crypto-watch-skill

• Outcome: Pass
• Latest audit: May 29, 2026 · 8:24 PM UTC
• Version: 1.0.1

Overview

This is a coherent crypto market-data analysis skill with external API calls and trading-style guidance, but no evidence of credential theft, trade execution, exfiltration, or destructive behavior.

Install only in an isolated Python environment, consider pinning dependencies, and be aware that market queries are sent to public data providers. Treat leverage and trading-plan outputs as educational analysis, not financial advice, and avoid providing wallet keys, exchange API keys, or authority to trade.

SkillSpector

By NVIDIA

Vulnerability Patterns

• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code
• MCP Tool Poisoning: Hidden Instructions, Unicode Deception, Parameter Description Injection
• 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 (9)

Description-Behavior Mismatch

Medium

• Confidence: 89% confidence
• Finding: The module and function context present this code as 'pure computation' with no side effects, but analyze_all_assets creates a directory and writes results to disk. In an agent skill, undocumented filesystem writes are a real security concern because they can leak sensitive market inputs, create unexpected persistence, and violate sandbox or user expectations even without network access.

Intent-Code Divergence

Medium

• Confidence: 84% confidence
• Finding: The top-level docstring says the module is 'pure computation' and implies no side effects beyond external data provision, but the implementation writes JSON output files. This mismatch is dangerous in agent environments because downstream systems or reviewers may trust the documentation and allow the skill in contexts where disk writes are not expected or permitted.

Missing User Warnings

Medium

• Confidence: 96% confidence
• Finding: The document gives prescriptive trading guidance that explicitly encourages increasing leverage when ATR% is low and reducing it when volatility is high, but it provides no risk disclosure, suitability checks, or safeguards. In the context of a crypto market-analysis skill that the agent must use for trading-related queries, this can be surfaced to end users as actionable financial advice and may encourage unsafe leveraged trading behavior.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

pandas>=2.0.0
numpy>=1.24.0
requests>=2.31.0
urllib3>=2.0.0

• Confidence: 94% confidence
• Finding: The dependency is specified with a lower bound only, which allows future versions to be installed without review. This weakens build reproducibility and can introduce supply-chain risk if a later release contains a breaking change or vulnerability.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

pandas>=2.0.0
numpy>=1.24.0
requests>=2.31.0
urllib3>=2.0.0

• Confidence: 94% confidence
• Finding: The dependency is unpinned and may resolve to different versions over time, making builds non-reproducible. That increases the chance of unintentionally pulling a vulnerable or incompatible release.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

pandas>=2.0.0
numpy>=1.24.0
requests>=2.31.0
urllib3>=2.0.0

• Confidence: 95% confidence
• Finding: Using requests with only a minimum version allows installation of any later release, which increases supply-chain and reproducibility risk. In a network-facing skill that likely fetches market data, uncontrolled dependency drift is somewhat more relevant because HTTP client behavior affects security.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

pandas>=2.0.0
numpy>=1.24.0
requests>=2.31.0
urllib3>=2.0.0

• Confidence: 95% confidence
• Finding: An unpinned urllib3 version allows future releases to be installed automatically, reducing determinism and increasing exposure to newly introduced defects. Because this skill likely performs external HTTP requests for crypto and market data, transport-library changes can have direct security impact.

Known Vulnerable Dependency: requests — 10 advisory(ies): CVE-2014-1830 (Exposure of Sensitive Information to an Unauthorized Actor in Requests); 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) +7 more

High

• Category: Supply Chain
• Confidence: 72% confidence
• Finding: The requirement `requests>=2.31.0` does not exclude later vulnerable versions, and the listed advisories include recent issues affecting requests behavior around credential handling and verification. In a skill that likely makes outbound HTTP calls to crypto/market data providers, a vulnerable HTTP client can expose credentials, weaken request security, or enable SSRF-adjacent abuse depending on usage.

Known Vulnerable Dependency: urllib3 — 10 advisory(ies): CVE-2025-66471 (urllib3 streaming API improperly handles highly compressed data); CVE-2024-37891 (urllib3's Proxy-Authorization request header isn't stripped during cross-origin ); CVE-2026-21441 (Decompression-bomb safeguards bypassed when following HTTP redirects (streaming ) +7 more

High

• Category: Supply Chain
• Confidence: 76% confidence
• Finding: The requirement `urllib3>=2.0.0` permits installation of future vulnerable versions, and the listed advisories include recent HTTP/proxy/decompression issues that can matter for network-fetching code. Given this skill's market-data purpose, urllib3 is likely part of the request path, so exploitable client-side HTTP flaws could affect confidentiality, integrity, or availability.

VirusTotal

64/64 vendors flagged this skill as clean.

Static analysis

No suspicious patterns detected.