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Security audit

scraping-tiktok-posts-by-music

Security checks for vulnerabilities and agentic risk

Overview

This skill is a straightforward TikTok-by-sound scraping guide that uses Apify as disclosed, with no hidden persistence or local executable payload in the artifact.

Before installing, make sure you are comfortable sending TikTok music URLs and run parameters to Apify/apidojo, use a scoped Apify token, avoid including sensitive query data, and set maxItems when you do not need an unlimited scrape.

A.I.G

Vulnerability Patterns
  • Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
  • Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
  • Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
  • Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally
  • Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Trigger AbuseOverly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
  • 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)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
90% confidence
Finding

The manifest says the skill triggers when the user asks to 'find TikTok posts using an audio clip' or 'find creators using a specific sound,' but it does not define stricter activation boundaries or exclusions. These phrases are broad enough that they could match general exploratory requests and cause unintended invocation.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The skill routes user-supplied TikTok URLs and related parameters to Apify, a third-party service, but does not clearly warn the user about that data transfer. This can cause unanticipated disclosure of user-provided data, query parameters, and usage context to an external processor, which is especially relevant in enterprise or privacy-sensitive settings.

Content

No source excerpt is available for this finding.

External Transmission

Medium
Category
Data Exfiltration
Confidence
95% confidence
Finding

The documented REST call sends input data and an authorization-bearing request to api.apify.com, which is a real external transmission path. While expected for this integration, it is still a security-relevant behavior because user inputs leave the local environment and are processed by a third party.

Content

Scanner excerpt · SKILL.md (reported line 49)May include surrounding context.

REST API fallback

bash
curl -X POST "https://api.apify.com/v2/acts/apidojo~tiktok-music-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": ["https://www.tiktok.com/music/Song-Title-123456"], "maxItems": 100}'

External Transmission

Medium
Category
Data Exfiltration
Confidence
95% confidence
Finding

The documented REST call sends input data and an authorization-bearing request to api.apify.com, which is a real external transmission path. While expected for this integration, it is still a security-relevant behavior because user inputs leave the local environment and are processed by a third party.

Content

Scanner excerpt · SKILL.md (reported line 49)May include surrounding context.

REST API fallback

bash
curl -X POST "https://api.apify.com/v2/acts/apidojo~tiktok-music-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": ["https://www.tiktok.com/music/Song-Title-123456"], "maxItems": 100}'

Static analysis

No suspicious patterns detected.