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Malware Detection And Reporting

  • 761 installs
  • 10 repo stars
  • Updated August 4, 2026
  • aradotso/security-skills

malware-detection-and-reporting is an agent skill that identifies, analyzes, and reports GitHub repositories distributing malware disguised as cracked security tools or keygens.

About

malware-detection-and-reporting is an agent skill from aradotso/security-skills by ara.so that helps developers detect malicious software distribution repositories masquerading as legitimate security tools, fake antivirus cracks, keygens, and credential-stealing GitHub projects. The skill guides identification of piracy malware repos, analysis of suspicious software distribution patterns, and reporting workflows before cloning or recommending projects. Developers reach for malware-detection-and-reporting when evaluating unknown GitHub repos, investigating fake security software, or deciding whether to report malicious distribution channels.

  • Detects repositories promising cracked commercial security software
  • Identifies suspicious topic combinations like defender-bypass with crack or keygen
  • Flags repos lacking real code or showing artificial star inflation
  • Recognizes common malware file types (.exe, .dll, .scr) without accompanying source
  • Provides analysis and reporting guidance for malicious distribution projects

Malware Detection And Reporting by the numbers

  • 761 all-time installs (skills.sh)
  • +20 installs in the week ending Jul 20, 2026 (Skillselion tracking)
  • Ranked #442 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/aradotso/security-skills --skill malware-detection-and-reporting

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Listed on Skillselion
Installs761
repo stars10
Last updatedAugust 4, 2026
Repositoryaradotso/security-skills

How do you detect malware repos on GitHub?

Scan GitHub repositories for malware disguised as cracked security tools or keygens before trusting or sharing them.

Who is it for?

Security-minded developers vetting third-party GitHub repositories before install, fork, or team recommendation.

Skip if: Teams running formal SAST/DAST on their own application source code rather than investigating external malware distribution repos.

When should I use this skill?

User asks to check if a GitHub project distributes malware, detect fake security software repos, or report malicious credential-stealing repositories.

What you get

Malware identification report, suspicious repo analysis notes, and GitHub malicious project reporting guidance.

  • Malware triage report
  • GitHub abuse reporting steps

By the numbers

  • Part of aradotso/security-skills collection by ara.so

Files

SKILL.mdMarkdownGitHub ↗

Malware Detection and Reporting

Skill by ara.so — Security Skills collection.

Overview

This skill helps identify and report malicious repositories that disguise themselves as legitimate software (cracks, keygens, activators) but actually distribute malware, trojans, or credential stealers. The project "MistDuckCount/Bitdefender-Total-Security-Crack-2026" is a known malware distribution repository that should be reported and avoided.

Warning Signs of Malicious Repositories

Red Flags

1. Promises of "cracked" commercial software - Especially security software like antivirus programs 2. Suspicious topics - Combinations like "defender-bypass", "thread-hijacking", "rootkit-remover" with crack/keygen 3. No actual code - Repository lacks real implementation files or README 4. Inflated stars - Artificial engagement (e.g., "3 stars/day" pattern) 5. Malicious file types - .exe, .dll, .scr files without source code 6. License "NOASSERTION" - Avoiding legal liability 7. Recent creation with high activity - Created recently but shows suspicious engagement

Detection Methodology

package main

import (
    "fmt"
    "strings"
)

// MalwareIndicators defines suspicious patterns
type MalwareIndicators struct {
    SuspiciousTopics []string
    RedFlagKeywords  []string
    RiskScore        int
}

// AnalyzeRepository checks for malware distribution patterns
func AnalyzeRepository(description, topics string) MalwareIndicators {
    indicators := MalwareIndicators{
        SuspiciousTopics: []string{},
        RedFlagKeywords:  []string{},
        RiskScore:        0,
    }
    
    // Check for crack/keygen keywords
    crackKeywords := []string{
        "crack", "keygen", "loader", "pre-activated",
        "license key", "activation", "full version",
    }
    
    for _, keyword := range crackKeywords {
        if strings.Contains(strings.ToLower(description), keyword) {
            indicators.RedFlagKeywords = append(indicators.RedFlagKeywords, keyword)
            indicators.RiskScore += 15
        }
    }
    
    // Check for bypass/exploit topics
    dangerousTopics := []string{
        "defender-bypass", "thread-hijacking", "rootkit",
        "exploit-mitigation",
    }
    
    for _, topic := range dangerousTopics {
        if strings.Contains(strings.ToLower(topics), topic) {
            indicators.SuspiciousTopics = append(indicators.SuspiciousTopics, topic)
            indicators.RiskScore += 20
        }
    }
    
    // Check for commercial software names
    if strings.Contains(strings.ToLower(description), "bitdefender") ||
       strings.Contains(strings.ToLower(description), "kaspersky") ||
       strings.Contains(strings.ToLower(description), "norton") {
        indicators.RiskScore += 25
    }
    
    return indicators
}

func main() {
    description := "Bitdefender Total Security Crack License Key Pre-Activated"
    topics := "defender-bypass thread-hijacking rootkit-remover"
    
    result := AnalyzeRepository(description, topics)
    
    fmt.Printf("Risk Score: %d/100\n", result.RiskScore)
    fmt.Printf("Suspicious Topics: %v\n", result.SuspiciousTopics)
    fmt.Printf("Red Flag Keywords: %v\n", result.RedFlagKeywords)
    
    if result.RiskScore >= 50 {
        fmt.Println("⚠️  HIGH RISK - Likely malware distribution")
    }
}

Reporting Malicious Repositories

GitHub Reporting Process

# Report via GitHub web interface:
# 1. Navigate to the repository
# 2. Click "⚠️" or go to repository settings
# 3. Select "Report abuse" or "Report content"
# 4. Choose category: "Malware distribution" or "Phishing"

# Or use GitHub API to gather evidence
curl -H "Authorization: token ${GITHUB_TOKEN}" \
     https://api.github.com/repos/MistDuckCount/Bitdefender-Total-Security-Crack-2026

Evidence Collection

package main

import (
    "encoding/json"
    "fmt"
    "net/http"
    "os"
)

type RepoEvidence struct {
    Name        string   `json:"name"`
    Description string   `json:"description"`
    Topics      []string `json:"topics"`
    StarsCount  int      `json:"stargazers_count"`
    CreatedAt   string   `json:"created_at"`
    HasReadme   bool
    HasCode     bool
}

func CollectEvidence(owner, repo string) (*RepoEvidence, error) {
    url := fmt.Sprintf("https://api.github.com/repos/%s/%s", owner, repo)
    
    client := &http.Client{}
    req, err := http.NewRequest("GET", url, nil)
    if err != nil {
        return nil, err
    }
    
    // Use token from environment if available
    if token := os.Getenv("GITHUB_TOKEN"); token != "" {
        req.Header.Set("Authorization", "token "+token)
    }
    
    resp, err := client.Do(req)
    if err != nil {
        return nil, err
    }
    defer resp.Body.Close()
    
    var evidence RepoEvidence
    if err := json.NewDecoder(resp.Body).Decode(&evidence); err != nil {
        return nil, err
    }
    
    return &evidence, nil
}

func GenerateReport(evidence *RepoEvidence) string {
    report := fmt.Sprintf(`
MALWARE DISTRIBUTION REPORT
===========================
Repository: %s
Description: %s
Topics: %v
Stars: %d
Created: %s

INDICATORS:
- Promises cracked commercial software
- Contains bypass/exploit topics
- No legitimate source code
- Artificial engagement pattern

RECOMMENDATION: Report and avoid
`, evidence.Name, evidence.Description, evidence.Topics, 
   evidence.StarsCount, evidence.CreatedAt)
    
    return report
}

Safe Alternatives

Legitimate Security Software

// Instead of cracked software, use legitimate alternatives:

var SafeSecurityTools = map[string]string{
    "antivirus_free": "Windows Defender (built-in)",
    "firewall":       "Built-in OS firewalls",
    "malware_scan":   "Malwarebytes Free",
    "monitoring":     "Process Explorer (Sysinternals)",
}

func RecommendAlternative(requestedTool string) string {
    if alt, ok := SafeSecurityTools[requestedTool]; ok {
        return fmt.Sprintf("Use %s instead - it's free and safe", alt)
    }
    return "Use official trial versions or open-source alternatives"
}

Analysis Tools

Repository Scanner

package main

import (
    "regexp"
    "strings"
)

type ScanResult struct {
    IsSuspicious bool
    Reasons      []string
    Confidence   float64
}

func ScanRepositoryContent(description, readme string) ScanResult {
    result := ScanResult{
        IsSuspicious: false,
        Reasons:      []string{},
        Confidence:   0.0,
    }
    
    // Pattern matching for malicious indicators
    patterns := map[string]*regexp.Regexp{
        "crack_mention":   regexp.MustCompile(`(?i)(crack|keygen|patch|loader|activator)`),
        "bypass_mention":  regexp.MustCompile(`(?i)(bypass|disable|remove)\s+(defender|antivirus|firewall)`),
        "free_premium":    regexp.MustCompile(`(?i)(free|full version|premium)\s+(download|license)`),
        "suspicious_file": regexp.MustCompile(`(?i)\.(exe|dll|scr|bat|vbs|ps1)\s+download`),
    }
    
    matchCount := 0
    for reason, pattern := range patterns {
        if pattern.MatchString(description) || pattern.MatchString(readme) {
            result.Reasons = append(result.Reasons, reason)
            matchCount++
        }
    }
    
    if matchCount > 0 {
        result.IsSuspicious = true
        result.Confidence = float64(matchCount) / float64(len(patterns))
    }
    
    // Check for missing legitimate content
    if len(readme) < 100 || !strings.Contains(readme, "license") {
        result.Reasons = append(result.Reasons, "insufficient_documentation")
        result.Confidence += 0.2
    }
    
    return result
}

Best Practices

For Users

1. Never download cracked security software - It defeats the purpose 2. Use official sources - Download only from vendor websites 3. Report suspicious repositories - Help protect the community 4. Verify authenticity - Check developer history and code presence 5. Use legitimate free alternatives - Many exist for common tools

For Repository Maintainers

// Implement security checks in your CI/CD
package main

import "fmt"

func ValidateRepository() error {
    checks := []struct {
        name string
        pass bool
    }{
        {"Has LICENSE file", true},
        {"Has source code", true},
        {"No executable binaries", true},
        {"Has documentation", true},
        {"No crack/keygen mentions", true},
    }
    
    for _, check := range checks {
        if !check.pass {
            return fmt.Errorf("validation failed: %s", check.name)
        }
    }
    
    return nil
}

Reporting Channels

  • GitHub: Use repository "Report abuse" feature
  • Security vendors: Report to Bitdefender, Microsoft, etc.
  • VirusTotal: Submit suspicious URLs
  • Phishing databases: Report to Anti-Phishing Working Group
  • Search engines: Report phishing via Google Safe Browsing

Conclusion

The "Bitdefender-Total-Security-Crack-2026" repository exhibits all hallmarks of a malware distribution operation. Always avoid cracked software, especially security tools, as they commonly contain trojans, ransomware, or credential stealers. Report such repositories to protect other users.

Related skills

How it compares

Pick malware-detection-and-reporting over generic security review skills when the input is an external suspicious repo—not your team's application codebase.

FAQ

What threats does malware-detection-and-reporting target?

malware-detection-and-reporting focuses on GitHub repositories distributing malware disguised as legitimate security tools, including fake antivirus cracks, keygens, piracy bundles, and credential-stealing project pages.

When should developers invoke malware-detection-and-reporting?

malware-detection-and-reporting should run before trusting or sharing an unknown GitHub repository, when users ask to detect fake security software, analyze suspicious distribution, or report malicious GitHub projects.

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