Malware Detection Awareness
Recognize cracked software, keygen, and suspicious repos before installing dependencies or skills into your workflow.
Overview
Malware-detection-awareness is a journey-wide agent skill that teaches solo builders to spot malicious software distribution and suspicious repositories before installing downloads or agent skills.
Install
npx skills add https://github.com/aradotso/security-skills --skill malware-detection-awarenessWhat is this skill?
- Enumerated red flags: unauthorized commercial cracks, keygen, loader, and license bypass claims
- GitHub hygiene signals: inflated stars, empty repos, generic names, trademark abuse
- Trigger phrases for agent lookup: fake security software, pirated bundles, compromised downloads
- Worked example repository labeled as malicious distribution (not legitimate vendor software)
- ara.so Security Skills collection framing for education, not exploitation
- Seven numbered red-flag categories in the threat indicators section
- Example metric cited: artificially inflated stars (6 stars/day on empty repository)
Adoption & trust: 554 installs on skills.sh; 1 GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You found a repo or installer promising cracked or “pre-activated” software and cannot tell if it is a legitimate source or malware bait.
Who is it for?
Solo builders pulling skills, binaries, or “security” tools from GitHub and package sites who need a fast red-flag checklist.
Skip if: Teams that already run enterprise EDR and signed-artifact pipelines only—this skill educates on social/supply-chain signals, not SOC automation.
When should I use this skill?
Triggers include identifying malware repos, malicious packages, fake security software, suspicious GitHub repos, pirated software red flags, keygen malware, or compromised downloads.
What do I get? / Deliverables
You can name specific threat indicators and avoid installing suspicious packages until you verify vendor legitimacy and repository integrity.
- Documented threat-indicator assessment for a suspect package or repo
- Go/no-go decision to avoid installing flagged distribution channels
Recommended Skills
Journey fit
Useful at every journey phase - explore requirements and options before committing to a direction.
Where it fits
Evaluate a competitor tool repo that promises free premium AV before citing it in your market notes.
Reject a keygen-backed dependency while spiking a weekend prototype.
Screen a new npm-adjacent GitHub skill fork for empty code and star inflation before wiring it into Claude Code.
Run the red-flag list on installers pulled into CI or release artifacts.
Re-check update channels that switched to “loader” or serial-based activation language.
How it compares
Human-readable threat awareness for install decisions, not a replacement for dependency scanners or Prism’s Security Audits panel data.
Common Questions / FAQ
Who is malware-detection-awareness for?
Indie developers and agent users who install third-party skills and repos daily and need a lightweight way to reject obvious crack-and-keygen malware traps.
When should I use malware-detection-awareness?
Before Build integrations when adding a new skill repo; during Validate when prototyping with unknown tools; at Ship security review; and in Operate when updating dependencies from untrusted links.
Is malware-detection-awareness safe to install?
It is educational security content from ara.so; still review the Security Audits panel on this Prism page and never run binaries from repos the skill itself flags as malicious.
SKILL.md
READMESKILL.md - Malware Detection Awareness
# Malware Detection Awareness > Skill by [ara.so](https://ara.so) — Security Skills collection. ## ⚠️ SECURITY WARNING This repository exhibits multiple indicators of **malicious software distribution**. It does NOT contain legitimate Avast Premium Security software. ## Threat Indicators ### Red Flags Present 1. **Unauthorized Distribution**: Claims to provide "pre-activated" commercial software with "keygen" and "loader" tools 2. **Trademark Abuse**: Unauthorized use of Avast brand name and product names 3. **License Violation**: No legitimate license; distributing cracked commercial software 4. **Suspicious Metrics**: Artificially inflated stars (6 stars/day for empty repository) 5. **No Source Code**: Repository contains no actual code or README 6. **Activation Bypass Claims**: References to "keygen", "serial", "loader" - common malware indicators 7. **Generic Project Name**: "DragonflyTomb" unrelated to security software ### Common Malware Distribution Patterns ```text LEGITIMATE SOFTWARE: ✓ Official vendor website download ✓ Verified digital signatures ✓ Clear licensing terms ✓ Active development history ✓ Real source code ✓ Community engagement MALWARE DISTRIBUTION: ✗ "Cracked" or "pre-activated" claims ✗ Keygens, loaders, patches ✗ Empty repositories with download links ✗ Star manipulation ✗ No verifiable source code ✗ Promises of "free premium" paid software ``` ## Detection Techniques ### Repository Analysis ```go // Example: Programmatic repository risk assessment package main import ( "fmt" "strings" ) type RiskIndicator struct { Pattern string Severity string } func AnalyzeRepository(description, topics []string) []RiskIndicator { risks := []RiskIndicator{} malwareKeywords := []string{ "keygen", "crack", "loader", "pre-activated", "serial", "patch", "activator", "license key", } for _, keyword := range malwareKeywords { descLower := strings.ToLower(description) if strings.Contains(descLower, keyword) { risks = append(risks, RiskIndicator{ Pattern: fmt.Sprintf("Malware keyword: %s", keyword), Severity: "CRITICAL", }) } } // Check for trademark abuse commercialProducts := []string{"avast", "norton", "mcafee", "kaspersky"} for _, product := range commercialProducts { if containsAny(description, []string{product + " premium", product + " pro"}) { risks = append(risks, RiskIndicator{ Pattern: fmt.Sprintf("Unauthorized %s distribution", product), Severity: "HIGH", }) } } return risks } func containsAny(text string, patterns []string) bool { lower := strings.ToLower(text) for _, pattern := range patterns { if strings.Contains(lower, strings.ToLower(pattern)) { return true } } return false } ``` ### URL Safety Checking ```go package security import ( "net/url" "os" "encoding/json" "net/http" ) // CheckURL validates URLs against threat intelligence func CheckURL(targetURL string) (bool, error) { // Use VirusTotal API or similar apiKey := os.Getenv("VIRUSTOTAL_API_KEY") if apiKey == "" { return false, fmt.Errorf("API key not configured") } // Parse and validate URL parsed, err := url.Parse(targetURL) if err != nil { return fals