Amazon FBA Finder

• Outcome: Review
• Latest audit: May 29, 2026 · 9:24 PM UTC
• Version: 1.0.0

Overview

This skill is not clearly destructive, but it asks for marketplace API keys and sells real-time Amazon/Alibaba research features that the included code mostly does not implement.

Review before installing or paying. Do not provide real Amazon or Alibaba API keys until the publisher documents credential handling and ships working, scoped integrations. Treat product discovery and supplier recommendations as unproven in this version; the useful implemented portion appears mainly to be local FBA profit calculation.

SkillSpector

By NVIDIA

Vulnerability Patterns

• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Supply Chain: Unpinned Dependencies, External Script Fetching, Obfuscated Code
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep

Findings (10)

Missing User Warnings

Medium

• Confidence: 93% confidence
• Finding: The README instructs users to provide Amazon and Alibaba API keys but does not disclose how marketplace queries, supplier searches, or related business data may be transmitted to external services. This creates a real transparency and privacy/security risk because users may expose sensitive operational data and credentials without understanding the data-sharing surface.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

requests>=2.31.0
beautifulsoup4>=4.12.0
pandas>=2.0.0
numpy>=1.24.0

• Confidence: 96% confidence
• Finding: The dependency is specified with a lower bound only, which allows installation of different versions over time and weakens build reproducibility and supply-chain control. In a security-sensitive environment this can result in pulling an unintended or newly compromised release, though the requirements file alone does not prove active exploitation.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

requests>=2.31.0
beautifulsoup4>=4.12.0
pandas>=2.0.0
numpy>=1.24.0
python-dotenv>=1.0.0

• Confidence: 96% confidence
• Finding: Using an unpinned version for beautifulsoup4 permits non-deterministic installs and increases supply-chain risk because future builds may resolve to different code than was tested. This is generally a configuration weakness rather than a direct exploitable flaw by itself.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

requests>=2.31.0
beautifulsoup4>=4.12.0
pandas>=2.0.0
numpy>=1.24.0
python-dotenv>=1.0.0
aiohttp>=3.9.0

• Confidence: 96% confidence
• Finding: A lower-bound-only pandas requirement allows dependency drift across environments and time, reducing reproducibility and making it easier for vulnerable or unexpected releases to enter the build. This does not itself execute malicious code, but it materially increases supply-chain exposure.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

requests>=2.31.0
beautifulsoup4>=4.12.0
pandas>=2.0.0
numpy>=1.24.0
python-dotenv>=1.0.0
aiohttp>=3.9.0

• Confidence: 97% confidence
• Finding: An unpinned numpy dependency means installs may resolve to varying versions, undermining reproducibility and potentially introducing vulnerable or incompatible releases without review. This is a classic supply-chain hardening issue, especially important for widely used transitive dependencies.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

beautifulsoup4>=4.12.0
pandas>=2.0.0
numpy>=1.24.0
python-dotenv>=1.0.0
aiohttp>=3.9.0

• Confidence: 95% confidence
• Finding: python-dotenv is not pinned to an exact version, so future installs may pull unexpected package contents and weaken control over the runtime dependency set. The issue is primarily reduced supply-chain assurance rather than immediate direct exploitation from this file alone.

Unpinned Dependencies

Low

• Category: Supply Chain

Content

pandas>=2.0.0
numpy>=1.24.0
python-dotenv>=1.0.0
aiohttp>=3.9.0

• Confidence: 96% confidence
• Finding: The aiohttp requirement allows any version at or above the minimum, making builds non-reproducible and increasing the chance of unintentionally consuming a flawed release. For network-facing libraries, this can amplify risk because security posture depends strongly on exact version behavior.

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: 90% confidence
• Finding: The requirements file permits installation of requests versions affected by multiple known advisories, and because the specifier is only a minimum bound, vulnerable versions may be selected depending on environment and resolver behavior. Since requests handles outbound HTTP and may process attacker-controlled URLs or credentials, known flaws in this library can expose secrets or weaken transport security in realistic deployments.

Known Vulnerable Dependency: numpy — 10 advisory(ies): CVE-2014-1859 (Numpy arbitrary file write via symlink attack); CVE-2021-41495 (NumPy NULL Pointer Dereference); CVE-2021-33430 (NumPy Buffer Overflow (Disputed)) +7 more

Critical

• Category: Supply Chain
• Confidence: 82% confidence
• Finding: The numpy dependency is flagged with multiple advisories, and the unpinned minimum-version constraint creates uncertainty about whether affected releases may be installed. However, many numpy CVEs require local file-system conditions or specific application usage patterns, so the practical exploitability from this requirements file alone is less clear than for directly network-facing libraries.

Known Vulnerable Dependency: aiohttp — 10 advisory(ies): CVE-2024-52303 (aiohttp has a memory leak when middleware is enabled when requesting a resource ); CVE-2026-34514 (AIOHTTP has CRLF injection through multipart part content type header constructi); CVE-2026-34517 (AIOHTTP has late size enforcement for non-file multipart fields causes memory Do) +7 more

High

• Category: Supply Chain
• Confidence: 87% confidence
• Finding: aiohttp is a network-facing framework/client library, and the requirements file allows versions with multiple known advisories, including issues that can lead to denial of service or request/response handling weaknesses. In skill contexts that may fetch remote content or expose HTTP behavior, leaving this dependency unresolved to a safe version materially increases risk.

VirusTotal

63/63 vendors flagged this skill as clean.

Static analysis

No suspicious patterns detected.