Skills spiderfoot

install
source · Clone the upstream repo
git clone https://github.com/TerminalSkills/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/TerminalSkills/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/spiderfoot" ~/.claude/skills/terminalskills-skills-spiderfoot && rm -rf "$T"
manifest: skills/spiderfoot/SKILL.md
safety · automated scan (medium risk)
This is a pattern-based risk scan, not a security review. Our crawler flagged:
  • pip install
  • shell exec via library
Always read a skill's source content before installing. Patterns alone don't mean the skill is malicious — but they warrant attention.
source content

SpiderFoot

Overview

SpiderFoot is an open-source intelligence automation platform with 200+ modules that query hundreds of public data sources simultaneously. It correlates data across passive DNS, Whois, social media, dark web, certificate transparency, breach databases, geolocation services, and more. SpiderFoot is unique in its ability to automatically chain discoveries — finding an email leads to social profiles, which leads to more domains, which leads to more IPs, building a comprehensive intelligence picture automatically.

Supports two modes: Web UI (browser-based, visual) and CLI (scriptable, automated).

Instructions

Step 1: Install SpiderFoot

# Clone and install
git clone https://github.com/smicallef/spiderfoot.git
cd spiderfoot
pip install -r requirements.txt

# Verify
python3 sf.py --help

Step 2: Launch the Web UI

# Start the web server (default: http://127.0.0.1:5001)
python3 sf.py -l 127.0.0.1:5001

# Bind to all interfaces (use with caution — no auth by default)
python3 sf.py -l 0.0.0.0:5001

# Access the UI at http://127.0.0.1:5001
# Create a new scan: Scans → New Scan → Enter target + select modules

Step 3: CLI usage — run scans without the UI

# Basic syntax
python3 sf.py -s TARGET -t TARGET_TYPE -m MODULE1,MODULE2

# Target types:
# INTERNET_NAME  — domain or hostname (example.com)
# IP_ADDRESS     — IPv4 address (1.2.3.4)
# EMAILADDR      — email address (user@example.com)
# USERNAME       — username
# NETBLOCK       — IP range (1.2.3.0/24)
# PHONE_NUMBER   — phone number
# HUMAN_NAME     — person name

# Scan a domain with all modules
python3 sf.py -s example.com -t INTERNET_NAME -m ALL -o json -f results.json

# Scan with specific modules only (faster, focused)
python3 sf.py -s example.com -t INTERNET_NAME \
  -m sfp_dnsresolve,sfp_dnsdumpster,sfp_shodan,sfp_certspotter,sfp_whois \
  -o json -f dns_results.json

# Scan an IP address
python3 sf.py -s 1.2.3.4 -t IP_ADDRESS \
  -m sfp_shodan,sfp_virustotal,sfp_ipinfo,sfp_abuseipdb \
  -o json -f ip_results.json

# Scan an email address
python3 sf.py -s user@example.com -t EMAILADDR \
  -m sfp_haveibeenpwned,sfp_hunter,sfp_emailrep \
  -o json -f email_results.json

# List all available modules
python3 sf.py -M

Step 4: Key module categories and selections

# Passive DNS and infrastructure
PASSIVE_DNS_MODULES="sfp_dnsresolve,sfp_dnsdumpster,sfp_certspotter,sfp_crt,sfp_passivetotal"

# Subdomain discovery
SUBDOMAIN_MODULES="sfp_dnsbrute,sfp_dnsdumpster,sfp_certspotter,sfp_virustotal,sfp_shodan"

# Social media and people
SOCIAL_MODULES="sfp_twitter,sfp_linkedin,sfp_instagram,sfp_github,sfp_keybase"

# Breach and leaked data
BREACH_MODULES="sfp_haveibeenpwned,sfp_dehashed,sfp_leakix,sfp_intelx"

# Dark web
DARKWEB_MODULES="sfp_torch,sfp_ahmia,sfp_onionsearchengine"

# Geolocation
GEO_MODULES="sfp_ipinfo,sfp_maxmind,sfp_abstractapi"

# Malware / threat intel
THREAT_MODULES="sfp_virustotal,sfp_threatcrowd,sfp_abuseipdb,sfp_maltiverse"

# Run a focused infrastructure scan
python3 sf.py -s example.com -t INTERNET_NAME \
  -m "$PASSIVE_DNS_MODULES,$SUBDOMAIN_MODULES" \
  -o json -f infra_scan.json

Step 5: Parse JSON output programmatically

import json
import subprocess
from collections import defaultdict

def run_spiderfoot_scan(target, target_type="INTERNET_NAME", modules=None, output_file=None):
    """Run a SpiderFoot CLI scan and return parsed results."""
    if output_file is None:
        output_file = f"sf_{target.replace('.', '_').replace('@', '_at_')}.json"

    if modules is None:
        modules = "sfp_dnsresolve,sfp_dnsdumpster,sfp_certspotter,sfp_whois,sfp_shodan"

    cmd = [
        "python3", "sf.py",
        "-s", target,
        "-t", target_type,
        "-m", modules,
        "-o", "json",
        "-f", output_file,
    ]

    print(f"Starting SpiderFoot scan: {target} ({target_type})")
    result = subprocess.run(cmd, capture_output=True, text=True, timeout=1800, cwd="./spiderfoot")
    if result.returncode != 0:
        print(f"Warning: {result.stderr[:500]}")

    return parse_sf_output(output_file)

def parse_sf_output(json_file):
    """Parse SpiderFoot JSON output and categorize findings."""
    try:
        with open(json_file) as f:
            data = json.load(f)
    except (FileNotFoundError, json.JSONDecodeError) as e:
        print(f"Could not parse output: {e}")
        return {}

    # SpiderFoot output is a list of [type, source, data, confidence, ...]
    findings = defaultdict(list)
    for row in data:
        if len(row) >= 3:
            event_type = row[0]
            source = row[1]
            value = row[2]
            findings[event_type].append({"value": value, "source": source})

    return dict(findings)

def summarize_findings(findings):
    """Print a summary of SpiderFoot scan results."""
    priority_types = [
        "EMAILADDR", "INTERNET_NAME", "IP_ADDRESS", "PHONE_NUMBER",
        "USERNAME", "LINKEDIN_URL", "TWITTER_URL", "GITHUB_URL",
        "LEAKEDDATA", "HACKED_EMAIL", "VULNERABILITY_CVE_CRITICAL",
        "VULNERABILITY_CVE_HIGH", "SSL_CERTIFICATE_MISMATCH",
    ]

    print("\n=== SpiderFoot Scan Summary ===")
    for event_type in priority_types:
        items = findings.get(event_type, [])
        if items:
            print(f"\n{event_type} ({len(items)}):")
            for item in items[:10]:
                print(f"  {item['value']}")
            if len(items) > 10:
                print(f"  ... and {len(items) - 10} more")

    print(f"\nAll event types found: {sorted(findings.keys())}")
    print(f"Total events: {sum(len(v) for v in findings.values())}")

# Example usage
findings = run_spiderfoot_scan(
    "example.com",
    target_type="INTERNET_NAME",
    modules="sfp_dnsresolve,sfp_certspotter,sfp_haveibeenpwned,sfp_shodan,sfp_whois"
)
summarize_findings(findings)

Step 6: Configure API keys in SpiderFoot

# Via Web UI: Settings → API Keys → enter keys for each module

# Via config file (~/.spiderfoot/spiderfoot.cfg or sf.cfg)
# Key settings to configure:
# sfp_shodan → shodan_api_key
# sfp_virustotal → virustotal_api_key
# sfp_haveibeenpwned → hibp_api_key
# sfp_hunter → hunter_api_key
# sfp_securitytrails → securitytrails_api_key
# sfp_censys → censys_api_id + censys_api_secret
# sfp_ipinfo → ipinfo_api_key

Step 7: Use the REST API for automation

import requests
import time

SPIDERFOOT_URL = "http://127.0.0.1:5001"

def create_scan_via_api(target, scan_name, modules="sfp_dnsresolve,sfp_certspotter"):
    """Create and start a SpiderFoot scan via the REST API."""
    resp = requests.post(f"{SPIDERFOOT_URL}/startscan", data={
        "scanname": scan_name,
        "scantarget": target,
        "scantype": "INTERNET_NAME",
        "modulelist": modules,
        "typelist": "",
    })
    if resp.status_code == 200:
        scan_id = resp.json().get("id")
        print(f"Scan started: {scan_id}")
        return scan_id
    raise Exception(f"Failed to create scan: {resp.text}")

def wait_for_scan(scan_id, poll_interval=30):
    """Poll until scan completes."""
    while True:
        resp = requests.get(f"{SPIDERFOOT_URL}/scanopts?id={scan_id}")
        status = resp.json().get("status", "")
        print(f"Status: {status}")
        if status in ("FINISHED", "FAILED", "ABORTED"):
            return status
        time.sleep(poll_interval)

def get_scan_results(scan_id):
    """Fetch all results for a completed scan."""
    resp = requests.get(f"{SPIDERFOOT_URL}/scaneventresults?id={scan_id}&eventType=ALL")
    return resp.json()

scan_id = create_scan_via_api("example.com", "Example Corp Scan")
status = wait_for_scan(scan_id)
if status == "FINISHED":
    results = get_scan_results(scan_id)
    print(f"Got {len(results)} findings")

Common SpiderFoot Modules Reference

ModulePurpose
sfp_dnsresolve
DNS resolution for discovered hosts
sfp_dnsdumpster
Passive DNS history lookup
sfp_certspotter
Certificate transparency log search
sfp_shodan
Query Shodan for host information
sfp_virustotal
VirusTotal domain/IP/file reputation
sfp_haveibeenpwned
Check emails in breach database
sfp_whois
WHOIS lookup for domains
sfp_hunter
Hunter.io email discovery
sfp_linkedin
LinkedIn profile search
sfp_twitter
Twitter/X profile lookup
sfp_github
GitHub user and code search
sfp_abuseipdb
IP abuse score lookup
sfp_threatcrowd
Threat intelligence correlation
sfp_leakix
LeakIX exposed service data

Guidelines

  • Module selection matters: Running all 200+ modules against a target takes hours and consumes significant API credits. Select focused module sets for specific investigative goals.
  • API keys: Many modules are no-ops without API keys. Configure at least Shodan, VirusTotal, and HIBP for meaningful results.
  • Correlation is the superpower: SpiderFoot's unique value is automatically chaining discoveries. Let it run fully on a focused set of modules rather than stopping it early.
  • Legal notice: SpiderFoot should only be used on targets you have authorization to investigate. Even passive OSINT may violate terms of service of some data providers.
  • Dark web modules: Modules like
    sfp_torch
    require Tor to be running locally (
    tor
    service on port 9050).