Building Automated Malware Submission PipelineBLOCK

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The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: building-automated-malware-submission-pipeline
description: 'Builds an automated malware submission and analysis pipeline that collects
  suspicious files from endpoints and email gateways, submits them to sandbox environments
  and multi-engine scanners, and generates verdicts with IOCs for SIEM integration.
  Use when SOC teams need to scale malware analysis beyond manual sandbox submissions
  for high-volume alert triage.

  '
domain: cybersecurity
subdomain: soc-operations
tags:
- soc
- malware-analysis
- sandbox
- automation
- virustotal
- cuckoo
- any-run
- pipeline
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- DE.CM-01
- DE.AE-02
- RS.MA-01
- DE.AE-06
mitre_attack:
- T1204.002
- T1566.001
- T1027
- T1055
- T1497
---
# Building Automated Malware Submission Pipeline

## When to Use

Use this skill when:
- SOC teams face high volume of suspicious file alerts requiring sandbox analysis
- Manual sandbox submission creates bottlenecks in alert triage workflow
- Endpoint and email security tools quarantine files needing automated verdict determination
- Incident response requires rapid malware family identification and IOC extraction

**Do not use** for analyzing live malware samples in production environments — always use isolated sandbox infrastructure.

## Prerequisites

- Sandbox environment: Cuckoo Sandbox, Joe Sandbox, Any.Run, or VMRay
- VirusTotal API key (Enterprise for submission, free for lookup)
- MalwareBazaar API access for known malware lookup
- File collection mechanism: EDR quarantine API, email gateway export, network capture
- Python 3.8+ with `requests`, `vt-py`, `pefile` libraries
- Isolated analysis network with no production connectivity

## Workflow

### Step 1: Build File Collection Pipeline

Collect suspicious files from multiple sources:

```python
import requests
import hashlib
import os
from pathlib import Path
from datetime import datetime

class MalwareCollector:
    def __init__(self, quarantine_dir="/opt/malware_quarantine"):
        self.quarantine_dir = Path(quarantine_dir)
        self.quarantine_dir.mkdir(exist_ok=True)

    def collect_from_edr(self, edr_api_url, api_token):
        """Pull quarantined files from CrowdStrike Falcon"""
        headers = {"Authorization": f"Bearer {api_token}"}

        # Get recent quarantine events
        response = requests.get(
            f"{edr_api_url}/quarantine/queries/quarantined-files/v1",
            headers=headers,
            params={"filter": "state:'quarantined'", "limit": 50}
        )
        file_ids = response.json()["resources"]

        for file_id in file_ids:
            # Download quarantined file
            dl_response = requests.get(
                f"{edr_api_url}/quarantine/entities/quarantined-files/v1",
                headers=headers,
                params={"ids": file_id}
            )
            file_data = dl_response.content
            sha256 = hashlib.sha256(file_data).hexdigest()

            filepath = self.quarantine_dir / f"{sha256}.sample"
            filepath.write_bytes(file_data)
            yield {"sha256": sha256, "path": str(filepath), "source": "edr"}

    def collect_from_email_gateway(self, smtp_quarantine_path):
        """Pull attachments from email gateway quarantine"""
        import email
        from email import policy

        for eml_file in Path(smtp_quarantine_path).glob("*.eml"):
            msg = email.message_from_binary_file(
                eml_file.open("rb"), policy=policy.default
            )
            for attachment in msg.iter_attachments():
                content = attachment.get_content()
                if isinstance(content, str):
                    content = content.encode()
                sha256 = hashlib.sha256(content).hexdigest()
                filename = attachment.get_filename() or "unknown"

                filepath = self.quarantine_dir / f"{sha256}.sample"
                filepath.write_bytes(content)
                yield {
                    "sha256": sha256,
                    "path": str(filepath),
                    "source": "email",
                    "original_filename": filename,
                    "sender": msg["From"],
                    "subject": msg["Subject"]
                }

    def compute_hashes(self, filepath):
        """Calculate MD5, SHA1, SHA256 for a file"""
        with open(filepath, "rb") as f:
            content = f.read()
        return {
            "md5": hashlib.md5(content).hexdigest(),
            "sha1": hashlib.sha1(content).hexdigest(),
            "sha256": hashlib.sha256(content).hexdigest(),
            "size": len(content)
        }
```

### Step 2: Pre-Screen with Hash Lookups

Check if the file is already known before sandbox submission:

```python
import vt

class MalwarePreScreener:
    def __init__(self, vt_api_key, mb_api_url="https://mb-api.abuse.ch/api/v1/"):
        self.vt_client = vt.Client(vt_api_key)
        self.mb_api_url = mb_api_url

    def check_virustotal(self, sha256):
        """Lookup hash in VirusTotal"""
        try:
            file_obj = self.vt_client.get_object(f"/files/{sha256}")
            stats = file_obj.last_analysis_stats
            return {
                "found": True,
                "malicious": stats.get("malicious", 0),
                "suspicious": stats.get("suspicious", 0),
                "undetected": stats.get("undetected", 0),
                "total": sum(stats.values()),
                "threat_label": getattr(file_obj, "popular_threat_classification", {}).get(
                    "suggested_threat_label", "Unknown"
                ),
                "type": getattr(file_obj, "type_description", "Unknown")
            }
        except vt.APIError:
            return {"found": False}

    def check_malwarebazaar(self, sha256):
        """Lookup hash in MalwareBazaar"""
        response = requests.post(
            self.mb_api_url,
            data={"query": "get_info", "hash": sha256}
        )
 

BLOCKgrade D · trust 69/100 Do not install this without reading the findings. The audit found something that could harm you or your machine.

What the source does

Filesystem

none-observed

Network

declared (5 observation(s))

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (3)

if verdict["verdict"] == "MALICIOUS":
        push_iocs_to_blocklist(verdict["iocs"], config["firewall_api"])

"md5": hashlib.md5(content).hexdigest(),

"sha1": hashlib.sha1(content).hexdigest(),

Gates applied: no_behavioural_pass.