ClawHub
Back to skill

Security audit

Geoskill: Drought Monitor

Security checks across malware telemetry and agentic risk

Overview

This skill is a straightforward drought-monitoring tool that fetches public NASA POWER weather data or processes local CSV files, with some privacy and dependency hygiene notes.

Install only in an environment where it is acceptable to send queried coordinates and date ranges to NASA POWER. For sensitive sites, use the local CSV mode. Consider pinning or constraining updated dependency versions before production use.

SkillSpector

By NVIDIA
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (10)

Intent-Code Divergence

Medium
Confidence
93% confidence
Finding
The privacy disclosure asserts that NASA does not log IP addresses, but this script has no way to verify, enforce, or guarantee a third-party service's logging practices. This can mislead users about privacy risks when the tool transmits precise location and date-range data to an external endpoint.

Missing User Warnings

Low
Confidence
86% confidence
Finding
The skill explicitly promotes automatic fetching from the NASA POWER API using user-supplied latitude, longitude, and date ranges, but it does not warn users that these inputs will be transmitted to an external service. While the data is not highly sensitive in most cases, geolocation and temporal query data can still reveal operational interests, monitored sites, or user activity patterns in some environments.

Unpinned Dependencies

Low
Category
Supply Chain
Content
numpy>=1.21.0
requests>=2.28.0
scipy>=1.7.0
tqdm>=4.64.0
Confidence
92% confidence
Finding
numpy>=1.21.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
numpy>=1.21.0
requests>=2.28.0
scipy>=1.7.0
tqdm>=4.64.0
Confidence
95% confidence
Finding
requests>=2.28.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
numpy>=1.21.0
requests>=2.28.0
scipy>=1.7.0
tqdm>=4.64.0
Confidence
91% confidence
Finding
scipy>=1.7.0

Unpinned Dependencies

Low
Category
Supply Chain
Content
numpy>=1.21.0
requests>=2.28.0
scipy>=1.7.0
tqdm>=4.64.0
Confidence
90% confidence
Finding
tqdm>=4.64.0

Known Vulnerable Dependency: numpy==1.21.0 — 1 advisory(ies): CVE-2021-34141 (Incorrect Comparison in NumPy)

Low
Category
Supply Chain
Confidence
70% confidence
Finding
numpy==1.21.0

Known Vulnerable Dependency: requests==2.28.0 — 8 advisory(ies): CVE-2024-47081 (Requests vulnerable to .netrc credentials leak via malicious URLs); CVE-2024-35195 (Requests `Session` object does not verify requests after making first request wi); CVE-2026-25645 (Requests has Insecure Temp File Reuse in its extract_zipped_paths() utility func) +5 more

High
Category
Supply Chain
Confidence
97% confidence
Finding
requests==2.28.0

Known Vulnerable Dependency: scipy==1.7.0 — 2 advisory(ies): CVE-2023-25399 (A refcounting issue which leads to potential memory leak was discovered in scipy); CVE-2023-29824 (** DISPUTED ** A use-after-free issue was discovered in Py_FindObjects() functio)

High
Category
Supply Chain
Confidence
86% confidence
Finding
scipy==1.7.0

Known Vulnerable Dependency: tqdm==4.64.0 — 2 advisory(ies): CVE-2024-34062 (tqdm CLI arguments injection attack); CVE-2024-34062 (tqdm CLI arguments injection attack)

Low
Category
Supply Chain
Confidence
83% confidence
Finding
tqdm==4.64.0

VirusTotal

65/65 vendors flagged this skill as clean.

View on VirusTotal

Static analysis

No suspicious patterns detected.