LLM ShieldBox™
Autonomous AI/LLM Governance & Security Testing Platform
LLM ShieldBox™ continuously tests enterprise AI systems for vulnerabilities, governance gaps, and compliance exposures using automated scenarios based on OWASP Top-10 for LLMs and J.S. Held’s proprietary 13-category LLM testing framework.
Why Security Matters
Enterprises adopting generative AI use ShieldBox™ to ensure safe, accountable, and defensible operations.
LLM ShieldBox™ is an automated AI security and governance testing platform that evaluates the safety, integrity, and compliance posture of enterprise LLM deployments.
It continuously scans for vulnerabilities—including prompt injection, data exfiltration, model theft, training data poisoning, insecure plugin designs, excessive agent autonomy, and misconfigured access controls.
The platform also assesses the governance frameworks surrounding AI deployments, benchmarking them against global standards such as NIST AI RMF, ISO 42001, EU AI Act, and internal governance policies.
Core Capabilities
Defensive operations for the Generative AI era.
1. Continuous LLM Vulnerability Scanning
Automated red-teaming to identify weaknesses like prompt injection and data leakage in real-time.
2. AI Governance Evaluation
Assess alignment with internal policies and external standards (NIST, ISO, EU AI Act).
3. Data Lineage & Privacy Testing
Traces data flow to ensure sensitive information remains private and compliant.
4. Adversarial Sandbox Testing
Simulates sophisticated attacks in a safe environment to test system resilience.
5. Compliance Mapping & Evidence Generation
Automatically generates reports and evidence for audits and regulatory reviews.