performing-automated-malware-analysis-with-cape

name	performing-automated-malware-analysis-with-cape
description	Use when deploying and operating 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	oyi77
license	Apache-2.0
nist_csf	["DE.AE-02","RS.AN-03","ID.RA-01","DE.CM-01"]

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

Trigger phrases:

• "performing automated malware analysis with cape"

• "Deploy and operate CAPEv2 sandbox for automated malware analysis with behavioral"

• 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

1. Isolate the sample — ensure the malware is in a sandboxed environment with no network access
2. Record file metadata — hash the sample and note file type, size, and compile timestamp
3. Static analysis — examine strings, imports, and disassembled code without execution
4. Dynamic analysis — execute in a monitored sandbox and record behavior (file, registry, network)
5. Document IOCs — extract indicators of compromise and write the analysis report

Step 1: Submit and Analyze Samples via API

#!/usr/bin/env python3
"""CAPE sandbox API client for automated malware submission and analysis."""
import requests
 json
 time
 sys
 pathlib  Path


 :
     ():
        .base_url = base_url.rstrip()
        .headers = {}
         api_token:
            .headers[] = 

     ():
        
        url = 
        files = {: (filepath, )}
        data = options  {}
        data.setdefault(, )
        data.setdefault(, )

        resp = requests.post(url, files=files, data=data, headers=.headers)
        resp.raise_for_status()
        result = resp.json()
        task_id = result.get(, {}).get(, [])[]
        ()
         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=))