Agent skill

Building Cloud Siem With Sentinel

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Deploy Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps…

Apache-2.0Auto-check passedSecurity

Install Building Cloud Siem With Sentinel

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-cloud-siem-with-sentinel -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-cloud-siem-with-sentinel --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/building-cloud-siem-with-sentinel .claude/skills/building-cloud-siem-with-sentinel && 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
building-cloud-siem-with-sentinel
GitHub stars
34k
Token cost
~3.3k tokens
SKILL.md length
654 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Deploy Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps…

  • Works in 5 steps: Provision Sentinel Workspace and Data… → Write KQL Detection Rules → Build SOAR Playbooks with Logic Apps → …
  • Establishing a centralized SOC for multi-cloud environments
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; calls az and aws

What it does

Building Cloud Siem With Sentinel is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps response playbooks. Use when establishing a centralized SOC for multi-cloud environments, migrating from a legacy SIEM, or performing petabyte-scale threat hunting; not for AWS-only setups where Security Hub/GuardDuty suffice or for endpoint EDR needs.

Its SKILL.md is about 3.3k 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 Microsoft Sentinel, Amazon Web Services, Microsoft Azure and Google Cloud. 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

  • Establishing a centralized SOC for multi-cloud environments
  • Migrating from a legacy SIEM
  • Performing petabyte-scale threat hunting
  • Not for AWS-only setups where Security Hub/GuardDuty suffice

Example prompts

  • “/building-cloud-siem-with-sentinel”

Requirements

  • Python 3

Workflow steps

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

  1. Provision Sentinel Workspace and Data Connectors
  2. Write KQL Detection Rules
  3. Build SOAR Playbooks with Logic Apps
  4. Configure Sentinel Data Lake for Long-Term Hunting
  5. Integrate Threat Intelligence

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.

    Shell commands in SKILL.md call:

    • az
    • aws

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

  • Network

    No URLs in SKILL.md. Its commands use az and aws, which can reach the network depending on how they are called.

    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

Building Cloud Siem With Sentinel loads about 3.3k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 120 tokens; SKILL.md has 654 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

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). 654 words, ~3,283 tokens.

Download SKILL.mdSave it as .claude/skills/building-cloud-siem-with-sentinel/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
building-cloud-siem-with-sentinel
description
Deploy Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps response playbooks. Use when establishing a centralized SOC for multi-cloud environments, migrating from a legacy SIEM, or performing petabyte-scale threat hunting; not for AWS-only setups where Security Hub/GuardDuty suffice or for endpoint EDR needs.
domain
cybersecurity
subdomain
cloud-security
tags
microsoft-sentinel, cloud-siem, kql-queries, soar-automation, threat-detection
version
1.0.0
author
mahipal
license
Apache-2.0
nist_ai_rmf
MEASURE-2.7, MAP-5.1, MANAGE-2.4
atlas_techniques
AML.T0070, AML.T0066, AML.T0082
nist_csf
PR.IR-01, ID.AM-08, GV.SC-06, DE.CM-01
mitre_attack
T1078.004, T1548.005, T1485, T1530, T1021.007

Building Cloud SIEM with Sentinel

When to Use

  • When establishing a centralized security operations center for multi-cloud environments
  • When migrating from legacy SIEM platforms (Splunk, QRadar) to cloud-native architecture
  • When building automated incident response workflows for cloud-specific threats
  • When performing large-scale threat hunting across petabytes of security telemetry
  • When integrating threat intelligence feeds with cloud security log analysis

Do not use for AWS-only environments where Security Hub and GuardDuty suffice, for endpoint detection requiring EDR capabilities (use Defender for Endpoint), or for compliance posture monitoring (see building-cloud-security-posture-management).

Prerequisites

  • Azure subscription with Microsoft Sentinel enabled on a Log Analytics workspace
  • Data connector permissions for target log sources (AWS CloudTrail, Azure Activity, GCP)
  • Logic Apps or Azure Functions for automated response playbooks
  • KQL (Kusto Query Language) proficiency for writing detection rules and hunting queries

Workflow

Step 1: Provision Sentinel Workspace and Data Connectors

Create a Log Analytics workspace optimized for security data and enable data connectors for multi-cloud ingestion.

powershell
# Create Log Analytics workspace
az monitor log-analytics workspace create \
  --resource-group security-rg \
  --workspace-name sentinel-workspace \
  --location eastus \
  --retention-time 365 \
  --sku PerGB2018

# Enable Microsoft Sentinel on the workspace
az sentinel onboarding-state create \
  --resource-group security-rg \
  --workspace-name sentinel-workspace

# Enable AWS CloudTrail connector
az sentinel data-connector create \
  --resource-group security-rg \
  --workspace-name sentinel-workspace \
  --data-connector-id aws-cloudtrail \
  --kind AmazonWebServicesCloudTrail \
  --aws-cloud-trail-data-connector '{
    "awsRoleArn": "arn:aws:iam::123456789012:role/SentinelCloudTrailRole",
    "dataTypes": {"logs": {"state": "Enabled"}}
  }'

# Enable Azure AD sign-in and audit logs
az sentinel data-connector create \
  --resource-group security-rg \
  --workspace-name sentinel-workspace \
  --data-connector-id azure-ad \
  --kind AzureActiveDirectory \
  --azure-active-directory '{
    "dataTypes": {
      "alerts": {"state": "Enabled"},
      "signinLogs": {"state": "Enabled"},
      "auditLogs": {"state": "Enabled"}
    }
  }'
Step 2: Write KQL Detection Rules

Create analytics rules using Kusto Query Language to detect cloud-specific threats. Map each rule to MITRE ATT&CK techniques.

kql
// Detect impossible travel - sign-ins from geographically distant locations
let timeframe = 1h;
let distance_threshold = 500; // km
SigninLogs
| where TimeGenerated > ago(timeframe)
| where ResultType == 0 // Successful sign-ins only
| project TimeGenerated, UserPrincipalName, IPAddress, Location,
          Latitude = toreal(LocationDetails.geoCoordinates.latitude),
          Longitude = toreal(LocationDetails.geoCoordinates.longitude)
| sort by UserPrincipalName asc, TimeGenerated asc
| extend PrevLatitude = prev(Latitude, 1), PrevLongitude = prev(Longitude, 1),
         PrevTime = prev(TimeGenerated, 1), PrevUser = prev(UserPrincipalName, 1)
| where UserPrincipalName == PrevUser
| extend TimeDiff = datetime_diff('minute', TimeGenerated, PrevTime)
| where TimeDiff < 60
| extend Distance = geo_distance_2points(Longitude, Latitude, PrevLongitude, PrevLatitude) / 1000
| where Distance > distance_threshold
| project TimeGenerated, UserPrincipalName, IPAddress, Location, Distance, TimeDiff
kql
// Detect AWS IAM credential abuse from CloudTrail
AWSCloudTrail
| where TimeGenerated > ago(24h)
| where EventName in ("ConsoleLogin", "AssumeRole", "GetSessionToken")
| where ErrorCode == ""
| summarize LoginCount = count(), DistinctIPs = dcount(SourceIpAddress),
            IPList = make_set(SourceIpAddress, 10)
            by UserIdentityArn, bin(TimeGenerated, 1h)
| where DistinctIPs > 3
| project TimeGenerated, UserIdentityArn, LoginCount, DistinctIPs, IPList
kql
// Detect mass S3 object deletion (potential ransomware)
AWSCloudTrail
| where TimeGenerated > ago(1h)
| where EventName == "DeleteObject" or EventName == "DeleteObjects"
| summarize DeleteCount = count(), BucketsAffected = dcount(RequestParameters_bucketName)
            by UserIdentityArn, bin(TimeGenerated, 10m)
| where DeleteCount > 100
| project TimeGenerated, UserIdentityArn, DeleteCount, BucketsAffected
Step 3: Build SOAR Playbooks with Logic Apps

Create automated response playbooks that execute when analytics rules trigger incidents. Common actions include blocking users, isolating resources, and enriching alerts with threat intelligence.

json
{
  "definition": {
    "triggers": {
      "Microsoft_Sentinel_incident": {
        "type": "ApiConnectionWebhook",
        "inputs": {
          "body": {"incidentArmId": "subscriptions/@{triggerBody()?['workspaceInfo']?['SubscriptionId']}/resourceGroups/@{triggerBody()?['workspaceInfo']?['ResourceGroupName']}/providers/Microsoft.OperationalInsights/workspaces/@{triggerBody()?['workspaceInfo']?['WorkspaceName']}/providers/Microsoft.SecurityInsights/Incidents/@{triggerBody()?['object']?['properties']?['incidentNumber']}"},
          "host": {"connection": {"name": "@parameters('$connections')['microsoftsentinel']['connectionId']"}}
        }
      }
    },
    "actions": {
      "Get_incident_entities": {
        "type": "ApiConnection",
        "inputs": {"method": "post", "path": "/Incidents/entities"}
      },
      "For_each_account_entity": {
        "type": "Foreach",
        "foreach": "@body('Get_incident_entities')?['Accounts']",
        "actions": {
          "Disable_Azure_AD_user": {
            "type": "ApiConnection",
            "inputs": {
              "method": "PATCH",
              "path": "/v1.0/users/@{items('For_each_account_entity')?['AadUserId']}",
              "body": {"accountEnabled": false}
            }
          },
          "Add_comment_to_incident": {
            "type": "ApiConnection",
            "inputs": {
              "body": {"message": "User @{items('For_each_account_entity')?['Name']} disabled by automated playbook"}
            }
          }
        }
      }
    }
  }
}
Step 4: Configure Sentinel Data Lake for Long-Term Hunting

Enable the Sentinel data lake for petabyte-scale log retention and advanced threat hunting using both KQL and SQL endpoints.

kql
// Threat hunting query: detect lateral movement across AWS accounts
let suspicious_roles = AWSCloudTrail
| where TimeGenerated > ago(7d)
| where EventName == "AssumeRole"
| extend AssumedRoleArn = tostring(parse_json(RequestParameters).roleArn)
| where AssumedRoleArn contains "cross-account" or AssumedRoleArn contains "admin"
| summarize AssumeCount = count(), UniqueSourceAccounts = dcount(RecipientAccountId)
            by UserIdentityArn, AssumedRoleArn
| where AssumeCount > 10 and UniqueSourceAccounts > 2;
suspicious_roles
| join kind=inner (
    AWSCloudTrail
    | where TimeGenerated > ago(7d)
    | where EventName in ("RunInstances", "CreateFunction", "PutBucketPolicy")
) on UserIdentityArn
| project TimeGenerated, UserIdentityArn, AssumedRoleArn, EventName, SourceIpAddress
Step 5: Integrate Threat Intelligence

Connect threat intelligence providers and create indicator-based matching rules to detect communication with known malicious infrastructure.

powershell
# Enable Microsoft Threat Intelligence connector
az sentinel data-connector create \
  --resource-group security-rg \
  --workspace-name sentinel-workspace \
  --data-connector-id microsoft-ti \
  --kind MicrosoftThreatIntelligence \
  --microsoft-threat-intelligence '{
    "dataTypes": {"microsoftEmergingThreatFeed": {"lookbackPeriod": "2025-01-01T00:00:00Z", "state": "Enabled"}}
  }'
kql
// Match network indicators against cloud flow logs
let TI_IPs = ThreatIntelligenceIndicator
| where TimeGenerated > ago(30d)
| where isnotempty(NetworkIP)
| distinct NetworkIP;
AzureNetworkAnalytics_CL
| where TimeGenerated > ago(24h)
| where DestIP_s in (TI_IPs)
| project TimeGenerated, SrcIP_s, DestIP_s, DestPort_d, FlowType_s

Key Concepts

TermDefinition
KQLKusto Query Language, the primary query language for Microsoft Sentinel used to search, analyze, and visualize security data
Analytics RuleDetection logic in Sentinel that evaluates log data on a schedule and creates incidents when conditions match
SOAR PlaybookAutomated workflow triggered by incidents that performs response actions such as blocking accounts, enriching alerts, or notifying teams
Data ConnectorIntegration module that ingests security logs from cloud services, identity providers, and third-party tools into Sentinel
Sentinel Data LakePetabyte-scale storage layer providing long-term log retention with KQL and SQL query interfaces for advanced hunting
WorkbookInteractive dashboard in Sentinel displaying visualizations of security data, trends, and operational metrics
WatchlistReference data tables in Sentinel used to enrich alerts with context such as VIP user lists or approved IP ranges
Fusion DetectionMachine learning-powered correlation engine that automatically detects multi-stage attacks across data sources
Show full SKILL.md (244 more words)Show less

Tools & Systems

  • Microsoft Sentinel: Cloud-native SIEM/SOAR platform built on Azure Log Analytics with AI-powered threat detection
  • Azure Logic Apps: Low-code automation platform for building SOAR playbooks triggered by Sentinel incidents
  • Microsoft Threat Intelligence: Integrated threat feeds providing IP, domain, and URL indicators for matching against security logs
  • Azure Data Explorer: High-performance analytics engine underlying Sentinel KQL queries for large-scale data exploration
  • MITRE ATT&CK Navigator: Framework for mapping Sentinel detection rules to adversary tactics and techniques

Common Scenarios

Scenario: Detecting Cross-Cloud Credential Theft Campaign

Context: An attacker compromises an Azure AD account through phishing, then uses the account to access AWS resources via federated identity. Sentinel needs to correlate the Azure sign-in anomaly with unusual AWS API activity.

Approach:

  1. Create an analytics rule detecting Azure AD impossible travel or anomalous sign-in risk
  2. Write a KQL query correlating the compromised Azure AD identity with AWS CloudTrail AssumeRoleWithSAML events
  3. Build a Fusion detection rule that links Azure AD risk events with subsequent AWS privilege escalation activity
  4. Deploy a SOAR playbook that automatically disables the Azure AD account and revokes AWS STS sessions
  5. Create a workbook showing the timeline from initial compromise through lateral movement to AWS
  6. Run a hunting query across the data lake to check for similar patterns affecting other accounts

Pitfalls: Not correlating identity across cloud providers misses the full attack chain. Setting analytics rule frequency too low (e.g., 24 hours) allows attackers hours of undetected access.

Output Format

Microsoft Sentinel SOC Operations Report
==========================================
Workspace: sentinel-workspace
Data Sources: 14 connectors active
Report Period: 2025-02-01 to 2025-02-23

DATA INGESTION:
  Azure AD Sign-in Logs:     2.3 TB (23 days)
  AWS CloudTrail:            1.8 TB (23 days)
  Azure Activity:            0.9 TB (23 days)
  Defender for Cloud Alerts: 45 GB (23 days)
  Total Ingestion:           5.1 TB

DETECTION SUMMARY:
  Active Analytics Rules: 87
  Incidents Created: 234
    Critical: 8 | High: 34 | Medium: 89 | Low: 103
  Mean Time to Detect (MTTD): 4.2 minutes
  Mean Time to Respond (MTTR): 18 minutes

TOP INCIDENT TYPES:
  Impossible Travel Detected:          42 incidents
  AWS Unauthorized API Call Pattern:   28 incidents
  Mass File Deletion in S3:            3 incidents
  Suspicious Azure AD App Registration: 12 incidents

AUTOMATION:
  Playbooks Executed: 156
  Accounts Auto-Disabled: 23
  Incidents Auto-Enriched: 198
  False Positive Rate: 12%

© 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/building-cloud-siem-with-sentinel 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

Building Cloud Siem With Sentinel next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Building Cloud Siem With Sentinel compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Building Cloud Siem With Sentinel this skillmukul975/Anthropic-Cybersecurity-Skills34k—~3.3kAutomated safety check: PassApache-2.0
Siem Loggingancoleman/ai-design-components525—~3.4kAutomated safety check: PassMIT
Cloud Defensetransilienceai/communitytools563—~476Automated safety check: PassMIT
Investigating GCP Incidentstrilwu/secskills157—~2.2kAutomated safety check: PassMIT
Defender For Cloud Hardeningvinayaklatthe/microsoft-security-skills175—~1.9kAutomated safety check: PassMIT
Cloud Auditbriiirussell/cybersecurity-skills413—~1.3kAutomated safety check: NotesMIT

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Categories

Questions about Building Cloud Siem With Sentinel

What does Building Cloud Siem With Sentinel do?

Deploy Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps…. Building Cloud Siem With Sentinel is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps response playbooks.

When should I use Building Cloud Siem With Sentinel?

Building Cloud Siem With Sentinel fits situations like: establishing a centralized SOC for multi-cloud environments; migrating from a legacy SIEM; performing petabyte-scale threat hunting; not for AWS-only setups where Security Hub/GuardDuty suffice.

How do I install Building Cloud Siem With Sentinel in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-cloud-siem-with-sentinel -a claude-code`. Or copy the skill folder (skills/building-cloud-siem-with-sentinel in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/building-cloud-siem-with-sentinel in your project. Claude Code loads it when a task matches its description.

How do I install Building Cloud Siem With Sentinel in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-cloud-siem-with-sentinel -a codex`. Or copy the skill folder (skills/building-cloud-siem-with-sentinel in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/building-cloud-siem-with-sentinel in your project. Codex loads it when a task matches its description.

Can I use Building Cloud Siem With Sentinel 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 building-cloud-siem-with-sentinel -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/building-cloud-siem-with-sentinel, .gemini/skills/building-cloud-siem-with-sentinel, .github/skills/building-cloud-siem-with-sentinel and .opencode/skills/building-cloud-siem-with-sentinel in your project.

What does Building Cloud Siem With Sentinel need to run?

Going by SKILL.md and its folder, Building Cloud Siem With Sentinel needs Python for the scripts in its folder and the command-line tools its instructions call (az and aws). Our summary lists: Python 3.

Does Building Cloud Siem With Sentinel 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 Building Cloud Siem With Sentinel 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 Building Cloud Siem With Sentinel use?

Building Cloud Siem With Sentinel 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 Building Cloud Siem With Sentinel use?

About 3.3k tokens (SKILL.md is roughly 13k 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 476 tokens, read only when the agent opens those files.

What are the alternatives to Building Cloud Siem With Sentinel?

Skills that share tags, products or a category with Building Cloud Siem With Sentinel: Siem Logging (ancoleman/ai-design-components, 525 stars), Cloud Defense (transilienceai/communitytools, 563 stars), Investigating GCP Incidents (trilwu/secskills, 157 stars) and Defender For Cloud Hardening (vinayaklatthe/microsoft-security-skills, 175 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Building Cloud Siem With Sentinel?

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.