| name | performing-automated-malware-analysis-with-cape |
| description | Deploy and operate CAPEv2 sandbox for automated malware analysis with behavioral monitoring, payload extraction, configuration parsing, and anti-evasion capabilities. |
| domain | cybersecurity |
| subdomain | malware-analysis |
| tags | ["cape","sandbox","automated-analysis","malware-analysis","behavioral-analysis","payload-extraction","cuckoo"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
Performing Automated Malware Analysis with CAPE
Overview
CAPE (Config And Payload Extraction) is an open-source malware sandbox derived from Cuckoo that automates behavioral analysis, payload dumping, and configuration extraction. CAPEv2 features API hooking for behavioral instrumentation, captures files created/modified/deleted during execution, records network traffic in PCAP format, and includes 70+ custom configuration extractors (cape-parsers) for families like Emotet, TrickBot, Cobalt Strike, AsyncRAT, and Rhadamanthys. The signature system includes 1000+ behavioral signatures detecting evasion techniques, persistence, credential theft, and ransomware behavior. CAPE's debugger enables dynamic anti-evasion bypasses combining debugger actions within YARA signatures. Recommended deployment: Ubuntu LTS host with Windows 10 21H2 guest VM.
Prerequisites
- Ubuntu 22.04 LTS server (8+ CPU cores, 32GB+ RAM, 500GB+ SSD)
- KVM/QEMU virtualization support
- Windows 10 21H2 guest image
- Python 3.9+ with CAPEv2 dependencies
- Network configuration for isolated analysis network
Practical Steps
Step 1: Submit and Analyze Samples via API
"""CAPE sandbox API client for automated malware submission and analysis."""
import requests
import json
import time
import sys
from pathlib import Path
class CAPEClient:
def __init__(self, base_url="http://localhost:8000", api_token=None):
self.base_url = base_url.rstrip("/")
self.headers = {}
if api_token:
self.headers["Authorization"] = f"Token {api_token}"
def submit_file(self, filepath, options=None):
"""Submit a file for analysis."""
url = f"{self.base_url}/apiv2/tasks/create/file/"
files = {"file": open(filepath, "rb")}
data = options or {}
data.setdefault("timeout", 120)
data.setdefault("enforce_timeout", False)
resp = requests.post(url, files=files, data=data, headers=self.headers)
resp.raise_for_status()
result = resp.json()
task_id = result.get("data", {}).get("task_ids", [None])[0]
print(f"[+] Submitted -> Task ID: ")
task_id
():
url =
resp = requests.get(url, headers=.headers)
resp.json().get(, )
():
elapsed =
elapsed < max_wait:
status = .get_status(task_id)
status == :
()
time.sleep(poll_interval)
elapsed += poll_interval
()
():
url =
resp = requests.get(url, headers=.headers)
resp.json()
():
report = .get_report(task_id)
configs = report.get(, {}).get(, [])
configs
():
report = .get_report(task_id)
report.get(, [])
():
report = .get_report(task_id)
network = report.get(, {})
iocs = {
: [d.get() d network.get(, [])],
: [h.get() h network.get(, [])],
: [
h network.get(, [])],
}
iocs
():
task_id = .submit_file(filepath)
task_id:
.wait_for_completion(task_id):
report = {
: task_id,
: .get_config(task_id),
: .get_network_iocs(task_id),
: (.get_dropped_files(task_id)),
}
report
__name__ == :
(sys.argv) < :
()
sys.exit()
url = sys.argv[] (sys.argv) >
client = CAPEClient(url)
result = client.analyze_sample(sys.argv[])
result:
(json.dumps(result, indent=))
Validation Criteria
- Samples submitted and analyzed within configured timeout
- Behavioral signatures triggered for known malware families
- Malware configurations extracted by cape-parsers
- Network traffic captured and IOCs extracted
- Dropped files and payloads collected for further analysis
- Anti-evasion bypasses effective against sandbox-aware malware
References
