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Security audit

Dataset-Creation-Skill

Security checks for vulnerabilities and agentic risk

Overview

This is a coherent Markdown guide for dataset creation and model training, with no hidden execution, persistence, or credential-handling behavior found.

Before installing or using this skill, treat it as a workflow guide: only use data you are authorized to process, confirm licenses and scraping permissions, remove PII/secrets from internal data, and document dataset sources and restrictions before training or sharing outputs.

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 (2)

Vague Triggers

Medium
Category
Not specified by scanner
Confidence
95% confidence
Finding

The description uses very broad trigger phrases such as 'create a dataset', 'prepare training data', and 'fine-tune a model', which can cause the skill to activate for many generic ML requests outside the user's actual intent. Over-broad invocation increases the chance the agent applies this workflow in inappropriate contexts, potentially steering users toward data collection or training actions without sufficient scoping, privacy review, or consent checks.

Content

No source excerpt is available for this finding.

Missing User Warnings

Medium
Category
Not specified by scanner
Confidence
93% confidence
Finding

The skill recommends sourcing data from internal logs/databases and synthetic generation, but it does not prominently require privacy, consent, redaction, or policy checks before those activities. In a dataset-creation context, this omission is meaningful because users may operationalize collection from sensitive sources and propagate PII, confidential data, or restricted content into training sets.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.