Build an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.
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name
building-ioc-defanging-and-sharing-pipeline
description
Build an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.
Vendored verbatim from an external Apache-2.0 security-skill library, pinned by commit. Exceeds the internal 300-line skill guideline (agent-code-constraints.md) -- kept as-is because this is vendored reference material (forensics/threat-intel procedure), not Yana AI-authored content, and trimming would damage technical accuracy.
Building IOC Defanging and Sharing Pipeline
Overview
IOC defanging modifies potentially malicious indicators (URLs, IP addresses, domains, email addresses) to prevent accidental clicks or execution while preserving readability for analysis and sharing. This skill covers building an automated pipeline that ingests raw IOCs from multiple sources, normalizes and deduplicates them, applies defanging for safe human consumption, converts them to STIX 2.1 format for machine consumption, and distributes through TAXII servers, MISP instances, and email reports.
When to Use
When deploying or configuring building ioc defanging and sharing pipeline 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 defang, ioc-fanger, stix2, requests, validators libraries
MISP instance or TAXII server for automated sharing
Understanding of IOC types: IPv4/IPv6, domains, URLs, email addresses, file hashes
Familiarity with STIX 2.1 Indicator patterns and TLP marking definitions
Access to threat intelligence feeds for IOC ingestion
Key Concepts
IOC Defanging Standards
Defanging replaces active protocol and domain components to prevent execution: http:// becomes hxxp://, https:// becomes hxxps://, dots in domains/IPs become [.], @ in emails becomes [@]. This is critical for sharing IOCs in reports, emails, Slack channels, and paste sites where auto-linking could trigger network connections to malicious infrastructure.
IOC Normalization
Raw IOCs from different sources come in inconsistent formats. Normalization involves converting to lowercase, removing trailing slashes and whitespace, extracting domains from URLs, resolving URL encoding, validating format correctness, and deduplicating across sources.
STIX 2.1 Indicator Patterns
STIX patterns express IOCs in a standardized format: [ipv4-addr:value = '203.0.113.1'], [domain-name:value = 'malicious.example.com'], [url:value = 'http://evil.com/payload'], [file:hashes.'SHA-256' = 'abc123...']. Each indicator includes valid_from, indicator_types, confidence, and optional TLP markings.
Workflow
Step 1: Build IOC Extraction and Normalization
import re
import hashlib
from urllib.parse import urlparse, unquote
from datetime import datetime
classIOCExtractor:
"""Extract and normalize IOCs from text."""
PATTERNS = {
"ipv4": r'\b(?:(?:25[0-5]|2[0-4]\d|1\d{2}|[1-9]?\d)\.){3}(?:25[0-5]|2[0-4]\d|1\d{2}|[1-9]?\d)\b',
"domain": r'\b(?:[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?\.)+[a-zA-Z]{2,}\b',
"url": r'https?://[^\s<>"{}|\\^`\[\]]+',
"email": r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b',
"md5": r'\b[a-fA-F0-9]{32}\b',
"sha1": r'\b[a-fA-F0-9]{40}\b',
"sha256": r'\b[a-fA-F0-9]{64}\b',
}
WHITELIST_DOMAINS = {
"google.com", "microsoft.com", "amazon.com", "github.com",
"cloudflare.com", "akamai.com", "example.com",
}
defextract_from_text(self, text):
"""Extract all IOC types from free text."""# Refang any already-defanged indicators first
text = self._refang(text)
iocs = {"ipv4": set(), "domain": set(), "url": set(),
"email": set(), "md5": set(), "sha1": set(), "sha256": set()}
for ioc_type, pattern inself.PATTERNS.items():
matches = re.findall(pattern, text)
formatchin matches:
normalized = self._normalize(match, ioc_type)
if normalized andnotself._is_whitelisted(normalized, ioc_type):
iocs[ioc_type].add(normalized)
# Remove domains that are part of URLs
url_domains = set()
for url in iocs["url"]:
parsed = urlparse(url)
url_domains.add(parsed.netloc)
iocs["domain"] -= url_domains
total = sum(len(v) for v in iocs.values())
print(f"[+] Extracted {total} unique IOCs from text")
return {k: sorted(v) for k, v in iocs.items()}
def_refang(self, text):
"""Convert defanged indicators back to active form."""
text = text.replace("hxxp://", "http://").replace("hxxps://", "https://")
text = text.replace("[.]", ".").replace("[@]", "@")
text = text.replace("[://]", "://").replace("(.)", ".")
return text
def_normalize(self, value, ioc_type):
"""Normalize an IOC value."""
value = value.strip().lower()
if ioc_type == "url":
value = unquote(value).rstrip("/")
elif ioc_type == "domain":
value = value.rstrip(".")
return value
def_is_whitelisted(self, value, ioc_type):
"""Check if IOC is in whitelist."""if ioc_type == "domain":
return value inself.WHITELIST_DOMAINS
if ioc_type == "url":
parsed = urlparse(value)
return parsed.netloc inself.WHITELIST_DOMAINS
returnFalse
extractor = IOCExtractor()
sample_text = """
Malware C2: hxxps://evil-domain[.]com/beacon
Drops payload from 192.168.1.100 and contacts 10[.]0[.]0[.]1
SHA256: 275a021bbfb6489e54d471899f7db9d1663fc695ec2fe2a2c4538aabf651fd0f
Phishing email from attacker[@]phishing-domain[.]com
"""
iocs = extractor.extract_from_text(sample_text)
Step 2: Defanging Engine
classIOCDefanger:
"""Defang IOCs for safe sharing in reports and communications."""defdefang_url(self, url):
return url.replace("http://", "hxxp://").replace("https://", "hxxps://").replace(".", "[.]")
defdefang_domain(self, domain):
return domain.replace(".", "[.]")
defdefang_ip(self, ip):
return ip.replace(".", "[.]")
defdefang_email(self, email):
return email.replace("@", "[@]").replace(".", "[.]")
defdefang_all(self, iocs):
"""Defang all IOCs in a dictionary."""
defanged = {}
for ioc_type, values in iocs.items():
if ioc_type == "url":
defanged[ioc_type] = [self.defang_url(v) for v in values]
elif ioc_type == "domain":
defanged[ioc_type] = [self.defang_domain(v) for v in values]
elif ioc_type == "ipv4":
defanged[ioc_type] = [self.defang_ip(v) for v in values]
elif ioc_type == "email":
defanged[ioc_type] = [self.defang_email(v) for v in values]
else:
defanged[ioc_type] = values # Hashes don't need defangingreturn defanged
defgenerate_sharing_report(self, iocs, defanged, report_name="IOC Report"):
"""Generate a human-readable defanged IOC report."""
report = f"# {report_name}\n"
report += f"Generated: {datetime.now().isoformat()}\n\n"for ioc_type in ["url", "domain", "ipv4", "email", "sha256", "sha1", "md5"]:
values = defanged.get(ioc_type, [])
if values:
report += f"## {ioc_type.upper()} ({len(values)})\n"for v in values:
report += f"- `{v}`\n"
report += "\n"return report
defanger = IOCDefanger()
defanged = defanger.defang_all(iocs)
report = defanger.generate_sharing_report(iocs, defanged, "Malware Campaign IOCs")
print(report)
Step 3: Convert to STIX 2.1 Format
from stix2 import Indicator, Bundle, TLP_WHITE, TLP_GREEN, TLP_AMBER
from datetime import datetime
classSTIXConverter:
"""Convert raw IOCs to STIX 2.1 Indicator objects."""
TLP_MAP = {"white": TLP_WHITE, "green": TLP_GREEN, "amber": TLP_AMBER}
defiocs_to_stix(self, iocs, tlp="green", confidence=75):
"""Convert IOC dictionary to STIX 2.1 bundle."""
stix_objects = []
marking = self.TLP_MAP.get(tlp, TLP_GREEN)
for ip in iocs.get("ipv4", []):
stix_objects.append(Indicator(
name=f"Malicious IP: {ip}",
pattern=f"[ipv4-addr:value = '{ip}']",
pattern_type="stix",
valid_from=datetime.now(),
indicator_types=["malicious-activity"],
confidence=confidence,
object_marking_refs=[marking],
))
for domain in iocs.get("domain", []):
stix_objects.append(Indicator(
name=f"Malicious Domain: {domain}",
pattern=f"[domain-name:value = '{domain}']",
pattern_type="stix",
valid_from=datetime.now(),
indicator_types=["malicious-activity"],
confidence=confidence,
object_marking_refs=[marking],
))
for url in iocs.get("url", []):
escaped = url.replace("'", "\\'")
stix_objects.append(Indicator(
name=f"Malicious URL: {url[:60]}",
pattern=f"[url:value = '{escaped}']",
pattern_type="stix",
valid_from=datetime.now(),
indicator_types=["malicious-activity"],
confidence=confidence,
object_marking_refs=[marking],
))
for sha256 in iocs.get("sha256", []):
stix_objects.append(Indicator(
name=f"Malicious File Hash: {sha256[:16]}...",
pattern=f"[file:hashes.'SHA-256' = '{sha256}']",
pattern_type="stix",
valid_from=datetime.now(),
indicator_types=["malicious-activity"],
confidence=confidence,
object_marking_refs=[marking],
))
bundle = Bundle(objects=stix_objects)
print(f"[+] Created STIX bundle with {len(stix_objects)} indicators")
return bundle
converter = STIXConverter()
stix_bundle = converter.iocs_to_stix(iocs, tlp="amber", confidence=80)
withopen("iocs_stix_bundle.json", "w") as f:
f.write(stix_bundle.serialize(pretty=True))
Step 4: Distribute Through MISP and TAXII
import requests
import json
classIOCDistributor:
"""Distribute IOCs through various channels."""defpush_to_misp(self, iocs, misp_url, misp_key, event_info):
"""Push IOCs to MISP as a new event."""
headers = {
"Authorization": misp_key,
"Content-Type": "application/json",
"Accept": "application/json",
}
event = {
"Event": {
"info": event_info,
"distribution": "1", # This community only"threat_level_id": "2", # Medium"analysis": "2", # Completed"Attribute": [],
}
}
type_mapping = {
"ipv4": "ip-dst",
"domain": "domain",
"url": "url",
"email": "email-src",
"md5": "md5",
"sha1": "sha1",
"sha256": "sha256",
}
for ioc_type, values in iocs.items():
misp_type = type_mapping.get(ioc_type)
if misp_type:
for value in values:
event["Event"]["Attribute"].append({
"type": misp_type,
"value": value,
"category": "Network activity"if ioc_type in ("ipv4", "domain", "url") else"Payload delivery",
"to_ids": True,
})
resp = requests.post(
f"{misp_url}/events",
headers=headers,
json=event,
verify=not os.environ.get("SKIP_TLS_VERIFY", "").lower() == "true", # Set SKIP_TLS_VERIFY=true for self-signed certs in lab environments
)
if resp.status_code == 200:
event_id = resp.json().get("Event", {}).get("id", "")
print(f"[+] MISP event created: {event_id}")
return event_id
else:
print(f"[-] MISP error: {resp.status_code} - {resp.text[:200]}")
returnNonedefpush_to_taxii(self, stix_bundle, taxii_url, collection_id, username, password):
"""Push STIX bundle to TAXII 2.1 collection."""from taxii2client.v21 import Collection
collection = Collection(
f"{taxii_url}/collections/{collection_id}/",
user=username, password=password,
)
response = collection.add_objects(stix_bundle.serialize())
print(f"[+] TAXII: Published bundle, status: {response.status}")
return response
distributor = IOCDistributor()
distributor.push_to_misp(
iocs,
misp_url="https://misp.organization.com",
misp_key="YOUR_MISP_API_KEY",
event_info="Malware Campaign IOCs - 2025",
)
Validation Criteria
IOCs extracted correctly from free text with refanging support
Defanging produces safe, non-clickable indicators
STIX 2.1 bundle contains valid indicator patterns
IOCs distributed to MISP and TAXII successfully
Deduplication prevents duplicate indicators
Whitelisting prevents false positives on known-good domains
