Security audit

Newsletter Growth Hacker

Security checks for vulnerabilities and agentic risk

Overview

This is a local newsletter marketing helper with no evidence of hidden access, persistence, network use, or destructive behavior.

Installers should understand this is a Chinese-language, offline newsletter marketing toolkit with simple rule-based estimates. It does not appear to request sensitive access or run background behavior, but users should treat its benchmarks and predictions as advisory rather than authoritative.

A.I.G

Vulnerability Patterns

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
Unauthorized Access and Privilege EscalationObtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns

MCP Tool PoisoningHidden Instructions, Unicode Deception, Parameter Description Injection
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 (14)

Tp4

High

Category: MCP Tool Poisoning
Confidence: 91% confidence
Finding: The description partially matches the code: it does perform email marketing data analysis, reporting, trend comparison, and growth projection/tracking. However, several prominently declared capabilities are not implemented in this chunk, especially subscriber acquisition strategy generation and A/B test subject line generation. The code’s main purpose is a metrics/reporting engine with rule-based insights, not a full newsletter growth-hacking tool. There are no suspicious undeclared permissions or resource accesses, but the declared functionality materially overstates the implemented capabilities.
Content: No source excerpt is available for this finding.

Tp4

High

Category: MCP Tool Poisoning
Confidence: 94% confidence
Finding: The description overstates the skill’s scope. The supplied code is focused on two concrete functions: analyzing newsletter content for basic structural issues (subject line, CTA, length, readability, paragraphing) and generating subject lines plus A/B test plans. It also includes static open-rate benchmarks by industry. However, it does not contain functionality for acquiring subscribers, producing subscriber growth strategies, forecasting growth, or tracking trends over time. There is no ingestion of campaign datasets, no statistical analysis pipeline beyond simple heuristic checks, and no predictive modeling. So while part of the declared purpose is accurate (content optimization and A/B subject-line generation), the overall description materially exceeds the actual implemented behavior.
Content: No source excerpt is available for this finding.

Tp4

High

Category: MCP Tool Poisoning
Confidence: 95% confidence
Finding: 声明描述覆盖多个核心能力模块，但提供的代码块只包含 subscriber acquisition 相关逻辑：内置策略列表、按投入筛选策略、用固定转化率做简化增长预测、以及生成通用执行计划。虽然“订阅者获取策略”和“增长预测”与声明部分一致，但“内容优化”“A/B 测试主题行生成”“数据分析”在代码中没有对应实现。因此描述高估了实际能力，属于明显的描述-行为不一致。
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 88% confidence
Finding: This markdown file presents all user-facing content in a single language, which can constitute a language/locale policy violation when no user opt-in or documented regional justification is provided. The file contains no indication that Chinese is optional, configurable, or required for a specific region-specific use case.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 91% confidence
Finding: The entire skill file is written in Chinese and presents all templates, labels, and guidance exclusively in that language, with no indication that users may choose another language or that the skill is intended only for a Chinese-language audience. This creates a natural-language locale constraint that is not documented as optional or region-specific.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 88% confidence
Finding: This code file contains user-facing natural-language content in Chinese, including the module description and later CLI output, but it does not indicate that Chinese output is optional or that the tool is region-specific. Under the policy rule, forcing a specific language without user opt-in can be a locale-policy violation.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 94% confidence
Finding: The command-line interface prints headings, labels, and insights in Chinese only, which forces a specific language for end users. There is no mechanism in the file for selecting another language and no justification that the tool is intended solely for a Chinese-speaking context.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 95% confidence
Finding: The module description and user-facing documentation in the file header are presented only in Chinese, which can impose a language constraint on users without opt-in. The policy for this audit flags language or locale restrictions when the skill does not offer a choice or justify the constraint.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 92% confidence
Finding: The CLI prints, prompts, and explanatory strings are all in Chinese, and the file does not indicate that Chinese is optional or required for a justified regional use case. This creates a natural-language policy issue because the skill effectively enforces one language for interaction.
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 file contains user-facing text, comments, and prompts entirely in Chinese, including the main description and interactive menu greeting. Because the skill presents a fixed language for interaction with no opt-in, fallback, or documented region-specific justification, it violates the language/locale policy criteria.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Medium

Category: Not specified by scanner
Confidence: 95% confidence
Finding: The class docstring is in Chinese, and the rest of the user-facing strings and comments throughout the script are also presented only in Chinese despite the file title and top-level description being in English. This indicates the skill effectively imposes a single language on users without offering a language choice or documenting a justified locale restriction.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 89% confidence
Finding: The manifest description and main documentation are primarily written in Chinese, with no indication that users can choose another language or locale. This can violate a language/locale policy when a skill imposes one language by default rather than offering opt-in or alternatives.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 89% confidence
Finding: This markdown file contains user-facing guidance exclusively in Chinese, and there is no indication that the skill is region-specific or that users can opt into a preferred language. Under the natural-language policy rule, forcing a specific language without opt-in can be a policy concern.
Content: No source excerpt is available for this finding.

Natural-Language Policy Violations

Low

Category: Not specified by scanner
Confidence: 76% confidence
Finding: This file contains natural-language comments in Chinese such as 'Python 依赖', '核心功能无需外部依赖', and '代码质量' without any indication that language choice is optional. Under the policy rule for language/locale, forcing a specific language without user opt-in can be a violation, even in comments or documentation-like text within code-related files.
Content: No source excerpt is available for this finding.

Static analysis

No suspicious patterns detected.