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Security audit

extracting-youtube-comments-for-research

Security checks across malware telemetry and agentic risk

Overview

This skill is a straightforward YouTube comment research helper that uses Apify as disclosed, with some credential and third-party data-flow considerations users should understand.

Install this only if you are comfortable sending the selected public YouTube targets and scrape job details to Apify, and keep APIFY_TOKEN protected. Prefer managed Apify tooling or the provided helper over pasting token-bearing curl URLs into shared logs or shell history, and set explicit max limits for large research runs.

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
Findings (4)

Description-Behavior Mismatch

Medium
Confidence
87% confidence
Finding
The manifest describes a skill focused on extracting and analyzing YouTube comments, returning comment text, likes, replies, username, and timestamp. However, the documented inputs include channel handles, keywords, trending retrieval, search filters, and a generic maxItems setting, which indicate a wider YouTube search/discovery capability beyond comment extraction alone.

External Transmission

Medium
Category
Data Exfiltration
Content
**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~youtube-comments-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "[VIDEO_URL]"}], "type": "comments", "maxComments": 500}'
Confidence
90% confidence
Finding
The skill explicitly instructs sending scraped data and a bearer-equivalent API token to an external third-party service endpoint. External transmission is expected for an Apify-based skill, but it still creates a real data-flow risk because user-supplied targets, scraped comment data, and credentials are sent off-platform and the token is embedded in the request URL, which can be exposed in logs or shell history.

External Transmission

Medium
Category
Data Exfiltration
Content
**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~youtube-comments-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "[VIDEO_URL]"}], "type": "comments", "maxComments": 500}'
```
Confidence
88% confidence
Finding
The hardcoded Apify API endpoint confirms data leaves the local environment and is sent to a third-party service. In this skill context that behavior is expected, but it remains security-relevant because it expands the trust boundary and may expose request metadata, target URLs, and associated credentials to external infrastructure.

Description-Behavior Mismatch

Low
Confidence
76% confidence
Finding
The manifest presents the skill as returning analysis-ready comment data, implying a data retrieval/reporting function. The documented workflow additionally performs local file output via run_actor.js with --output paths, which is extra behavior not described in the manifest.

VirusTotal

59/59 vendors flagged this skill as clean.

View on VirusTotal

Static analysis

No suspicious patterns detected.