ai-incident-reporting-mcp

v1.1.2 suspicious
4.0
Medium Risk

AI Incident Reporting Compliance MCP. Unified classification + reporting-clock tracker across EU AI Act Article 73, DORA Article 19, NIS2 Article 23, GDPR Article 33, ISO/IEC 42001 clause 9, and UK AISI voluntary frontier-model reporting. One incident → all regime clocks in parallel. HMAC-signed post-incident attestation. By MEOK AI Labs.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks associated with network calls, shell execution, and obfuscation. However, the metadata risk score of 5 out of 10 due to unknown authorship and low repository activity raises concerns about potential supply-chain attacks.

  • Unknown author and low repository activity
  • Subscription link to external site
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external API interactions.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
  • Metadata: The package shows some red flags such as an unknown author and low repository activity, but there's no direct evidence of malice.

📦 Package Quality Overall: Low (4.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 2 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (10040 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

  • 5 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 17 commits in CSOAI-ORG/ai-incident-reporting-mcp
  • Two distinct contributors found

🔬 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

Email domain looks legitimate: meok.ai>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ 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 ai-incident-reporting-mcp 
Create a web-based incident reporting system using Python and the 'ai-incident-reporting-mcp' package. This system will allow users to log incidents related to AI compliance across multiple regulatory regimes including the EU AI Act, DORA, NIS2, GDPR, ISO/IEC 42001, and UK AISI. The application should provide a user-friendly interface where users can input details of an incident, such as date, type, severity, and description. Upon submission, the system should automatically classify the incident according to relevant compliance requirements and initiate the appropriate reporting clocks for each applicable regulation.

Key Features:
- User authentication and authorization to ensure only authorized personnel can report incidents.
- A form for incident reporting that includes fields for incident details, impact assessment, and corrective actions.
- Real-time classification of incidents based on the content provided, aligning with the standards set by 'ai-incident-reporting-mcp'.
- Automated tracking of reporting deadlines for each regulatory requirement.
- An HMAC-signed post-incident attestation feature that allows for secure verification of reported incidents.
- A dashboard that displays an overview of all reported incidents, their status, and upcoming deadlines.

Utilization of 'ai-incident-reporting-mcp':
- Integrate the package to handle the classification and reporting of incidents according to the specified regulations.
- Use the package's features to track the reporting clocks for each incident, ensuring timely compliance.
- Implement HMAC-signed attestations as per the package documentation to secure the integrity of reported incidents.