Trust Assessment
web3-testing received a trust score of 68/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.
SkillShield's automated analysis identified 9 findings: 0 critical, 0 high, 5 medium, and 4 low severity. Key findings include Accesses sensitive environment variables, Unpinned dependencies in example code.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 57/100, indicating areas for improvement.
Last analyzed on June 1, 2026 (commit 0818067b). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings9
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Accesses sensitive environment variables The provided Hardhat configuration snippet accesses several environment variables (`MAINNET_RPC_URL`, `GOERLI_RPC_URL`, `PRIVATE_KEY`, `COINMARKETCAP_API_KEY`, `ETHERSCAN_API_KEY`). If an AI agent is instructed to execute or integrate this code, and its execution environment contains these variables, the agent could read and potentially expose or misuse these sensitive credentials. While standard practice for local development, in an AI agent context, this poses a risk if the agent's environment is not properly sandboxed or if the agent is instructed to log/send these values. Advise users to ensure their AI agent execution environment is properly sandboxed and that sensitive environment variables are not exposed to untrusted code. If the agent is meant to handle such configurations, ensure secure handling and storage of credentials, possibly through a secrets management system rather than direct environment variables. For documentation, explicitly warn users about the security implications of exposing these variables to an agent. | LLM | SKILL.md:20 | |
| MEDIUM | Accesses sensitive environment variables The provided Hardhat configuration snippet accesses several environment variables (`MAINNET_RPC_URL`, `GOERLI_RPC_URL`, `PRIVATE_KEY`, `COINMARKETCAP_API_KEY`, `ETHERSCAN_API_KEY`). If an AI agent is instructed to execute or integrate this code, and its execution environment contains these variables, the agent could read and potentially expose or misuse these sensitive credentials. While standard practice for local development, in an AI agent context, this poses a risk if the agent's environment is not properly sandboxed or if the agent is instructed to log/send these values. Advise users to ensure their AI agent execution environment is properly sandboxed and that sensitive environment variables are not exposed to untrusted code. If the agent is meant to handle such configurations, ensure secure handling and storage of credentials, possibly through a secrets management system rather than direct environment variables. For documentation, explicitly warn users about the security implications of exposing these variables to an agent. | LLM | SKILL.md:26 | |
| MEDIUM | Accesses sensitive environment variables The provided Hardhat configuration snippet accesses several environment variables (`MAINNET_RPC_URL`, `GOERLI_RPC_URL`, `PRIVATE_KEY`, `COINMARKETCAP_API_KEY`, `ETHERSCAN_API_KEY`). If an AI agent is instructed to execute or integrate this code, and its execution environment contains these variables, the agent could read and potentially expose or misuse these sensitive credentials. While standard practice for local development, in an AI agent context, this poses a risk if the agent's environment is not properly sandboxed or if the agent is instructed to log/send these values. Advise users to ensure their AI agent execution environment is properly sandboxed and that sensitive environment variables are not exposed to untrusted code. If the agent is meant to handle such configurations, ensure secure handling and storage of credentials, possibly through a secrets management system rather than direct environment variables. For documentation, explicitly warn users about the security implications of exposing these variables to an agent. | LLM | SKILL.md:27 | |
| MEDIUM | Accesses sensitive environment variables The provided Hardhat configuration snippet accesses several environment variables (`MAINNET_RPC_URL`, `GOERLI_RPC_URL`, `PRIVATE_KEY`, `COINMARKETCAP_API_KEY`, `ETHERSCAN_API_KEY`). If an AI agent is instructed to execute or integrate this code, and its execution environment contains these variables, the agent could read and potentially expose or misuse these sensitive credentials. While standard practice for local development, in an AI agent context, this poses a risk if the agent's environment is not properly sandboxed or if the agent is instructed to log/send these values. Advise users to ensure their AI agent execution environment is properly sandboxed and that sensitive environment variables are not exposed to untrusted code. If the agent is meant to handle such configurations, ensure secure handling and storage of credentials, possibly through a secrets management system rather than direct environment variables. For documentation, explicitly warn users about the security implications of exposing these variables to an agent. | LLM | SKILL.md:33 | |
| MEDIUM | Accesses sensitive environment variables The provided Hardhat configuration snippet accesses several environment variables (`MAINNET_RPC_URL`, `GOERLI_RPC_URL`, `PRIVATE_KEY`, `COINMARKETCAP_API_KEY`, `ETHERSCAN_API_KEY`). If an AI agent is instructed to execute or integrate this code, and its execution environment contains these variables, the agent could read and potentially expose or misuse these sensitive credentials. While standard practice for local development, in an AI agent context, this poses a risk if the agent's environment is not properly sandboxed or if the agent is instructed to log/send these values. Advise users to ensure their AI agent execution environment is properly sandboxed and that sensitive environment variables are not exposed to untrusted code. If the agent is meant to handle such configurations, ensure secure handling and storage of credentials, possibly through a secrets management system rather than direct environment variables. For documentation, explicitly warn users about the security implications of exposing these variables to an agent. | LLM | SKILL.md:36 | |
| LOW | Unpinned dependencies in example code The `hardhat.config.js` snippet uses `require` statements for several Hardhat plugins without specifying exact versions (e.g., `require("@nomicfoundation/hardhat-toolbox");`). While this is a common pattern in `require` statements, if these dependencies were to be installed without specific version pinning in a `package.json` or similar dependency management file, it introduces a supply chain risk. A compromise in any of these packages could lead to malicious code being executed. When defining dependencies for actual projects, always pin exact versions or use strict version ranges (e.g., `^1.2.3` or `~1.2.3`) to mitigate supply chain risks. Regularly audit and update dependencies. For documentation, it is good practice to show versioned dependencies. | LLM | SKILL.md:13 | |
| LOW | Unpinned dependencies in example code The `hardhat.config.js` snippet uses `require` statements for several Hardhat plugins without specifying exact versions (e.g., `require("@nomicfoundation/hardhat-toolbox");`). While this is a common pattern in `require` statements, if these dependencies were to be installed without specific version pinning in a `package.json` or similar dependency management file, it introduces a supply chain risk. A compromise in any of these packages could lead to malicious code being executed. When defining dependencies for actual projects, always pin exact versions or use strict version ranges (e.g., `^1.2.3` or `~1.2.3`) to mitigate supply chain risks. Regularly audit and update dependencies. For documentation, it is good practice to show versioned dependencies. | LLM | SKILL.md:14 | |
| LOW | Unpinned dependencies in example code The `hardhat.config.js` snippet uses `require` statements for several Hardhat plugins without specifying exact versions (e.g., `require("@nomicfoundation/hardhat-toolbox");`). While this is a common pattern in `require` statements, if these dependencies were to be installed without specific version pinning in a `package.json` or similar dependency management file, it introduces a supply chain risk. A compromise in any of these packages could lead to malicious code being executed. When defining dependencies for actual projects, always pin exact versions or use strict version ranges (e.g., `^1.2.3` or `~1.2.3`) to mitigate supply chain risks. Regularly audit and update dependencies. For documentation, it is good practice to show versioned dependencies. | LLM | SKILL.md:15 | |
| LOW | Unpinned dependencies in example code The `hardhat.config.js` snippet uses `require` statements for several Hardhat plugins without specifying exact versions (e.g., `require("@nomicfoundation/hardhat-toolbox");`). While this is a common pattern in `require` statements, if these dependencies were to be installed without specific version pinning in a `package.json` or similar dependency management file, it introduces a supply chain risk. A compromise in any of these packages could lead to malicious code being executed. When defining dependencies for actual projects, always pin exact versions or use strict version ranges (e.g., `^1.2.3` or `~1.2.3`) to mitigate supply chain risks. Regularly audit and update dependencies. For documentation, it is good practice to show versioned dependencies. | LLM | SKILL.md:16 |
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