animal-mediakit

v1.18.65 suspicious
5.0
Medium Risk

CLI 工具：通过 animal-gateway 调用 AI 图像/视频生成，以及本地图像处理能力

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits some unusual characteristics such as missing repository information and a short author name, which raises concerns about its origin and authenticity. While the direct risk indicators like shell execution and credential harvesting are low, the network and metadata risks warrant further scrutiny.

  • Missing repository information
  • Short author name
  • Network risk due to external URL calls
Per-check LLM notes
  • Network: The package makes network calls to external URLs, which could be for legitimate purposes like fetching models or service data, but further investigation is needed to confirm the legitimacy of these endpoints.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The base64 decoding is likely used for handling image data, which is a common practice and not inherently suspicious.
  • Credentials: No credential harvesting patterns were detected in the provided code snippet.
  • Metadata: The missing repository and short author name suggest potential risks.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4482 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 86 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • _id}" try: resp = httpx.get(url, timeout=10) if resp.status_code == 200:
  • ) try: resp = httpx.get( f"{GATEWAY_BASE_URL}/v1/models", he
  • ny]]: try: resp = httpx.post( f"{GATEWAY_BASE_URL}/sso/cli/switch-team",
  • parameters, } resp = httpx.post( f"{GATEWAY_BASE_URL}/dashscope/api/v1/services/aigc
  • f url: img_resp = httpx.get(url, timeout=60) img_resp.raise_for_status()
  • sync"] = "enable" resp = httpx.post( f"{GATEWAY_BASE_URL}/dashscope/api/v1/services/aigc
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • 64: images.append(base64.b64decode(b64)) return images def generate_video_veo( prompt
  • 64: images.append(base64.b64decode(b64)) elif item.get("url"): img_resp = h
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with animal-mediakit 
Create a fun and interactive mini-application called 'Animal Photo Studio' using the 'animal-mediakit' Python package. This app will allow users to upload their photos and apply various AI-generated enhancements and effects specifically tailored for animals. Users can also choose to generate new images of animals based on textual descriptions or other input media. Here’s a detailed step-by-step guide on how to build this application:

1. **Setup Environment**: Ensure you have Python installed along with the 'animal-mediakit' package.
2. **User Interface**: Develop a simple yet user-friendly interface where users can upload their photos. Consider using Flask or Django for backend development and HTML/CSS/JavaScript for the frontend.
3. **Photo Upload**: Implement functionality to accept image uploads from users. Ensure these images are processed safely and securely.
4. **AI Enhancements**: Utilize the 'animal-mediakit' package to apply AI-generated enhancements to the uploaded images. This could include things like improving the quality, generating realistic animal faces, or adding special effects that enhance the animal presence.
5. **Text-to-Image Generation**: Allow users to describe an animal scene or provide another image as reference, and use 'animal-mediakit' to generate a new image based on this input.
6. **Save & Share**: Provide options for users to save their enhanced images locally or share them directly to social media platforms.
7. **Feedback Mechanism**: Incorporate a feedback system where users can rate the quality of the AI-generated enhancements, helping improve the service over time.

Suggested Features:
- Integration with popular social media sharing buttons for direct posting.
- A gallery section showcasing examples of previous transformations.
- User accounts for saving preferences and viewing past edits.
- Option to download original and edited versions side-by-side for comparison.

Remember, the goal is to leverage the capabilities of 'animal-mediakit' to create a unique and engaging experience for users interested in enhancing or generating animal-related imagery.

💬 Discussion Feed

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