Agent skill

Building Threat Actor Profile From Osint

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools…

Apache-2.0Auto-check passedSecurity

Install Building Threat Actor Profile From Osint

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-threat-actor-profile-from-osint -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-threat-actor-profile-from-osint --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-threat-actor-profile-from-osint .claude/skills/building-threat-actor-profile-from-osint && 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-threat-actor-profile-from-osint
GitHub stars
34k
Token cost
~3.8k tokens
SKILL.md length
405 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools…

  • Works in 5 steps: Collect Intelligence from Multiple Sources → Build Structured Threat Actor Profile → Map TTPs to MITRE ATT&CK → …
  • Performing attribution
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; reaches otx.alienvault.com and virustotal.com

What it does

Building Threat Actor Profile From Osint is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools like Maltego and SpiderFoot, and producing structured dossiers of motivations, capabilities, infrastructure, and TTPs. Use when performing attribution or building an adversary dossier from open-source intelligence.

Its SKILL.md is about 3.8k 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 OSINT. 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

  • Performing attribution
  • Building an adversary dossier from open-source intelligence

Example prompts

  • “/building-threat-actor-profile-from-osint”

Requirements

  • Python 3
  • A credential in YOUR_VT_KEY
  • A credential in YOUR_OTX_KEY

Workflow steps

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

  1. Collect Intelligence from Multiple Sources
  2. Build Structured Threat Actor Profile
  3. Map TTPs to MITRE ATT&CK
  4. Correlate Infrastructure with SpiderFoot
  5. Generate Threat Actor Dossier

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

    Hosts in commands or code, which the agent is likely to contact:

    • otx.alienvault.com
    • virustotal.com
    • api.shodan.io

    Also links to:

    • github.com
    • huntress.com
    • crowdstrike.com
    • attack.mitre.org
    • shadowdragon.io
    • isaca.org

    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 Threat Actor Profile From Osint loads about 3.8k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 405 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~113
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.3k

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). 405 words, ~3,801 tokens.

Download SKILL.mdSave it as .claude/skills/building-threat-actor-profile-from-osint/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
building-threat-actor-profile-from-osint
description
Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools like Maltego and SpiderFoot, and producing structured dossiers of motivations, capabilities, infrastructure, and TTPs. Use when performing attribution or building an adversary dossier from open-source intelligence.
domain
cybersecurity
subdomain
threat-intelligence
tags
osint, threat-actor, threat-actor-profiling, maltego, spiderfoot, attribution, threat-intelligence, reconnaissance
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
ID.RA-01, ID.RA-05, DE.CM-01, DE.AE-02
mitre_attack
T1591, T1589, T1593, T1590

Building Threat Actor Profile from OSINT

Overview

Threat actor profiling using OSINT systematically gathers and analyzes publicly available information to build comprehensive profiles of adversary groups. This skill covers collecting intelligence from public sources (security vendor reports, paste sites, dark web forums, social media, code repositories), correlating indicators across platforms, mapping adversary infrastructure using tools like Maltego and SpiderFoot, and producing structured threat actor dossiers that inform defensive strategies and attribution assessments.

When to Use

  • When deploying or configuring building threat actor profile from osint 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

  • Python 3.9+ with shodan, requests, beautifulsoup4, maltego-trx, stix2 libraries
  • SpiderFoot (https://github.com/smicallef/spiderfoot) or SpiderFoot HX
  • Maltego CE or Maltego XL for link analysis
  • API keys: Shodan, VirusTotal, AlienVault OTX, PassiveTotal/RiskIQ
  • MITRE ATT&CK knowledge for TTP mapping
  • Understanding of STIX 2.1 Intrusion Set, Threat Actor, and Identity SDOs

Key Concepts

OSINT Sources for Threat Actor Profiling

Primary intelligence sources include vendor threat reports (Mandiant, CrowdStrike, Recorded Future, Talos), government advisories (CISA, NSA, FBI joint advisories), academic research papers, malware repositories (VirusTotal, MalwareBazaar, Malpedia), paste sites (Pastebin, GitHub Gists), code repositories, social media accounts, dark web forums, and certificate transparency logs.

Structured Analytical Techniques

Profiling uses the Diamond Model (adversary, infrastructure, capability, victim), Analysis of Competing Hypotheses (ACH) for attribution confidence, and MITRE ATT&CK mapping for TTP documentation. Link analysis tools like Maltego visualize relationships between indicators, infrastructure, and actors.

Show full SKILL.md (153 more words)Show less
Profile Components

A complete threat actor profile includes: aliases and naming conventions across vendors, suspected origin and sponsorship, motivation (espionage, financial, hacktivism, disruption), targeted sectors and geographies, known campaigns and operations, TTPs mapped to ATT&CK, toolset and malware families, infrastructure patterns, and historical timeline.

Workflow

Step 1: Collect Intelligence from Multiple Sources
python
import requests
import json
from datetime import datetime

class OSINTCollector:
    def __init__(self, vt_key=None, otx_key=None, shodan_key=None):
        self.vt_key = vt_key
        self.otx_key = otx_key
        self.shodan_key = shodan_key
        self.collected_data = {"sources": [], "indicators": [], "reports": []}

    def search_alienvault_otx(self, actor_name):
        """Search AlienVault OTX for threat actor pulses."""
        headers = {"X-OTX-API-KEY": self.otx_key}
        url = f"https://otx.alienvault.com/api/v1/search/pulses?q={actor_name}&limit=20"
        resp = requests.get(url, headers=headers)
        if resp.status_code == 200:
            data = resp.json()
            pulses = data.get("results", [])
            for pulse in pulses:
                self.collected_data["reports"].append({
                    "source": "AlienVault OTX",
                    "title": pulse.get("name", ""),
                    "created": pulse.get("created", ""),
                    "description": pulse.get("description", "")[:500],
                    "tags": pulse.get("tags", []),
                    "indicators_count": len(pulse.get("indicators", [])),
                    "pulse_id": pulse.get("id", ""),
                })
                for ioc in pulse.get("indicators", []):
                    self.collected_data["indicators"].append({
                        "type": ioc.get("type", ""),
                        "value": ioc.get("indicator", ""),
                        "source": "OTX",
                        "pulse": pulse.get("name", ""),
                    })
            print(f"[+] OTX: Found {len(pulses)} pulses for '{actor_name}'")
        return self.collected_data

    def search_virustotal_collections(self, actor_name):
        """Search VirusTotal for threat actor collections."""
        headers = {"x-apikey": self.vt_key}
        url = "https://www.virustotal.com/api/v3/intelligence/search"
        params = {"query": f"tag:{actor_name.lower().replace(' ', '-')}"}
        resp = requests.get(url, headers=headers, params=params)
        if resp.status_code == 200:
            results = resp.json().get("data", [])
            print(f"[+] VT: Found {len(results)} samples tagged '{actor_name}'")
            return results
        return []

    def query_shodan_infrastructure(self, indicators):
        """Query Shodan for infrastructure details on IPs."""
        results = []
        for ip in indicators:
            url = f"https://api.shodan.io/shodan/host/{ip}?key={self.shodan_key}"
            resp = requests.get(url)
            if resp.status_code == 200:
                data = resp.json()
                results.append({
                    "ip": ip,
                    "org": data.get("org", ""),
                    "asn": data.get("asn", ""),
                    "country": data.get("country_code", ""),
                    "ports": data.get("ports", []),
                    "hostnames": data.get("hostnames", []),
                    "os": data.get("os", ""),
                    "last_update": data.get("last_update", ""),
                })
        print(f"[+] Shodan: Enriched {len(results)} IPs")
        return results

collector = OSINTCollector(
    vt_key="YOUR_VT_KEY",
    otx_key="YOUR_OTX_KEY",
    shodan_key="YOUR_SHODAN_KEY",
)
data = collector.search_alienvault_otx("APT29")
Step 2: Build Structured Threat Actor Profile
python
from stix2 import ThreatActor, IntrusionSet, Identity, Relationship, Bundle
from datetime import datetime

# Create STIX 2.1 Threat Actor profile
identity = Identity(
    name="Cybersecurity Analyst",
    identity_class="individual",
)

threat_actor = ThreatActor(
    name="APT29",
    description="APT29 (also known as Cozy Bear, Midnight Blizzard, NOBELIUM, The Dukes) "
                "is a Russian state-sponsored threat group attributed to Russia's Foreign "
                "Intelligence Service (SVR). Active since at least 2008, the group conducts "
                "cyber espionage targeting government, diplomatic, think tank, healthcare, "
                "and energy organizations primarily in NATO countries.",
    aliases=["Cozy Bear", "Midnight Blizzard", "NOBELIUM", "The Dukes",
             "Dark Halo", "UNC2452", "YTTRIUM", "Blue Kitsune", "Iron Ritual"],
    roles=["agent"],
    sophistication="strategic",
    resource_level="government",
    primary_motivation="organizational-gain",
    secondary_motivations=["ideology"],
    threat_actor_types=["nation-state"],
    goals=["Intelligence collection on foreign governments",
           "Long-term persistent access to high-value targets",
           "Supply chain compromise for broad access"],
    created_by_ref=identity.id,
)

intrusion_set = IntrusionSet(
    name="APT29",
    description="Intrusion set tracked as APT29, attributed to Russian SVR.",
    aliases=["Cozy Bear", "Midnight Blizzard"],
    first_seen="2008-01-01T00:00:00Z",
    goals=["espionage"],
    resource_level="government",
    primary_motivation="organizational-gain",
)

relationship = Relationship(
    relationship_type="attributed-to",
    source_ref=intrusion_set.id,
    target_ref=threat_actor.id,
)

bundle = Bundle(objects=[identity, threat_actor, intrusion_set, relationship])
with open("apt29_profile.json", "w") as f:
    f.write(bundle.serialize(pretty=True))
print("[+] STIX profile saved: apt29_profile.json")
Step 3: Map TTPs to MITRE ATT&CK
python
from attackcti import attack_client

lift = attack_client()
apt29_techs = lift.get_techniques_used_by_group("G0016")

profile_ttps = {
    "initial_access": [],
    "execution": [],
    "persistence": [],
    "defense_evasion": [],
    "credential_access": [],
    "lateral_movement": [],
    "collection": [],
    "c2": [],
    "exfiltration": [],
}

tactic_mapping = {
    "initial-access": "initial_access",
    "execution": "execution",
    "persistence": "persistence",
    "defense-evasion": "defense_evasion",
    "credential-access": "credential_access",
    "lateral-movement": "lateral_movement",
    "collection": "collection",
    "command-and-control": "c2",
    "exfiltration": "exfiltration",
}

for tech in apt29_techs:
    tech_id = ""
    for ref in tech.get("external_references", []):
        if ref.get("source_name") == "mitre-attack":
            tech_id = ref.get("external_id", "")
            break
    for phase in tech.get("kill_chain_phases", []):
        tactic = phase.get("phase_name", "")
        key = tactic_mapping.get(tactic)
        if key:
            profile_ttps[key].append({
                "id": tech_id,
                "name": tech.get("name", ""),
                "description": tech.get("description", "")[:200],
            })

print("=== APT29 TTP Profile ===")
for tactic, techs in profile_ttps.items():
    if techs:
        print(f"\n{tactic.upper()} ({len(techs)} techniques):")
        for t in techs[:5]:
            print(f"  {t['id']}: {t['name']}")
Step 4: Correlate Infrastructure with SpiderFoot
python
import subprocess
import json

def run_spiderfoot_scan(target, scan_name="actor_recon"):
    """Run SpiderFoot scan against target domain or IP."""
    cmd = [
        "python3", "-m", "spiderfoot", "-s", target,
        "-m", "sfp_dns,sfp_whois,sfp_shodan,sfp_virustotal,sfp_certspotter",
        "-o", "json", "-q",
    ]
    result = subprocess.run(cmd, capture_output=True, text=True, timeout=300)
    if result.returncode == 0:
        findings = json.loads(result.stdout) if result.stdout else []
        print(f"[+] SpiderFoot: {len(findings)} findings for {target}")
        return findings
    return []

def correlate_infrastructure(indicators):
    """Find relationships between infrastructure indicators."""
    ip_to_domains = {}
    domain_to_ips = {}
    registrar_patterns = {}

    for indicator in indicators:
        ioc_type = indicator.get("type", "")
        value = indicator.get("value", "")

        if ioc_type == "IP_ADDRESS":
            if value not in ip_to_domains:
                ip_to_domains[value] = set()
        elif ioc_type == "INTERNET_NAME":
            if value not in domain_to_ips:
                domain_to_ips[value] = set()

    # Identify shared hosting, registration patterns
    shared_ips = {ip: domains for ip, domains in ip_to_domains.items() if len(domains) > 1}
    print(f"[+] Shared infrastructure IPs: {len(shared_ips)}")
    return {"shared_ips": shared_ips, "registrar_patterns": registrar_patterns}
Step 5: Generate Threat Actor Dossier
python
def generate_dossier(actor_name, profile_data, ttp_data, infrastructure_data):
    dossier = f"""# Threat Actor Dossier: {actor_name}
## Generated: {datetime.now().isoformat()}

## Executive Summary
{profile_data.get('description', '')}

## Attribution
- **Suspected Origin**: {profile_data.get('origin', 'Unknown')}
- **Sponsorship**: {profile_data.get('sponsorship', 'Unknown')}
- **Confidence Level**: {profile_data.get('confidence', 'Medium')}
- **First Observed**: {profile_data.get('first_seen', 'Unknown')}

## Aliases
{', '.join(profile_data.get('aliases', []))}

## Targeting
- **Sectors**: {', '.join(profile_data.get('sectors', []))}
- **Regions**: {', '.join(profile_data.get('regions', []))}
- **Motivation**: {profile_data.get('motivation', 'Unknown')}

## TTP Summary (MITRE ATT&CK)
"""
    for tactic, techs in ttp_data.items():
        if techs:
            dossier += f"\n### {tactic.replace('_', ' ').title()}\n"
            for t in techs:
                dossier += f"- **{t['id']}**: {t['name']}\n"

    dossier += f"""
## Infrastructure Patterns
- Known C2 servers: {len(infrastructure_data.get('c2_servers', []))}
- Domain patterns: {', '.join(infrastructure_data.get('domain_patterns', []))}
- Hosting preferences: {', '.join(infrastructure_data.get('hosting', []))}

## Recommendations
1. Monitor for known TTPs in EDR/SIEM
2. Block known infrastructure indicators
3. Hunt for behavioral patterns in network traffic
4. Implement detections for top technique gaps
"""
    with open(f"{actor_name.lower().replace(' ', '_')}_dossier.md", "w") as f:
        f.write(dossier)
    print(f"[+] Dossier saved for {actor_name}")

generate_dossier("APT29", {
    "description": "Russian state-sponsored espionage group attributed to SVR",
    "origin": "Russia", "sponsorship": "SVR (Foreign Intelligence Service)",
    "confidence": "High", "first_seen": "2008",
    "aliases": ["Cozy Bear", "Midnight Blizzard", "NOBELIUM", "The Dukes"],
    "sectors": ["Government", "Diplomatic", "Think Tank", "Healthcare", "Energy"],
    "regions": ["North America", "Europe", "NATO countries"],
    "motivation": "Espionage",
}, profile_ttps, {"c2_servers": [], "domain_patterns": [], "hosting": []})

Validation Criteria

  • Intelligence collected from at least 3 OSINT sources
  • STIX 2.1 Threat Actor and Intrusion Set objects created correctly
  • TTPs mapped to ATT&CK with technique IDs and procedure examples
  • Infrastructure indicators correlated across sources
  • Dossier includes attribution assessment with confidence levels
  • Profile is actionable for detection engineering and threat hunting

References

© 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-threat-actor-profile-from-osint 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 Threat Actor Profile From Osint 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.

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Run Claude Osintelementalsouls/Claude-OSINT2.8k—~1.2kAutomated safety check: PassMIT

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Categories

Questions about Building Threat Actor Profile From Osint

What does Building Threat Actor Profile From Osint do?

Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools…. Building Threat Actor Profile From Osint is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools like Maltego and SpiderFoot, and producing structured dossiers of motivations, capabilities, infrastructure, and TTPs.

When should I use Building Threat Actor Profile From Osint?

Building Threat Actor Profile From Osint fits situations like: performing attribution; building an adversary dossier from open-source intelligence.

How do I install Building Threat Actor Profile From Osint in Claude Code?

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

How do I install Building Threat Actor Profile From Osint in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-threat-actor-profile-from-osint -a codex`. Or copy the skill folder (skills/building-threat-actor-profile-from-osint in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/building-threat-actor-profile-from-osint in your project. Codex loads it when a task matches its description.

Can I use Building Threat Actor Profile From Osint 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-threat-actor-profile-from-osint -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-threat-actor-profile-from-osint, .gemini/skills/building-threat-actor-profile-from-osint, .github/skills/building-threat-actor-profile-from-osint and .opencode/skills/building-threat-actor-profile-from-osint in your project.

What does Building Threat Actor Profile From Osint need to run?

Going by SKILL.md and its folder, Building Threat Actor Profile From Osint needs Python for the scripts in its folder. Our summary lists: Python 3; A credential in YOUR_VT_KEY; A credential in YOUR_OTX_KEY.

Does Building Threat Actor Profile From Osint access the network?

SKILL.md names 9 domains. In commands or code: otx.alienvault.com, virustotal.com and api.shodan.io; the agent is likely to contact these when it follows the instructions. As links in the text: github.com, huntress.com, crowdstrike.com, attack.mitre.org, shadowdragon.io and isaca.org. This is read from the text; nothing was executed.

Is Building Threat Actor Profile From Osint 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 Threat Actor Profile From Osint use?

Building Threat Actor Profile From Osint 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 Threat Actor Profile From Osint use?

About 3.8k tokens (SKILL.md is roughly 15k 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 460 tokens, read only when the agent opens those files.

What are the alternatives to Building Threat Actor Profile From Osint?

Skills that share tags, products or a category with Building Threat Actor Profile From Osint: Metabigor OSINT Recon (j3ssie/metabigor, 1.9k stars), Ctf Osint (ljagiello/ctf-skills, 3.4k stars), ShadowBroker Intelligence Client (BigBodyCobain/Shadowbroker, 11k stars) and Awesome Osint Operator (shoyann/RZK-The-Hunter, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Building Threat Actor Profile From Osint?

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.