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Security audit

monitoring-brand-mentions-on-twitter

Security checks across malware telemetry and agentic risk

Overview

This skill coherently uses Apify to collect public Twitter/X brand mentions, with expected credential and data-sharing risks that should be handled carefully.

Install only if you are comfortable sending brand search terms and scraper requests to Apify. Store APIFY_TOKEN securely, avoid exposing it in shell history or logs, and treat downloaded CSV/JSON outputs as potentially sensitive operational data containing public tweet content and metadata.

SkillSpector

Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (5)

Missing User Warnings

Medium
Confidence
95% confidence
Finding
The skill requires an APIFY_TOKEN and demonstrates API usage without any warning about protecting secrets, avoiding shell history leakage, or limiting exposure of the token in logs and shared terminals. Although common in documentation, embedding tokens in command examples can cause accidental disclosure or mishandling of credentials.

External Transmission

Medium
Category
Data Exfiltration
Content
**If Apify MCP is not available:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
Confidence
97% confidence
Finding
This command sends user-supplied search terms and the APIFY token to an external third-party service, which is a real data transmission boundary. In the context of brand monitoring this is expected functionality, but it still creates privacy and credential-handling risk because operational data and secrets leave the local environment.

External Transmission

Medium
Category
Data Exfiltration
Content
### Step 3: Fetch and Merge Results

```bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"
```

Merge datasets from all runs. Deduplicate by tweet `id`. Result: unified list of all mentions.
Confidence
94% confidence
Finding
This command retrieves dataset contents from Apify to the local environment and includes the APIFY token in the request URL, again crossing a third-party data boundary. The behavior is aligned with the skill's purpose, but it still risks exposing credentials through logs/history and handling potentially sensitive scraped content without notice.

External Transmission

Medium
Category
Data Exfiltration
Content
### Step 3: Fetch and Merge Results

```bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"
```

Merge datasets from all runs. Deduplicate by tweet `id`. Result: unified list of all mentions.
Confidence
94% confidence
Finding
This command retrieves dataset contents from Apify to the local environment and includes the APIFY token in the request URL, again crossing a third-party data boundary. The behavior is aligned with the skill's purpose, but it still risks exposing credentials through logs/history and handling potentially sensitive scraped content without notice.

Missing User Warnings

Low
Confidence
90% confidence
Finding
The skill explicitly instructs saving fetched results to local CSV/JSON files but does not warn the user where data will be written or that the output may contain scraped tweet content and metadata. This can lead to unintended local data persistence, especially in automated environments or shared workspaces, even though it is not an exploit by itself.

VirusTotal

63/63 vendors flagged this skill as clean.

View on VirusTotal

Static analysis

No suspicious patterns detected.