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Security audit

Pytest Test Master

Security checks for vulnerabilities and agentic risk

Overview

This is a coherent pytest guidance CLI that mainly prints static Chinese-language educational content, with no hidden execution, persistence, or data collection found.

Install only if a Chinese-language pytest reference is useful to you. Use a virtual environment, pin Python dependencies, and review any copied GitHub Actions or Codecov examples before adding them to a repository, especially in CI jobs with secrets or write permissions.

A.I.G

Vulnerability Patterns
  • Insecure DependenciesIntroduces malicious components through unsafe dependency sources
  • 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)

T08 · Insecure Dependencies

Warning
Location
README.md:22
Finding

Unpinned Python Dependencies in Installation Instructions

Content
View full analysis
Remediation
View remediation

T08 · Insecure Dependencies

Warning
Location
pytest_master.py:1374
Finding

Generated CI Example Executes a Mutable Third-Party GitHub Action

Content
View full analysis
Remediation
View remediation

SkillSpector

Vulnerability Patterns
  • 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
  • Excessive AgencyUnrestricted Tool Access, Autonomous Decision Making, Scope Creep
Findings (8)

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
94% confidence
Finding

The primary skill description is written as a Chinese-only instruction/context statement, and the README provides all usage guidance in Chinese without indicating that other languages are supported. Under the policy, forcing a specific language without user opt-in is a natural-language policy violation unless the locale restriction is explicit and justified.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
97% confidence
Finding

This markdown file presents all user-facing instructions, examples, and command explanations exclusively in Chinese. Under the language/locale policy rule, forcing a specific language without user opt-in is a natural-language policy violation unless the locale constraint is explicitly justified, which is not provided here.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium
Category
Not specified by scanner
Confidence
96% confidence
Finding

The module docstring describes the skill entirely in Chinese and presents it as the core library for the skill, with no indication that users may choose another language. Under the policy, forcing a specific language without user opt-in is a natural-language locale violation unless clearly documented as region-specific and justified.

Content

No source excerpt is available for this finding.

External Transmission

Medium
Category
Data Exfiltration
Confidence
60% confidence
Finding

Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.

Content

Scanner excerpt · pytest_master.py (reported line 504)May include surrounding context.

python
result = fetch_user(1)
    assert result["name"] == "Alice"
    mock_get.assert_called_once_with(
        "https://api.example.com/users/1"
    )

# 方式二：patch 上下文管理器（更直观）

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
93% confidence
Finding

The description is written entirely in Chinese, which indicates a language-specific experience in user-facing metadata. There is no accompanying indication that users may choose another language or that the skill is intentionally limited to a Chinese-speaking context.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
95% confidence
Finding

This code file contains user-facing natural-language strings almost entirely in Chinese, including the module description and CLI help text. Under the policy rule for language/locale, this is a violation because the skill does not present any opt-in, fallback, or alternative language choice.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
98% confidence
Finding

The script's comments and user-facing echo messages are written in Chinese throughout, which imposes a specific language on users without any visible option to select another locale. This matches the policy category for language/locale constraints expressed in natural-language content.

Content

No source excerpt is available for this finding.

Natural-Language Policy Violations

Low
Category
Not specified by scanner
Confidence
92% confidence
Finding

This is a code file, so SQP-3 applies to natural-language content in docstrings and comments. The module docstring and multiple test/doc comments use Chinese exclusively, which imposes a specific language without any visible opt-in or justification in the file.

Content

No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.