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Enrich malware hashes using VirusTotal API for detection rates, YARA matches, and threat intelligence. Useful for SOC triage and IOC validation.
How this skill is triggered — by the user, by Claude, or both
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/cybersecurity-skills:performing-malware-hash-enrichment-with-virustotalThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
VirusTotal is the world's largest crowdsourced malware corpus, scanning files with 70+ antivirus engines and providing behavioral analysis, YARA rule matches, network indicators, and community intelligence. This skill covers using the VirusTotal API v3 to enrich file hashes (MD5, SHA-1, SHA-256) with detection verdicts, sandbox reports, related indicators, and contextual intelligence for SOC tr...
VirusTotal is the world's largest crowdsourced malware corpus, scanning files with 70+ antivirus engines and providing behavioral analysis, YARA rule matches, network indicators, and community intelligence. This skill covers using the VirusTotal API v3 to enrich file hashes (MD5, SHA-1, SHA-256) with detection verdicts, sandbox reports, related indicators, and contextual intelligence for SOC triage, incident response, and threat intelligence enrichment workflows.
vt-py (official VirusTotal Python client) or requestsThe API provides RESTful endpoints for file reports (/files/{hash}), URL scanning, domain reports, IP address intelligence, and advanced hunting with VirusTotal Intelligence (VTI). Each file report includes detection results from 70+ AV engines, behavioral analysis from sandboxes, YARA rule matches, sigma rule matches, file metadata (PE headers, imports, sections), network indicators (contacted IPs, domains, URLs), and community votes and comments.
The typical enrichment flow is: receive hash from alert/EDR -> query VT API -> parse detection ratio -> extract behavioral indicators -> correlate with existing intelligence -> make triage decision. The API returns a last_analysis_stats object with malicious, suspicious, undetected, and harmless counts.
VirusTotal enables pivoting from a single hash to related intelligence: similar files (ITW/in-the-wild samples), contacted domains and IPs (C2 infrastructure), dropped files, embedded URLs, YARA rule matches, and threat actor attribution through crowdsourced intelligence.
import vt
import json
import hashlib
from datetime import datetime
class VTEnricher:
def __init__(self, api_key):
self.client = vt.Client(api_key)
def enrich_hash(self, file_hash):
"""Enrich a file hash with VirusTotal intelligence."""
try:
file_obj = self.client.get_object(f"/files/{file_hash}")
stats = file_obj.last_analysis_stats
report = {
"hash": file_hash,
"sha256": file_obj.sha256,
"sha1": file_obj.sha1,
"md5": file_obj.md5,
"file_type": getattr(file_obj, "type_description", "Unknown"),
"file_size": getattr(file_obj, "size", 0),
"first_submission": str(getattr(file_obj, "first_submission_date", "")),
"last_analysis_date": str(getattr(file_obj, "last_analysis_date", "")),
"detection_stats": {
"malicious": stats.get("malicious", 0),
"suspicious": stats.get("suspicious", 0),
"undetected": stats.get("undetected", 0),
"harmless": stats.get("harmless", 0),
},
"detection_ratio": f"{stats.get('malicious', 0)}/{sum(stats.values())}",
"popular_threat_names": getattr(file_obj, "popular_threat_classification", {}),
"tags": getattr(file_obj, "tags", []),
"names": getattr(file_obj, "names", []),
}
total_engines = sum(stats.values())
mal_count = stats.get("malicious", 0)
report["threat_level"] = (
"critical" if mal_count > total_engines * 0.7
else "high" if mal_count > total_engines * 0.4
else "medium" if mal_count > total_engines * 0.1
else "low" if mal_count > 0
else "clean"
)
print(f"[+] {file_hash[:16]}... -> {report['detection_ratio']} "
f"({report['threat_level'].upper()})")
return report
except vt.error.APIError as e:
print(f"[-] VT API error for {file_hash}: {e}")
return None
def get_behavior_report(self, file_hash):
"""Get sandbox behavioral analysis for a file."""
try:
behaviors = self.client.get_object(f"/files/{file_hash}/behaviours")
behavior_data = {
"processes_created": [],
"files_written": [],
"registry_keys_set": [],
"dns_lookups": [],
"http_conversations": [],
"mutexes_created": [],
"commands_executed": [],
}
for sandbox in getattr(behaviors, "data", []):
attrs = sandbox.get("attributes", {})
behavior_data["processes_created"].extend(
attrs.get("processes_created", []))
behavior_data["files_written"].extend(
[f.get("path", "") for f in attrs.get("files_written", [])])
behavior_data["registry_keys_set"].extend(
[r.get("key", "") for r in attrs.get("registry_keys_set", [])])
behavior_data["dns_lookups"].extend(
[d.get("hostname", "") for d in attrs.get("dns_lookups", [])])
behavior_data["commands_executed"].extend(
attrs.get("command_executions", []))
return behavior_data
except Exception as e:
print(f"[-] Behavior report error: {e}")
return {}
def close(self):
self.client.close()
# Usage
enricher = VTEnricher("YOUR_VT_API_KEY")
report = enricher.enrich_hash("275a021bbfb6489e54d471899f7db9d1663fc695ec2fe2a2c4538aabf651fd0f")
print(json.dumps(report, indent=2, default=str))
enricher.close()
import time
import csv
def batch_enrich(api_key, hash_file, output_file, rate_limit=4):
"""Enrich a list of hashes from a file with rate limiting."""
enricher = VTEnricher(api_key)
results = []
with open(hash_file, "r") as f:
hashes = [line.strip() for line in f if line.strip()]
print(f"[*] Enriching {len(hashes)} hashes (rate: {rate_limit}/min)")
for i, file_hash in enumerate(hashes):
report = enricher.enrich_hash(file_hash)
if report:
results.append(report)
if (i + 1) % rate_limit == 0:
print(f" [{i+1}/{len(hashes)}] Rate limit pause (60s)...")
time.sleep(60)
# Export to CSV
with open(output_file, "w", newline="") as f:
if results:
writer = csv.DictWriter(f, fieldnames=results[0].keys())
writer.writeheader()
for r in results:
flat = {k: str(v) for k, v in r.items()}
writer.writerow(flat)
print(f"[+] Enrichment complete: {len(results)}/{len(hashes)} hashes")
print(f"[+] Results saved to {output_file}")
enricher.close()
return results
batch_enrich("YOUR_API_KEY", "hashes.txt", "enrichment_results.csv")
def extract_network_iocs(api_key, file_hash):
"""Extract network-based IOCs from VT for C2 identification."""
client = vt.Client(api_key)
network_iocs = {
"contacted_ips": [],
"contacted_domains": [],
"contacted_urls": [],
"embedded_urls": [],
}
try:
# Get contacted IPs
it = client.iterator(f"/files/{file_hash}/contacted_ips")
for ip_obj in it:
network_iocs["contacted_ips"].append({
"ip": ip_obj.id,
"country": getattr(ip_obj, "country", ""),
"asn": getattr(ip_obj, "asn", 0),
"as_owner": getattr(ip_obj, "as_owner", ""),
})
# Get contacted domains
it = client.iterator(f"/files/{file_hash}/contacted_domains")
for domain_obj in it:
network_iocs["contacted_domains"].append({
"domain": domain_obj.id,
"registrar": getattr(domain_obj, "registrar", ""),
"creation_date": str(getattr(domain_obj, "creation_date", "")),
})
# Get contacted URLs
it = client.iterator(f"/files/{file_hash}/contacted_urls")
for url_obj in it:
network_iocs["contacted_urls"].append({
"url": url_obj.url,
"last_http_response_code": getattr(url_obj, "last_http_response_content_length", 0),
})
except Exception as e:
print(f"[-] Error extracting network IOCs: {e}")
finally:
client.close()
print(f"[+] Network IOCs: {len(network_iocs['contacted_ips'])} IPs, "
f"{len(network_iocs['contacted_domains'])} domains, "
f"{len(network_iocs['contacted_urls'])} URLs")
return network_iocs
def get_yara_matches(api_key, file_hash):
"""Retrieve YARA rule matches for threat classification."""
client = vt.Client(api_key)
try:
file_obj = client.get_object(f"/files/{file_hash}")
crowdsourced_yara = getattr(file_obj, "crowdsourced_yara_results", [])
matches = []
for rule in crowdsourced_yara:
matches.append({
"rule_name": rule.get("rule_name", ""),
"ruleset_name": rule.get("ruleset_name", ""),
"author": rule.get("author", ""),
"description": rule.get("description", ""),
"source": rule.get("source", ""),
})
# Classify based on YARA matches
classifications = set()
for m in matches:
rule_lower = m["rule_name"].lower()
if any(k in rule_lower for k in ["apt", "nation", "state"]):
classifications.add("apt")
if any(k in rule_lower for k in ["ransom", "crypto"]):
classifications.add("ransomware")
if any(k in rule_lower for k in ["trojan", "rat", "backdoor"]):
classifications.add("trojan")
if any(k in rule_lower for k in ["loader", "dropper"]):
classifications.add("loader")
print(f"[+] YARA: {len(matches)} rules matched")
print(f"[+] Classifications: {classifications or {'unclassified'}}")
return {"matches": matches, "classifications": list(classifications)}
finally:
client.close()
def generate_enrichment_report(hash_report, behavior, network, yara_data):
"""Generate comprehensive enrichment report."""
report = {
"metadata": {
"generated": datetime.now().isoformat(),
"hash": hash_report.get("sha256", ""),
},
"verdict": {
"threat_level": hash_report.get("threat_level", "unknown"),
"detection_ratio": hash_report.get("detection_ratio", "0/0"),
"classifications": yara_data.get("classifications", []),
"threat_names": hash_report.get("popular_threat_names", {}),
},
"behavioral_indicators": {
"processes": behavior.get("processes_created", [])[:10],
"dns_queries": behavior.get("dns_lookups", [])[:10],
"commands": behavior.get("commands_executed", [])[:10],
},
"network_indicators": {
"c2_candidates": network.get("contacted_ips", [])[:10],
"domains": network.get("contacted_domains", [])[:10],
},
"yara_matches": yara_data.get("matches", [])[:10],
"recommendation": (
"BLOCK and investigate" if hash_report.get("threat_level") in ("critical", "high")
else "Monitor and analyze" if hash_report.get("threat_level") == "medium"
else "Low risk - continue monitoring"
),
}
with open(f"enrichment_{hash_report.get('sha256', 'unknown')[:16]}.json", "w") as f:
json.dump(report, f, indent=2, default=str)
return report
npx claudepluginhub mukul975/anthropic-cybersecurity-skills --plugin cybersecurity-skillsEnrich malware hashes using VirusTotal API for detection rates, YARA matches, and threat intelligence. Useful for SOC triage and IOC validation.
Enrich malware file hashes using VirusTotal API v3 to retrieve detection rates, behavioral analysis, YARA matches, and threat intelligence for SOC triage, incident response, and IOC validation.
Enrich malware file hashes using the VirusTotal API to retrieve detection rates, behavioral analysis, YARA matches, and contextual threat intelligence for incident triage and IOC validation.