patron-ig-f100k

• Outcome: Review
• Latest audit: Sep 17, 2026 · 8:56 PM UTC
• Version: 1.0.3

Overview

The skill’s Instagram analytics purpose is coherent, but it automatically sources a local secrets file and sends reel URLs to a third-party transcription service, so it deserves review before installation.

Review this skill before installing. It is not clearly malicious, but it should only be used if you are comfortable sharing Instagram reel URLs with Supadata, using Apify for Instagram scraping, and letting the agent update a persistent patterns memory file. Prefer providing only SUPADATA_API_KEY through a scoped secret mechanism instead of allowing the skill to source a whole secrets.env file.

A.I.G

Vulnerability Patterns

• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally
• Unauthorized Access and Privilege Escalation: Obtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (5)

Credential Access

High

• Category: Privilege Escalation

Content

Para CADA video/reel filtrado, ejecutar:

```bash
[ -z "$SUPADATA_API_KEY" ] && [ -f "$HOME/.config/f100k/secrets.env" ] && set -a && . "$HOME/.config/f100k/secrets.env" && set +a
curl -s -X GET "https://api.supadata.ai/v1/transcript?url=https://www.instagram.com/reel/[shortCode]/" \
  -H "x-api-key: $SUPADATA_API_KEY"
```

• Confidence: 88% confidence
• Finding: The skill instructs sourcing a local secrets file into the shell environment at runtime, which is a form of credential access beyond using already-provisioned environment variables. In an agent setting, this broadens secret exposure and can unintentionally grant the skill access to additional credentials present in the file, especially if the file contains more than the single API key needed.

Missing User Warnings

Medium

• Confidence: 95% confidence
• Finding: The skill sends Instagram reel URLs to a third-party transcription service without an explicit disclosure or consent step tied to that transmission. Even if the reels are public, this shares user-associated content and behavioral metadata with an external processor, creating privacy, compliance, and unexpected data-handling risks.

External Transmission

Medium

• Category: Data Exfiltration

Content

```bash
[ -z "$SUPADATA_API_KEY" ] && [ -f "$HOME/.config/f100k/secrets.env" ] && set -a && . "$HOME/.config/f100k/secrets.env" && set +a
curl -s -X GET "https://api.supadata.ai/v1/transcript?url=https://www.instagram.com/reel/[shortCode]/" \
  -H "x-api-key: $SUPADATA_API_KEY"
```

• Confidence: 94% confidence
• Finding: This is a real external transmission: the skill performs an HTTP request to Supadata containing a reel URL, which discloses user-related content to a third party. In this skill's context, the transmission is functionally necessary for transcription, but it still expands the trust boundary and introduces privacy and data governance risk.

Missing User Warnings

Medium

• Confidence: 90% confidence
• Finding: The skill instructs the agent to automatically write persistent memory files and update an index without requiring explicit user confirmation at execution time. In an agent context, silent file modification can surprise users, pollute long-term memory, and create integrity issues if the analysis is wrong or triggered unexpectedly by automation.

Natural-Language Policy Violations

Low

• Confidence: 95% confidence
• Finding: Hardcoding 'lunes que viene a las 08:05 Lima' in the final output can misrepresent when automation will actually run if the user's timezone differs. While low severity, this can cause operational confusion, missed reviews, or actions occurring at unintended times in an automated workflow.

Static analysis

No suspicious patterns detected.