Security audit

CSV Tools

Security checks for vulnerabilities and agentic risk

Overview

This is a coherent local CSV tool, but its file-writing behavior is broader and less controlled than its own safety documentation claims.

Review this before installing if you work in directories with important files. Use explicit output paths in a scratch directory, avoid running it on untrusted CSVs that will later be opened in spreadsheet software, and expect that existing files can be overwritten despite the documentation saying confirmation is required.

A.I.G

Vulnerability Patterns

Insecure Skill Coding PracticesFinds exploitable flaws such as hardcoded secrets or command injection
Skill Instruction HijackingAlters the agent's session goals or safety constraints when the skill loads
Agent Memory PoisoningWrites attacker-controlled rules into memory that affect later sessions
Remote Payload Retrieval and ExecutionFetches external code whose behavior can change after review
Embedded Malicious CodeShips malicious scripts inside the skill and executes them locally

Findings (2)

T09 · Insecure Skill Coding Practices

Warning

Location: scripts/csv_tools.py:37
Finding: Unrestricted Output Paths Permit Silent File Overwrite
Content: View full analysis
Remediation: View remediation

T09 · Insecure Skill Coding Practices

Warning

Location: scripts/csv_tools.py:37
Finding: Untrusted CSV Values Can Trigger Spreadsheet Formula Injection
Content: View full analysis
Remediation: View remediation

SkillSpector

Vulnerability Patterns

MCP Least PrivilegeUnderdeclared Capability, Wildcard Permission, Missing Permission Declaration
Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code

Findings (5)

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 86% confidence
Finding: The README’s user-facing instructions and safety information are presented entirely in Chinese, which effectively forces a specific language for users. The policy allows language constraints only when users are given a choice or when the locale limitation is clearly documented and justified, neither of which appears here.
Content: No source excerpt is available for this finding.

Undeclared Tool Scope

Medium

Category: MCP Least Privilege
Confidence: 92% confidence
Finding: The skill advertises file-writing behavior in its documented capabilities, but it does not declare an explicit tool/permission scope such as permissions or allowed-tools. That creates a policy gap: an agent may invoke the skill without a machine-readable restriction on write access, increasing the chance of unintended file creation or overwrite if the runtime grants broader filesystem privileges than the human-readable text implies.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 96% confidence
Finding: This Python skill’s top-level docstring, CLI help text, and many user-facing messages are written in Chinese, which effectively imposes a specific language on users. The file does not provide any documented language/locale selection, opt-in, or justification for being region-specific.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 85% confidence
Finding: The heading uses only Chinese for the changelog label ("更新日志"), which indicates a fixed language presentation without offering an alternative or documenting a locale-specific scope. Under the policy rule, forced language/locale choices in natural-language content can be a violation when no opt-in or justification is provided.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 83% confidence
Finding: The natural-language comment is written only in Chinese ('纯Python标准库，无外部依赖'), which imposes a specific language context without offering any user choice or alternate locale. This can conflict with language/locale policy expectations when skills should not force a language absent explicit opt-in or justification.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.