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Security audit

drought-monitor

Security checks across malware telemetry and agentic risk

Overview

This skill is a straightforward drought-monitoring CLI that fetches public NASA POWER weather data or processes local CSV files, with no hidden persistence or credential handling found.

Install this in an isolated Python environment, prefer updated or pinned dependency versions, and use local CSV mode if you do not want coordinates and date ranges sent to NASA POWER. Review output paths before running because the CLI writes CSV and JSON files where requested.

SkillSpector

By NVIDIA
Vulnerability Patterns
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (8)

Missing User Warnings

Low
Confidence
75% confidence
Finding
The skill states that it auto-fetches NASA POWER data but does not prominently disclose that execution sends user-supplied latitude, longitude, and date ranges to an external service. While the transmitted data is not highly sensitive in most cases, lack of explicit network disclosure can surprise users and create privacy or policy-compliance issues in restricted 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
89% 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
89% 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
89% 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
88% confidence
Finding
tqdm>=4.64.0

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
94% 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
73% confidence
Finding
tqdm==4.64.0

VirusTotal

65/65 vendors flagged this skill as clean.

View on VirusTotal

Static analysis

Detected: suspicious.dynamic_code_execution

Dynamic code execution detected.

Critical
Code
suspicious.dynamic_code_execution
Location
tests/test_drought-monitor.py:16