Building Automated Malware Submission Pipeline

---
name: building-automated-malware-submission-pipeline
description: 'Use when 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
tags:
- soc
- malware-analysis
- sandbox
- automation
- virustotal
- cuckoo
- any-run
- pipeline
subdomain: soc-operations
version: '1.0'
author: oyi77
license: Apache-2.0
nist_csf:
- DE.CM-01
- DE.AE-02
- RS.MA-01
- DE.AE-06
category: cybersecurity
---

# Building Automated Malware Submission Pipeline

## Overview

Cybersecurity skill for building automated malware submission pipeline. Follows industry best practices and security standards.

## When to Use

**Trigger phrases:**
- "building automated malware submission pipeline"
- "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 det"


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.


## When NOT to Use

- When you lack proper authorization for testing
- For production systems without change management
- When the task requires legal or compliance expertise beyond technical scope


## 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

```python
# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}
```

1. **Assess Requirements** — Evaluate current environment and define automated malware submission pipeline implementation requirements.
2. **Design Architecture** — Plan the automated malware submission pipeline architecture, including components, integrations, and data flows.
3. **Configure Components** — Set up and configure each automated malware submission pipeline component according to best practices.
4. **Test Integration** — Validate that all components work together. Run functional and security tests.
5. **Deploy to Production** — Roll out the implementation with monitoring and rollback capabilities.
6. **Validate and Document** — Verify the implementation meets requirements. Document configuration and runbooks.

## Tools

- **Configuration Management** — Infrastructure as code and automation
- **Monitoring Stack** — Observability and alerting
- **Documentation Platform** — Runbooks and architecture docs


## Process

1. **Reconnaissance** — Gather target information, identify attack surface, enumerate services
1. **Analysis/Exploitation** — Execute the technique, analyze results, document findings
1. **Reporting** — Document IOCs, write findings, provide remediation recommendations

## Verification

- [ ] All automated malware submission pipeline procedures executed completely and documented
- [ ] Findings validated against multiple data sources
- [ ] False positives identified and filtered
- [ ] Results documented with evidence and timestamps
- [ ] Recommendations provided with risk-based prioritization

## Anti-Rationalization Table

| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |