fort-firewall-malware-analysis

name	fort-firewall-malware-analysis
description	Analyze and document malicious software distribution disguised as legitimate Fort Firewall security software
triggers	["analyze this suspicious firewall repository","check if this Fort Firewall download is legitimate","investigate potential malware in security software","review this firewall project for malicious indicators","identify red flags in this security tool repository","verify authenticity of Fort Firewall download","detect malware distribution in open source projects","analyze fake software repository patterns"]

Fort Firewall Malware Analysis Skill

Skill by ara.so — Security Skills collection

⚠️ CRITICAL WARNING

This repository (lloyd17x/fort-firewall-security-fix) is NOT legitimate software. It is a malware distribution scheme disguised as a security tool. This skill teaches agents to identify and analyze such threats.

What This Repository Actually Is

Red Flags Indicating Malware:

1. Fake "Product Key Patch" - Promotes executable files that "unlock" software, a classic malware vector
2. GitHub Pages Download - Legitimate software uses GitHub Releases, not external redirect pages
3. Antivirus "False Positive" Claims - Dismisses security warnings as normal
4. No Source Code - HTML project with no actual firewall code
5. Keyword Stuffing - SEO spam topics like "fort-firewall-key", "fort-firewall-patch"
6. Suspicious Metrics - 182 stars in 19 days (9 stars/day) suggests bot inflation
7. Future Date - Created "2026-06-17" (impossible timestamp indicates manipulation)
8. MIT License Abuse - Claims permissive license for proprietary malware
9. "Community Edition" Framing - Legitimizes piracy/malware distribution

Real Fort Firewall Project

The legitimate Fort Firewall is:

• Repository: tnodir/fort (not this repository)
• License: GPL-3.0 (open source, no "product keys")
• Language: C++/Qt (not HTML)
• Distribution: GitHub Releases with source code

Malware Indicators Analysis

Pattern Recognition

import re
from dataclasses import dataclass
from typing import List

@dataclass
class MalwareIndicator:
    pattern: str
    severity: str
    description: str

MALWARE_PATTERNS = [
    MalwareIndicator(
        pattern=r"(crack|patch|keygen|product[_\s]?key|license[_\s]?key|activation)",
        severity="CRITICAL",
        description="Software cracking terminology"
    ),
    MalwareIndicator(
        pattern=r"disable.*antivirus|false[_\s]?positive|temporarily disable",
        severity="CRITICAL",
        description="Instructs users to disable security software"
    ),
    MalwareIndicator(
        pattern=r"\.github\.io/[^/]+/.*\.(exe|msi|zip)",
        severity="HIGH",
        description="Executable hosted on GitHub Pages"
    ),
    MalwareIndicator(
        pattern=r"(full[_\s]?version|premium|pro[_\s]?edition).*free",
        severity="MEDIUM",
        description="Promises premium software for free"
    ),
]

def analyze_repository_readme(readme_content: str) -> List[dict]:
    """Scan README for malware distribution indicators."""
    findings = []
    
    for indicator in MALWARE_PATTERNS:
        matches = re.finditer(indicator.pattern, readme_content, re.IGNORECASE)
        for match in matches:
            findings.append({
                "severity": indicator.severity,
                "pattern": indicator.description,
                : .group(),
                : .start()
            })
    
     findings


 (, , encoding=)  f:
    readme = f.read()

findings = analyze_repository_readme(readme)
 finding  findings:
    ()

GitHub Repository Metadata Analysis

// Node.js script to analyze suspicious repositories
const axios = require('axios');

async function analyzeRepository(owner, repo) {
  const apiUrl = `https://api.github.com/repos/${owner}/${repo}`;
  const token = process.env.GITHUB_TOKEN; // Use personal access token
  
  try {
    const response = await axios.get(apiUrl, {
      headers: { 'Authorization': `token ${token}` }
    });
    
    const data = response.data;
    const redFlags = [];
    
    // Check for suspicious patterns
    if (data.stargazers_count > 100 && data.forks_count < 5) {
      redFlags.push({
        flag: "STAR_INFLATION",
        detail: `${data.stargazers_count} stars but only ${data.forks_count} forks`
      });
    }
    
    if (data.language === "HTML" && data.name.includes("firewall")) {
      redFlags.push({
        flag: "LANGUAGE_MISMATCH",
        : 
      });
    }
    
     (!data.) {
      redFlags.({
        : ,
        : 
      });
    }
    
     (data. ===  && data. > ) {
      redFlags.({
        : ,
        : 
      });
    }
    
    
     suspiciousTopics = data..( 
      t.() || t.() || t.()
    );
    
     (suspiciousTopics. > ) {
      redFlags.({
        : ,
        : 
      });
    }
    
     {
      : ,
      : data.,
      : data.,
      : data.,
      : data.,
      : data.,
      : redFlags,
      : (redFlags)
    };
    
  }  (error) {
      ();
  }
}

 () {
   weights = {
    : ,
    : ,
    : ,
    : ,
    : 
  };
  
   redFlags.( 
    score + (weights[flag.] || ), 
  );
}


(, )
  .( {
    .(.(analysis, , ));
    
     (analysis. > ) {
      .();
    }
  })
  .(.);

Download Link Analysis

import requests
from urllib.parse import urlparse
import hashlib

def analyze_download_link(url: str) -> dict:
    """
    Analyze a download link for malware distribution patterns.
    DO NOT actually download or execute files.
    """
    parsed = urlparse(url)
    
    risk_factors = []
    
    # GitHub Pages used for malware hosting
    if ".github.io" in parsed.netloc:
        risk_factors.append({
            "factor": "GITHUB_PAGES_HOSTING",
            "severity": "HIGH",
            "reason": "Executable files should be in GitHub Releases, not Pages"
        })
    
    # Direct executable download
    if parsed.path.endswith((".exe", ".msi", ".bat", ".ps1", ".scr")):
        risk_factors.append({
            "factor": "DIRECT_EXECUTABLE",
            "severity": "CRITICAL",
            "reason": "Direct executable download without source code"
        })
    
    # Redirect through external page
    if not parsed.path.endswith((".exe", ".zip")) and "download" in url.lower():
        risk_factors.append({
            "factor": "REDIRECT_PAGE",
            "severity": ,
            : 
        })
    
     {
        : url,
        : parsed.netloc,
        : risk_factors,
        :   risk_factors  
    }


download_url = 
analysis = analyze_download_link(download_url)

()
()
 factor  analysis[]:
    ()

Reporting Malware Repositories

To GitHub

# Report via GitHub's abuse form
# URL: https://github.com/contact/report-abuse

# Provide these details:
# 1. Repository URL: https://github.com/lloyd17x/fort-firewall-security-fix
# 2. Violation type: Malware distribution
# 3. Evidence: 
#    - Promotes executable "patches" that bypass antivirus
#    - No source code despite claiming to be open source
#    - Uses GitHub Pages to host malware downloads
#    - Impersonates legitimate Fort Firewall project

Automated Reporting Script

import os
import requests

def report_malicious_repository(owner: str, repo: str, evidence: list):
    """
    Create a report document for malicious repository.
    Note: GitHub does not have a public API for abuse reports.
    This generates a report file for manual submission.
    """
    
    report = f"""
# Malware Distribution Report

## Repository Information
- **URL**: https://github.com/{owner}/{repo}
- **Report Date**: {datetime.now().isoformat()}
- **Reporter**: Security Researcher

## Violation Type
Malware Distribution / Software Piracy / Impersonation

## Evidence

"""
    
    for i, item in enumerate(evidence, 1):
        report += f"{i}. {item}\n"
    
    report += """

## Recommended Action
Immediate takedown and account suspension

## Additional Context
This repository impersonates the legitimate Fort Firewall project (tnodir/fort)
and distributes malware disguised as a "product key patch."
"""
    
    # Save report to file
    filename = f"malware_report_{owner}_{repo}_{datetime.now().strftime('%Y%m%d')}.txt"
    with open(filename, "w") as f:
        f.write(report)
    
    print(f"Report generated: {filename}")
    print("Submit manually at: https://github.com/contact/report-abuse")
    
    return filename

# Example
from datetime import datetime

evidence = [
    ,
    ,
    ,
    ,
    ,
    ,
    
]

report_malicious_repository(, , evidence)

Safe Security Software Verification

Checklist for Legitimate Projects

verification_checklist:
  source_code:
    - Present: true
    - Matches_language: true
    - Build_instructions: true
    
  distribution:
    - GitHub_Releases: true
    - Code_signing: true
    - Checksums_provided: true
    
  documentation:
    - Installation_from_source: true
    - No_antivirus_disable_instructions: false
    - No_piracy_terminology: false
    
  repository_health:
    - Active_issues: true
    - Organic_stars_to_forks_ratio: true  # Usually 5:1 to 20:1
    - Recent_commits: true
    
  licensing:
    - Clear_license: true
    - License_file_present: true
    - No_product_keys_required: true

Python Verification Tool

import requests
from typing import Dict, Any

def verify_security_software(owner: str, repo: str) -> Dict[str, Any]:
    """
    Verify if a security software repository is legitimate.
    """
    api_url = f"https://api.github.com/repos/{owner}/{repo}"
    token = os.getenv("GITHUB_TOKEN")
    
    headers = {"Authorization": f"token {token}"} if token else {}
    response = requests.get(api_url, headers=headers)
    
    if response.status_code != 200:
        return {"error": "Repository not found or inaccessible"}
    
    data = response.json()
    
    checks = {
        "has_source_code": data.get("language") not in ["HTML", None],
        "has_license": data.get("license") is not None,
        "has_issues": data.get("open_issues_count", 0) > 0,
        "stars_to_forks_ratio": (
            data.get("stargazers_count", 0) / max(data.get("forks_count", 1), )
        ),
        : ,  
    }
    
    
    releases_url = 
    releases_response = requests.get(releases_url, headers=headers)
     releases_response.status_code == :
        releases = releases_response.json()
        checks[] = (releases) > 
    
    
    score = 
     checks[]: score += 
     checks[]: score += 
     checks[]: score += 
      < checks[] < : score += 
     checks[]: score += 
    
     {
        : ,
        : checks,
        : score,
        :   score >=     score >=   
    }


legitimate = verify_security_software(, )
malicious = verify_security_software(, )

()
()
()

()
()
()

Common Patterns in Malware Distribution

1. "Enhanced Edition" / "Pro Version" - Fake premium versions of free software
2. "Community Patch" - Implies grassroots legitimacy for malware
3. "Product Key Generator" - Always malware, no exceptions
4. "Disable Antivirus Instructions" - Red flag for malicious payload
5. GitHub Pages for Executables - Abuse of static hosting for malware
6. Future Dates in Metadata - Manipulation to appear current
7. SEO Keyword Stuffing - Topics/tags designed to trap searchers
8. Zero Forks, High Stars - Bot-inflated popularity metrics

Troubleshooting / FAQ

Q: How do I identify fake security software? A: Check for source code, build instructions, and use of GitHub Releases (not Pages) for distribution.

Q: What should I do if I downloaded this file? A:

1. Do NOT execute the file
2. Delete the downloaded file
3. Run a full antivirus scan with updated definitions
4. Check for unauthorized changes (Task Scheduler, startup programs)

Q: Is there a legitimate Fort Firewall? A: Yes, the real project is at github.com/tnodir/fort (GPL-3.0 licensed, C++ source code).

Q: How can I report this to GitHub? A: Visit https://github.com/contact/report-abuse and select "Malware distribution"

Resources

• VirusTotal: https://www.virustotal.com - Scan suspicious files/URLs
• Legitimate Fort Firewall: https://github.com/tnodir/fort
• GitHub Security: https://docs.github.com/en/code-security
• MITRE ATT&CK - Malware: https://attack.mitre.org/techniques/T1204/

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This skill teaches agents to identify malware distribution schemes, not to use the malicious software.