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.
The Shield Enterprise framework offers a robust protection suite for LLMs, featuring:
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. |
In addition to the core offerings, Shield Enterprise provides additional components that enhance functionality for large-scale deployments, including:
Shield Enterprise seamlessly integrates with major AI models and SIEM systems, including:
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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