Shield Enterprise is a robust Python-based framework built for securing Large Language Model implementations in regulated industries. By integrating dynamic threat filtering, risk scoring, and GDPR-compliance measures, it ensures that sensitive applications in finance, healthcare, and more operate safely and transparently.
Shield Enterprise is a comprehensive, Python-based modular framework designed to fortify the security, compliance, and auditability of Large Language Model (LLM) applications within enterprise settings. This framework is particularly suitable for highly regulated industries such as finance, healthcare, legal, pharmaceuticals, and critical infrastructure, where data privacy and security are paramount.
Key Features
The Shield Enterprise framework offers a robust protection suite for LLMs, featuring:
- Dynamic Threat Filtering: Ensures that harmful or inappropriate content is filtered at runtime.
- Risk Scoring Mechanism: Assigns numeric values (0–100) to threats based on their content, with escalation protocols built-in.
- Comprehensive Audit Logging: Implements GDPR-compliant logs with options for data redaction and pseudonymization.
- Policy-Based Content Control: Integrates a flexible rule engine for content filtering according to specific regulations.
- Extensions for Compliance: Facilitates integration with GDPR/PII regulations, SIEM systems, and governance frameworks.
Modular Components
The core of the Shield Enterprise system comprises the following modules:
| Module | Description |
|---|---|
shield_core.py | Main execution layer serving as an I/O wrapper for GPT-based or customized LLMs. |
policy_engine.py | Rule-based filter with adjustable thresholds and domain-specific logic. |
risk_score.py | Computes threat values based on user input and instruction guidelines. |
audit_logger.py | Generates GDPR-compliant audit logs featuring redaction and pseudonymization. |
response_hooks.py | Manages output overrides and escalation triggers as well as integration stubs. |
siem_connector.py | Facilitates the transfer of logs/events to popular SIEM platforms such as Splunk and Elastic. |
Enterprise Modules
In addition to the core offerings, Shield Enterprise provides additional components that enhance functionality for large-scale deployments, including:
- Enterprise Configuration: Comprehensive configuration guidelines.
- Operational Strategy Overview: Detailed mapping of module interactions and operational tactics.
- Advanced Audit Design: Enhanced mechanisms for pseudonymization and audit processes.
- ISO-compliant Policy Extensions: Tailored policy filters to meet international standards.
- Data Tagging for Integration: Streamlined data pipelines for effective integration with enterprise systems.
- Control Logic and Routing: Intelligent scoring-based control logic for data routing and firewall management.
Use Cases
- Safeguarding AI-driven chat tools and copilots within organizations.
- Implementing GDPR and HIPAA compliant measures for healthcare LLM applications.
- Conducting financial content risk assessments for AI investment-related activities.
- Validating and controlling the redaction of legal documents.
- Ensuring pre-production safety for sensitive AI deployments.
Integration Capabilities
Shield Enterprise seamlessly integrates with major AI models and SIEM systems, including:
- OpenAI Models (ChatGPT, API)
- Gemini / PaLM 2 / Bard
- LLaMA / Meta AI
- Anthropic Claude
- Various SIEM solutions: Splunk, Sentinel, Graylog, Elastic.
Access and Licensing
The repository contains essential modules for the Shield Framework's core functionality, including system architecture, rule engine, and demo structure. However, advanced enterprise features such as GDPR compliance modules, risk response orchestration, and policy filtering are available upon request under a commercial license. For inquiries regarding enterprise access or evaluation, contact tom.wartenberg@web.de.
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