LogSentinelAI is an AI-powered log analysis tool that processes sensitive log data and integrates with external LLM providers and Elasticsearch. We take security seriously and appreciate the community's help in identifying and responsibly disclosing security vulnerabilities.

We actively maintain and provide security updates for the following versions:

LogSentinelAI processes potentially sensitive log data that may contain:

• IP addresses and network information
• User agents and system identifiers
• Application error messages
• Authentication attempts and failures

The tool integrates with external services that require security considerations:

• LLM Providers: OpenAI API, Ollama, vLLM
• Elasticsearch: Log storage and indexing
• SSH Connections: Remote log access
• GeoIP Services: MaxMind GeoLite2 database

• API keys and credentials must be properly secured
• SSH keys should be used instead of passwords when possible
• Elasticsearch credentials should follow least-privilege principles

Please report any security vulnerabilities you discover, including but not limited to:

• Authentication bypass: Unauthorized access to log data or system functions
• Injection vulnerabilities: SQL injection, command injection, or prompt injection
• Data exposure: Unintended disclosure of sensitive log data or credentials
• Privilege escalation: Unauthorized elevation of user permissions
• Denial of Service: Vulnerabilities that could crash or significantly slow the system
• Dependency vulnerabilities: Security issues in third-party libraries
• Configuration flaws: Insecure default configurations or settings

🔒 Private Disclosure (Preferred)

For security vulnerabilities, please DO NOT create public GitHub issues. Instead, use one of these secure channels:

1. Email: Send a detailed report to [email protected]

   • Use the subject line: [SECURITY] LogSentinelAI Vulnerability Report
   • Include "CONFIDENTIAL" in the email body

2. GitHub Security Advisories: Use GitHub's private vulnerability reporting

   • Go to the Security tab in our repository
   • Click "Report a vulnerability"
   • Fill out the advisory form

Please provide the following information in your security report:

1. Vulnerability Type: Brief description of the vulnerability category
2. Impact Assessment: Potential security impact and affected components
3. Affected Versions: Which versions of LogSentinelAI are affected
4. Reproduction Steps: Clear steps to reproduce the vulnerability
5. Proof of Concept: Code, commands, or screenshots demonstrating the issue
6. Suggested Fix: If you have ideas for remediation (optional)
7. Discovery Timeline: When you discovered the vulnerability

Subject: [SECURITY] LogSentinelAI Vulnerability Report - [Brief Description]

CONFIDENTIAL SECURITY REPORT

Vulnerability Type: [e.g., Authentication Bypass]
Severity: [Critical/High/Medium/Low]
Affected Versions: [e.g., 0.2.0 - 0.2.3]

Description:
[Detailed description of the vulnerability]

Impact:
[What an attacker could achieve by exploiting this]

Reproduction Steps:
1. [Step 1]
2. [Step 2]
3. [Step 3]

Proof of Concept:
[Code, commands, or screenshots]

Suggested Fix:
[Your recommendations, if any]

Additional Notes:
[Any other relevant information]

• Acknowledgment: We will acknowledge receipt of your report within 48 hours
• Initial Assessment: We will provide an initial assessment within 5 business days
• Regular Updates: We will provide regular updates on investigation progress
• Resolution Timeline: We aim to resolve critical vulnerabilities within 30 days

1. Day 0: Vulnerability reported
2. Day 1-2: Acknowledgment sent
3. Day 3-7: Initial assessment and triage
4. Day 8-30: Investigation, fix development, and testing
5. Day 31: Coordinated disclosure (if fix is ready)
6. Day 90: Public disclosure (maximum timeline)

# Use environment variables for sensitive data
export OPENAI_API_KEY="your-api-key-here"

# Secure file permissions for configuration
chmod 600 config

# Use SSH keys instead of passwords
ssh-keygen -t ed25519 -f ~/.ssh/logsentinel_key

• Use HTTPS/TLS for all external API connections
• Implement proper firewall rules for Elasticsearch
• Consider VPN or SSH tunneling for remote log access

• Follow least-privilege principles for system access
• Regularly rotate API keys and credentials
• Monitor access logs for unusual activity

• All user inputs must be properly validated and sanitized
• Use parameterized queries for database operations
• Implement proper error handling without information disclosure
• Regular dependency updates and security scanning

• Security-focused code reviews for authentication/authorization code
• Validation of all external data sources
• Review of credential handling and storage
• Assessment of logging practices to avoid sensitive data exposure

• Input Validation: Comprehensive validation of log data and user inputs
• Credential Management: Support for environment variables and secure storage
• Access Control: SSH key-based authentication for remote access
• Data Sanitization: Automatic removal of sensitive patterns in outputs
• Secure Defaults: Security-focused default configurations

• Enhanced Input Sanitization: Improved detection and handling of malicious log entries
• Audit Logging: Comprehensive audit trail for all analysis activities
• Role-Based Access: More granular access control mechanisms
• Data Encryption: Encryption at rest for sensitive configuration data

We regularly monitor and update our dependencies for security vulnerabilities:

• Python Security: Monitor Python CVE database
• PyPI Dependencies: Use tools like safety for vulnerability scanning
• LLM Providers: Follow security advisories from OpenAI, Ollama, etc.

• Dependency Scanning: Automated security scanning in CI/CD
• Static Analysis: Code security analysis tools
• Container Security: Docker image vulnerability scanning

We appreciate the security research community and will acknowledge security researchers who report vulnerabilities responsibly:

• Hall of Fame: Public recognition for significant security contributions
• Coordinated Disclosure: Proper attribution in security advisories
• Communication: Direct communication channel for ongoing security research

• Researchers who follow responsible disclosure will be publicly acknowledged
• Recognition will be provided in release notes and security advisories
• We support coordinated disclosure timelines that balance security and transparency

• Primary Contact: [email protected]
• PGP Key: Available upon request for encrypted communication
• Response Language: English, Korean

For critical security issues requiring immediate attention:

• Email: [email protected] with subject [URGENT SECURITY]
• Expected Response: Within 24 hours

We support responsible security research and will not pursue legal action against researchers who:

• Follow our responsible disclosure guidelines
• Do not access, modify, or delete user data
• Do not intentionally degrade service performance
• Do not perform testing against production systems without permission

This security policy applies to:

• LogSentinelAI source code and releases
• Official deployment guides and configurations
• Integration examples and documentation

This policy does not cover:

• Third-party services (LLM providers, Elasticsearch instances)
• User-deployed instances or configurations
• Issues in dependencies that we don't control

Last Updated: January 2025
Version: 1.0
Next Review: July 2025

Thank you for helping keep LogSentinelAI and our community safe! 🔒