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SKILL.md
Analyzing Malware Family Relationships with Malpedia
Overview
Malpedia is a collaborative platform maintained by Fraunhofer FKIE that catalogs malware families with their aliases, YARA rules, threat actor associations, and reference reports. With over 2,600 malware families documented, it serves as the definitive resource for understanding malware lineages, tracking variant evolution, and linking malware to specific threat groups. This skill covers querying the Malpedia API, mapping malware family relationships, extracting YARA rules for detection, and building intelligence on malware ecosystems used by adversaries.
When to Use
When investigating security incidents that require analyzing malware family relationships with malpedia
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques
Prerequisites
Python 3.9+ with requests, yara-python, stix2 libraries
Understanding of malware classification and naming conventions
Familiarity with YARA rule syntax for detection
Access to malware samples for validation (optional)
Key Concepts
Malpedia Data Model
Malpedia organizes malware into Families (e.g., "win.cobalt_strike"), each containing: aliases (vendor-specific names like "Beacon", "CobaltStrike"), YARA rules (community and vendor-contributed), actor associations (threat groups using the family), reference reports (CTI reports documenting the family), and sample hashes (representative samples for each variant).
Malware Family Naming
Malpedia uses the format platform.family_name (e.g., win.emotet, elf.mirai, apk.flubot). Platforms include win (Windows), elf (Linux), apk (Android), osx (macOS), and py (Python). This standardized naming resolves the "many names" problem where different vendors assign different names to the same malware.
Family Relationships
Malware families have relationships including: parent-child (code reuse, forks), loader-payload (Emotet loads TrickBot loads Ryuk), shared authorship (same threat actor develops multiple tools), and infrastructure sharing (common C2 frameworks).
Workflow
Step 1: Query Malpedia API for Malware Families
import requests
import json
from collections import defaultdict
class MalpediaClient:
BASE_URL = "https://malpedia.caad.fkie.fraunhofer.de/api"
def __init__(self, api_key):
self.headers = {"Authorization": f"apitoken {api_key}"}
def get_family_list(self):
"""Get list of all malware families."""
resp = requests.get(f"{self.BASE_URL}/list/families",
headers=self.headers, timeout=30)
if resp.status_code == 200:
families = resp.json()
print(f"[+] Malpedia: {len(families)} malware families")
return families
return {}
def get_family_info(self, family_name):
"""Get detailed information about a malware family."""
resp = requests.get(f"{self.BASE_URL}/get/family/{family_name}",
headers=self.headers, timeout=30)
if resp.status_code == 200:
info = resp.json()
print(f"[+] Family: {family_name}")
print(f" Aliases: {info.get('alt_names', [])}")
print(f" Actors: {[a.get('value', '') for a in info.get('attribution', [])]}")
print(f" URLs: {len(info.get('urls', []))} references")
return info
print(f"[-] Family not found: {family_name}")
return None
def get_family_yara(self, family_name):
"""Get YARA rules for a malware family."""
resp = requests.get(f"{self.BASE_URL}/get/yara/{family_name}",
headers=self.headers, timeout=30)
if resp.status_code == 200:
rules = resp.json()
rule_count = sum(len(v) for v in rules.values()) if isinstance(rules, dict) else 0
print(f"[+] YARA rules for {family_name}: {rule_count} rules")
return rules
return {}
def get_actor_families(self, actor_name):
"""Get malware families associated with a threat actor."""
resp = requests.get(f"{self.BASE_URL}/get/actor/{actor_name}",
headers=self.headers, timeout=30)
if resp.status_code == 200:
data = resp.json()
families = data.get("families", {})
print(f"[+] {actor_name}: {len(families)} malware families")
return data
return {}
def search_families(self, keyword):
"""Search families by keyword."""
all_families = self.get_family_list()
matches = {
name: info for name, info in all_families.items()
if keyword.lower() in name.lower()
or keyword.lower() in str(info.get("alt_names", [])).lower()
}
print(f"[+] Search '{keyword}': {len(matches)} matches")
return matches
client = MalpediaClient("YOUR_MALPEDIA_API_KEY")
families = client.get_family_list()
emotet_info = client.get_family_info("win.emotet")
Step 2: Map Malware Family Relationships
class MalwareFamilyMapper:
def __init__(self, malpedia_client):
self.client = malpedia_client
self.relationship_graph = defaultdict(list)
def map_actor_ecosystem(self, actor_name):
"""Map the malware ecosystem used by a threat actor."""
actor_data = self.client.get_actor_families(actor_name)
families = actor_data.get("families", {})
ecosystem = {
"actor": actor_name,
"families": [],
"family_count": len(families),
}
for family_name in families:
info = self.client.get_family_info(family_name)
if info:
ecosystem["families"].append({
"name": family_name,
"aliases": info.get("alt_names", []),
"description": info.get("description", "")[:200],
"shared_actors": [
a.get("value", "")
for a in info.get("attribution", [])
],
"reference_count": len(info.get("urls", [])),
})
print(f"\n=== {actor_name} Malware Ecosystem ===")
for fam in ecosystem["families"]:
shared = [a for a in fam["shared_actors"] if a != actor_name]
print(f" {fam['name']}")
print(f" Aliases: {fam['aliases'][:5]}")
if shared:
print(f" Also used by: {shared}")
return ecosystem
def find_shared_tooling(self, actor_names):
"""Find malware families shared between threat actors."""
actor_families = {}
for actor in actor_names:
data = self.client.get_actor_families(actor)
actor_families[actor] = set(data.get("families", {}).keys())
# Find overlaps
shared = {}
for i, actor1 in enumerate(actor_names):
for actor2 in actor_names[i+1:]:
common = actor_families[actor1] & actor_families[actor2]
if common:
shared[f"{actor1} <-> {actor2}"] = sorted(common)
print(f"\n=== Shared Tooling Analysis ===")
for pair, families in shared.items():
print(f" {pair}: {len(families)} shared families")
for f in families[:5]:
print(f" - {f}")
return shared
def build_loader_payload_chain(self, family_name):
"""Build the loader-payload delivery chain for a family."""
info = self.client.get_family_info(family_name)
if not info:
return {}
chain = {
"family": family_name,
"description": info.get("description", ""),
"known_loaders": [],
"known_payloads": [],
}
# Common known delivery chains
known_chains = {
"win.emotet": {"loaders": ["email/macro"], "payloads": ["win.trickbot", "win.qakbot", "win.cobalt_strike"]},
"win.trickbot": {"loaders": ["win.emotet"], "payloads": ["win.ryuk", "win.conti", "win.cobalt_strike"]},
"win.qakbot": {"loaders": ["email/macro", "win.emotet"], "payloads": ["win.cobalt_strike", "win.blackbasta"]},
"win.cobalt_strike": {"loaders": ["win.emotet", "win.trickbot", "win.qakbot"], "payloads": ["ransomware"]},
}
if family_name in known_chains:
chain["known_loaders"] = known_chains[family_name]["loaders"]
chain["known_payloads"] = known_chains[family_name]["payloads"]
return chain
mapper = MalwareFamilyMapper(client)
ecosystem = mapper.map_actor_ecosystem("Wizard Spider")
shared = mapper.find_shared_tooling(["Wizard Spider", "FIN7", "Lazarus Group"])
chain = mapper.build_loader_payload_chain("win.emotet")
Step 3: Extract and Compile YARA Rules
def compile_yara_ruleset(client, family_names, output_file="malware_yara_rules.yar"):
"""Compile YARA rules for multiple malware families."""
all_rules = []
for family in family_names:
yara_data = client.get_family_yara(family)
if isinstance(yara_data, dict):
for source, rules in yara_data.items():
if isinstance(rules, list):
for rule in rules:
all_rules.append(f"// Source: {source} - Family: {family}\n{rule}")
elif isinstance(rules, str):
all_rules.append(f"// Source: {source} - Family: {family}\n{rules}")
with open(output_file, "w") as f:
f.write(f"// Malpedia YARA Rules - {len(all_rules)} rules\n")
f.write(f"// Families: {', '.join(family_names)}\n\n")
for rule in all_rules:
f.write(rule + "\n\n")
print(f"[+] Compiled {len(all_rules)} YARA rules to {output_file}")
return all_rules
compile_yara_ruleset(client, ["win.emotet", "win.trickbot", "win.cobalt_strike"])
Validation Criteria
Malpedia API queried successfully for malware families
Family information retrieved with aliases, actors, and references
Actor-family relationships mapped correctly
Shared tooling between actors identified
YARA rules extracted and compiled for detection
Loader-payload chains documented for threat intelligence
