🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has a moderate risk score due to low maintainer activity and poor metadata quality, though it does not exhibit any direct malicious behavior such as network calls, shell execution, or obfuscation.

Metadata risk at 4 out of 10
No direct evidence of malicious behavior

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires them.
Shell: No shell execution patterns detected, indicating no immediate risk from command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting the package does not engage in secret or credential theft activities.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising some suspicion but not definitive evidence of malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with Xingyvan-Auto-Commenter

构建一个名为 'AutoGrader' 的小型应用程序，该应用使用Python的 'Xingyvan-Auto-Commenter' 包来自动批改和评论.docx格式的学生作业。这个应用程序应该能够读取.docx文件中的学生作业内容，并根据预设的标准或算法自动生成反馈和评分。此外，它还应该具备以下功能：

1. 支持用户上传多个.docx文件，以批量处理学生的作业。
2. 提供一个简单的界面，让用户选择或输入批改标准（例如：拼写错误扣分、语法正确性等）。
3. 自动生成评语，包括对每个作业的优点和需要改进的地方。
4. 将生成的评语和分数直接添加回原始的.docx文件中，以便老师可以直接打印或通过电子邮件发送给学生。
5. 具备保存和恢复进度的功能，以防意外关闭程序导致数据丢失。
6. 可以将所有批改过的作业及评语导出为一个新的.docx文件或者CSV格式的报告，方便统计分析。

为了实现这些功能，你将主要利用 'Xingyvan-Auto-Commenter' 包提供的核心能力来处理.docx文档并生成评语。具体来说，你需要导入此包，并调用其相关方法来读取和修改.docx文件的内容。同时，还需要结合其他Python库（如openpyxl用于CSV操作，tkinter用于创建图形用户界面）来完善整个应用程序的功能。