LLM Security & Governance
Ensure your large language models (LLMs) are secure, compliant, and responsibly managed with Syiert Corporation’s governance framework. Protect your organization from adversarial attacks, data leaks, and operational risks.
Why LLM Security & Governance Matters
LLMs introduce new risks for enterprises, especially when deployed in production or customer-facing applications. Key challenges include:
- Prompt injection and adversarial manipulations
- Unauthorized data access or leakage from training datasets
- Compliance violations with regulatory frameworks (FedRAMP, CMMC, NIST)
- Operational risks from misaligned or unsafe model outputs
- Lack of traceability for decisions made by the model
Our Approach — Safe, Compliant, & Traceable
- Data Handling & Provenance: Ensure datasets are approved, access-controlled, encrypted, and logged for audit readiness.
- Prompt & Output Validation: Adversarial prompt testing, sanitization, and filtering to prevent misuse or malicious instructions.
- Access & Deployment Controls: Fine-grained IAM, least privilege deployment, private endpoints, and model versioning.
- Monitoring & Anomaly Detection: Continuous logging, inference monitoring, drift detection, and explainability metrics.
- Governance & Compliance: Model cards, evidence packages, audit-ready reports, and regulatory alignment (FedRAMP, CMMC, NIST AI RMF).
- Incident Response & Remediation: Playbooks for unsafe outputs, rollback procedures, and incident reporting for governance assurance.
Deliverables
Governance Framework
Policies, oversight dashboards, and audit-ready documentation for LLM deployments.
Security Assessments
Adversarial testing, prompt-injection red-team exercises, and compliance gap analysis.
Monitoring & Alerts
Continuous monitoring of outputs, anomaly detection, and drift alerts for proactive risk management.
Remediation & Playbooks
Incident response procedures, rollback plans, and compliance-ready evidence packages.
Secure Your LLM Deployments
Schedule a consultation to implement governance and risk controls for large language models.
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