SentriAI：大语言模型安全评估与威胁情报平台

SentriAI is an open-source platform dedicated to large language model (LLM) security assessment, integrating threat intelligence, behavior analysis, MITRE ATLAS framework mapping, and compliance monitoring. It addresses emerging LLM security threats (prompt injection, jailbreaking, data leaks, biased outputs) and provides comprehensive tools for researchers and security practitioners. Key features include multi-dimensional assessment, continuous monitoring, and compatibility with existing security systems.

As LLMs are widely adopted across industries, their security issues are becoming increasingly prominent. These include prompt injection attacks, data leakage risks, model jailbreaking, and biased outputs. Traditional security tools are often ineffective for LLMs due to their open-ended input/output and uncertainty, creating a need for specialized platforms like SentriAI.

SentriAI has four core modules:

1. Threat Intelligence Integration: Tracks LLM-specific threats (prompt injection, indirect injection, jailbreaking, model extraction) to keep users updated on latest attack techniques and defenses.
2. Behavior Analysis Engine: Monitors runtime behavior (input/output anomalies, response patterns) by establishing normal baselines to detect deviations.
3. MITRE ATLAS Mapping: Aligns detected threats with MITRE ATLAS framework, enabling standardized threat description, understanding tactical goals, referencing mitigation measures, and integration with other tools.
4. Compliance Monitoring: Assesses LLM deployments against regulations (e.g., EU AI Act) in data privacy, transparency, interpretability, and fairness.

SentriAI uses a multi-dimensional assessment approach covering:

• Input Layer: Detects malicious prompts, adversarial inputs, and harmful input patterns.
• Model Layer: Evaluates training data security, model weight protection, and inference safety.
• Output Layer: Monitors sensitive info leaks, harmful content, and biased outputs.
• Interaction Layer: Analyzes multi-round dialogue risks (context manipulation, long-session attacks). It emphasizes continuous evaluation since LLM behavior changes with context, requiring ongoing monitoring and strategy updates.

SentriAI applies to multiple scenarios:

1. Enterprise AI Deployment: Pre-deployment security assessment via attack simulation to identify vulnerabilities.
2. Third-Party Model Audit: Validates vendor security claims and identifies risks for third-party LLM services.
3. Research & Education: Helps researchers reproduce attacks, develop defenses, and verify effectiveness.
4. Red Team Testing: Supports security teams with threat intelligence and attack libraries for effective testing.

SentriAI plans to expand in:

• Multimodal Security Assessment: Covering image/audio/video inputs for multi-modal LLMs.
• Automated Red Team Testing: Developing intelligent attack generation to simulate complex real-world scenarios.
• Industry-Specific Templates: Customized assessments for sectors like healthcare, finance, and law.
• Real-Time Protection: Evolving from assessment to active blocking/alerts when attacks are detected.

SentriAI fills a gap in LLM security assessment, addressing unique challenges posed by LLMs' openness and uncertainty. For organizations, using such tools is essential for responsible LLM deployment, balancing innovation and safety. As AI evolves, SentriAI serves as an early explorer, providing a foundation for future AI security infrastructure.