resolution,
            "u_incident_disposition": resolution.split(":")[0] if ":" in resolution else "Resolved"
        })
Step 3: Configure TheHive for Security-Focused Ticketing

TheHive Case Creation (alternative to ServiceNow):

python
import requests

class TheHiveCaseManager:
    def __init__(self, thehive_url, api_key):
        self.url = thehive_url
        self.headers = {
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json"
        }

    def create_case(self, alert_data):
        """Create case in TheHive from SIEM alert"""
        case = {
            "title": f"[{alert_data['severity'].upper()}] {alert_data['rule_name']}",
            "description": self._build_markdown_description(alert_data),
            "severity": {"critical": 4, "high": 3, "medium": 2, "low": 1}.get(
                alert_data["severity"], 2
            ),
            "tlp": 2,  # TLP:AMBER
            "pap": 2,  # PAP:AMBER
            "tags": [
                alert_data.get("mitre_technique", ""),
                alert_data.get("category", ""),
                f"source:{alert_data.get('src', 'unknown')}"
            ],
            "tasks": self._generate_tasks(alert_data["severity"]),
            "customFields": {
                "siem-event-id": {"string": alert_data.get("notable_id", "")},
                "mitre-technique": {"string": alert_data.get("mitre_technique", "")},
                "detection-source": {"string": "Splunk ES"}
            }
        }

        response = requests.post(
            f"{self.url}/api/case",
            headers=self.headers,
            json=case
        )
        return response.json()

    def _generate_tasks(self, severity):
        """Generate investigation tasks based on severity"""
        tasks = [
            {"title": "Initial Triage", "group": "Phase 1", "description": "Review SIEM alert and validate findings"},
            {"title": "IOC Enrichment", "group": "Phase 1", "description": "Enrich all IOCs with VT, AbuseIPDB"},
            {"title": "Scope Assessment", "group": "Phase 2", "description": "Determine affected systems and users"},
        ]
        if severity in ("critical", "high"):
            tasks.extend([
                {"title": "Containment Actions", "group": "Phase 2", "description": "Isolate affected systems"},
                {"title": "Evidence Collection", "group": "Phase 3", "description": "Preserve forensic artifacts"},
                {"title": "Eradication", "group": "Phase 3", "description": "Remove threat from environment"},
                {"title": "Recovery", "group": "Phase 4", "description": "Restore systems to normal operations"},
                {"title": "Post-Incident Review", "group": "Phase 4", "description": "Document lessons learned"},
            ])
        else:
            tasks.append(
                {"title": "Resolution and Documentation", "group": "Phase 2", "description": "Document findings and close"}
            )
        return tasks

    def add_observable(self, case_id, ioc_type, ioc_value, description=""):
        """Add IOC observable to case"""
        observable = {
            "dataType": ioc_type,
            "data": ioc_value,
            "message": description,
            "tlp": 2,
            "ioc": True,
            "tags": ["auto-extracted"]
        }
        response = requests.post(
            f"{self.url}/api/case/{case_id}/artifact",
            headers=self.headers,
            json=observable
        )
        return response.json()
Step 4: Implement SLA Tracking and Escalation

Splunk SLA Monitoring Dashboard:

spl
--- Active incidents approaching SLA breach
index=servicenow sourcetype="snow:incident" category="Security" state IN ("New", "In Progress")
| eval sla_minutes = case(
    urgency="1", 15,
    urgency="2", 30,
    urgency="3", 120,
    urgency="4", 480
  )
| eval age_minutes = round((now() - strptime(opened_at, "%Y-%m-%d %H:%M:%S")) / 60, 0)
| eval sla_remaining = sla_minutes - age_minutes
| eval sla_status = case(
    sla_remaining < 0, "BREACHED",
    sla_remaining < sla_minutes * 0.25, "AT RISK",
    1=1, "ON TRACK"
  )
| where sla_status IN ("BREACHED", "AT RISK")
| sort sla_remaining
| table number, short_description, urgency, assignment_group, assigned_to,
        age_minutes, sla_minutes, sla_remaining, sla_status

Auto-Escalation Logic:

python
def check_sla_breaches(ticket_manager):
    """Check for SLA breaches and auto-escalate"""
    open_incidents = ticket_manager.get_open_incidents()

    for incident in open_incidents:
        age_minutes = (datetime.utcnow() - incident["opened_at"]).total_seconds() / 60
        sla_minutes = {"1": 15, "2": 30, "3": 120, "4": 480}[incident["urgency"]]

        if age_minutes > sla_minutes and incident["state"] == "New":
            ticket_manager.escalate_incident(
                incident["number"],
                f"SLA BREACH: {int(age_minutes)}min elapsed, {sla_minutes}min SLA. Auto-escalating."
            )
Step 5: Build Reporting and Metrics
spl
--- Monthly incident metrics
index=servicenow sourcetype="snow:incident" category="Security"
opened_at > "2024-03-01" opened_at < "2024-04-01"
| stats count AS total,
        avg(eval((resolved_at - opened_at) / 3600)) AS avg_resolution_hours,
        sum(eval(if(urgency="1", 1, 0))) AS critical,
        sum(eval(if(urgency="2", 1, 0))) AS high,
        sum(eval(if(urgency="3", 1, 0))) AS medium,
        sum(eval(if(urgency="4", 1, 0))) AS low
| eval avg_resolution = round(avg_resolution_hours, 1)

--- SLA compliance rate
index=servicenow sourcetype="snow:incident" category="Security" state="Resolved"
| eval sla_target = case(urgency="1", 4, urgency="2", 8, urgency="3", 24, urgency="4", 72)
| eval resolution_hours = (resolved_at - opened_at) / 3600
| eval sla_met = if(resolution_hours <= sla_target, 1, 0)
| stats sum(sla_met) AS met, count AS total
| eval compliance_pct = round(met / total * 100, 1)

Key Concepts

TermDefinition
Incident TicketFormal tracking record for a confirmed security incident with lifecycle management
SLAService Level Agreement defining maximum response and resolution times by severity
Escalation PathDefined routing from Tier 1 to Tier 2/3 based on severity, time elapsed, or analyst request
DispositionFinal classification of a closed incident (true positive, false positive, duplicate, policy violation)
MTTRMean Time to Resolve — average time from ticket creation to resolution across all incidents
Case ManagementStructured approach to managing complex incidents with tasks, observables, and audit trails
Show full SKILL.md (135 more words)Show less

Tools & Systems

  • ServiceNow ITSM: Enterprise IT service management platform with security incident module and SLA tracking
  • Jira Service Management: Atlassian's service management platform with customizable incident workflows
  • TheHive: Open-source security incident response platform with case management and Cortex integration
  • PagerDuty: On-call management and incident notification platform for SOC analyst alerting
  • Splunk ITSI: IT Service Intelligence module for SLA tracking and service health dashboards

Common Scenarios

  • SIEM-to-Ticket Automation: Auto-create ServiceNow ticket for every critical/high notable event in Splunk ES
  • Multi-Team Coordination: Route malware incidents to SOC for triage, IT for remediation, Legal for notification
  • Compliance Documentation: Generate incident reports from ticket data for PCI DSS, HIPAA audit evidence
  • On-Call Alerting: Page on-call analyst via PagerDuty when critical ticket created after hours
  • Post-Incident Review: Query closed tickets to identify recurring incident types and systemic gaps

Output Format

INCIDENT TICKET — INC0012567
━━━━━━━━━━━━━━━━━━━━━━━━━━━
Title:        [SEC] Cobalt Strike C2 Beacon Detected — WORKSTATION-042
Category:     Security > Malware Infection
Severity:     Critical (P1)
SLA:          Response: 15 min | Resolution: 4 hours

Timeline:
  14:23  Ticket created (auto from Splunk ES NE-2024-08921)
  14:25  Assigned to analyst_jdoe (Tier 2)
  14:28  Work note: "VT confirms Cobalt Strike beacon, hash a1b2c3..."
  14:35  Work note: "Host isolated via CrowdStrike, C2 domain blocked"
  15:00  Work note: "Enterprise IOC scan — 2 additional hosts found"
  15:30  Escalated to Tier 3 for forensic analysis
  16:00  Work note: "All affected hosts contained and cleaned"
  18:00  Resolved: "Malware eradicated, systems restored, monitoring for 72h"

Metrics:
  Time to Acknowledge: 2 minutes
  Time to Contain:     12 minutes
  Time to Resolve:     3 hours 37 minutes
  SLA Status:          MET (within 4-hour resolution target)

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/implementing-ticketing-system-for-incidents of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

Compare with similar skills

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Questions about Implementing Ticketing System For Incidents

What does Implementing Ticketing System For Incidents do?

Implements an integrated incident ticketing system connecting SIEM alerts to ServiceNow, Jira, or TheHive for structured incident tracking, SLA management, escalation workflows, and compliance…. Implementing Ticketing System For Incidents is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Implements an integrated incident ticketing system connecting SIEM alerts to ServiceNow, Jira, or TheHive for structured incident tracking, SLA management, escalation workflows, and compliance documentation.

When should I use Implementing Ticketing System For Incidents?

Implementing Ticketing System For Incidents fits situations like: SOC teams need formalized incident lifecycle management with automated ticket creation; assignment routing; resolution tracking.

How do I install Implementing Ticketing System For Incidents in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-ticketing-system-for-incidents -a claude-code`. Or copy the skill folder (skills/implementing-ticketing-system-for-incidents in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-ticketing-system-for-incidents in your project. Claude Code loads it when a task matches its description.

How do I install Implementing Ticketing System For Incidents in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-ticketing-system-for-incidents -a codex`. Or copy the skill folder (skills/implementing-ticketing-system-for-incidents in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-ticketing-system-for-incidents in your project. Codex loads it when a task matches its description.

Can I use Implementing Ticketing System For Incidents in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-ticketing-system-for-incidents -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-ticketing-system-for-incidents, .gemini/skills/implementing-ticketing-system-for-incidents, .github/skills/implementing-ticketing-system-for-incidents and .opencode/skills/implementing-ticketing-system-for-incidents in your project.

What does Implementing Ticketing System For Incidents need to run?

Going by SKILL.md and its folder, Implementing Ticketing System For Incidents needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Implementing Ticketing System For Incidents access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Implementing Ticketing System For Incidents safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Implementing Ticketing System For Incidents use?

Implementing Ticketing System For Incidents is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implementing Ticketing System For Incidents use?

About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 604 tokens, read only when the agent opens those files.

What are the alternatives to Implementing Ticketing System For Incidents?

Skills that share tags, products or a category with Implementing Ticketing System For Incidents: Ise Incident Response (automateyournetwork/netclaw, 676 stars), Fme Pipeline (harness/harness-skills, 115 stars), Security Alert Triage (elastic/agent-skills, 592 stars) and Kubernetes Network Security Audit (kubeshark/kubeshark, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implementing Ticketing System For Incidents?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.