---
name: performing-automated-malware-analysis-with-cape
description: Deploy and operate the CAPEv2 malware sandbox (a Cuckoo derivative) to run samples in a
  monitored Windows guest VM, capturing behavioral signatures, dropped files, PCAP network traffic,
  and family-specific configuration extraction (e.g. Emotet, TrickBot, Cobalt Strike) via
  cape-parsers. Use when a suspicious file or payload needs automated dynamic analysis, anti-evasion
  debugger tricks, or config/payload extraction.
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
nist_csf:
- DE.AE-02
- RS.AN-03
- ID.RA-01
- DE.CM-01
mitre_attack:
- T1027
- T1055
- T1140
- T1497
- T1070
---
# 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.


## When to Use

- When conducting security assessments that involve performing automated malware analysis with cape
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing

## 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

## Workflow

### Step 1: Submit and Analyze Samples via API

```python
#!/usr/bin/env python3
"""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 {filepath} -> Task ID: {task_id}")
        return task_id

    def get_status(self, task_id):
        """Check task analysis status."""
        url = f"{self.base_url}/apiv2/tasks/status/{task_id}/"
        resp = requests.get(url, headers=self.headers)
        return resp.json().get("data", "unknown")

    def wait_for_completion(self, task_id, poll_interval=15, max_wait=600):
        """Wait for analysis to complete."""
        elapsed = 0
        while elapsed < max_wait:
            status = self.get_status(task_id)
            if status == "reported":
                print(f"[+] Task {task_id} completed")
                return True
            time.sleep(poll_interval)
            elapsed += poll_interval
            print(f"  Waiting... ({elapsed}s, status: {status})")
        return False

    def get_report(self, task_id):
        """Retrieve full analysis report."""
        url = f"{self.base_url}/apiv2/tasks/get/report/{task_id}/"
        resp = requests.get(url, headers=self.headers)
        return resp.json()

    def get_config(self, task_id):
        """Get extracted malware configuration."""
        report = self.get_report(task_id)
        configs = report.get("CAPE", {}).get("configs", [])
        return configs

    def get_dropped_files(self, task_id):
        """List files dropped during analysis."""
        report = self.get_report(task_id)
        return report.get("dropped", [])

    def get_network_iocs(self, task_id):
        """Extract network IOCs from analysis."""
        report = self.get_report(task_id)
        network = report.get("network", {})
        iocs = {
            "dns": [d.get("request") for d in network.get("dns", [])],
            "http": [h.get("uri") for h in network.get("http", [])],
            "tcp": [f"{h.get('dst')}:{h.get('dport')}"
                    for h in network.get("tcp", [])],
        }
        return iocs

    def analyze_sample(self, filepath):
        """Full automated analysis pipeline."""
        task_id = self.submit_file(filepath)
        if not task_id:
            return None

        if self.wait_for_completion(task_id):
            report = {
                "task_id": task_id,
                "config": self.get_config(task_id),
                "network_iocs": self.get_network_iocs(task_id),
                "dropped_files": len(self.get_dropped_files(task_id)),
            }
            return report
        return None


if __name__ == "__main__":
    if len(sys.argv) < 2:
        print(f"Usage: {sys.argv[0]} <malware_sample> [cape_url]")
        sys.exit(1)

    url = sys.argv[2] if len(sys.argv) > 2 else "http://localhost:8000"
    client = CAPEClient(url)
    result = client.analyze_sample(sys.argv[1])
    if result:
        print(json.dumps(result, indent=2))
```

## 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

- [CAPEv2 GitHub](https://github.com/kevoreilly/CAPEv2)
- [CAPE Sandbox Documentation](https://capev2.readthedocs.io/)
- [Automating Malware Analysis with CAPE](https://endsec.au/blog/building-an-automated-malware-sandbox-using-cape/)
- [Installing CAPEv2 on Ubuntu](https://medium.com/@rizqisetyokus/building-capev2-automated-malware-analysis-sandbox-part-1-da2a6ff69cdb)
