literature-review-paper-screener

• Outcome: Pass
• Latest audit: Sep 17, 2026 · 9:44 AM UTC
• Version: 1.4.6

Overview

This skill is a disclosed literature-review workflow that searches locally, sends minimized paper evidence to a paid cloud screener only after confirmation, and uses local helper scripts for validation and Excel output.

Before installing, be comfortable using the LoomLoom CLI and sending minimized paper evidence to the selected third-party cloud platform for a per-paper fee. Do not include personal details or credentials in handoff records, and require a fresh confirmation before every paid run.

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

• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep
• MCP Least Privilege: Underdeclared Capability, Wildcard Permission, Missing Permission Declaration
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access

Findings (3)

Lp3

Medium

• Category: MCP Least Privilege
• Confidence: 97% confidence
• Finding: The skill requires broad local file read/write behavior via helper scripts and generated artifacts, but it declares no explicit tool scope or allowed-tools boundary. That omission weakens least-privilege controls and makes it easier for an agent runtime to over-grant filesystem access beyond the files actually needed by the workflow.

Autonomous Decision Making

Medium

• Category: Excessive Agency

Content

## Operating rules

- **Ask the user which platform before every cloud run — including test and verification runs.**
  Never default to the currently active profile without asking (step 1.5), and never skip the
  platform + fee + count confirmation ceremony (step 8) for any run, test or not. The confirmation
  must come from the user after the numbers have been shown: silence, a previous run's approval, or
  an earlier platform choice is not a confirmation, and if the user does not respond you do not

• Confidence: 75% confidence
• Finding: Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Autonomous Decision Making

Medium

• Category: Excessive Agency

Content

## Operating rules

- **Ask the user which platform before every cloud run — including test and verification runs.**
  Never default to the currently active profile without asking (step 1.5), and never skip the
  platform + fee + count confirmation ceremony (step 8) for any run, test or not. The confirmation
  must come from the user after the numbers have been shown: silence, a previous run's approval, or
  an earlier platform choice is not a confirmation, and if the user does not respond you do not

• Confidence: 75% confidence
• Finding: Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Static analysis

No suspicious patterns detected.