--- 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 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 - 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]} [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)