Layers of Trustfor AI build
Uncover hidden security gaps in AI and complex systems. Build resilience and operate securely in an ever-evolving threat landscape.
Five Phases.
Unlimited Protection.
Build - CoreLayer Radar
Scan system prompts, templates, and tool configurations for security vulnerabilities before deployment. AST-style prompt parsing detects injection surfaces and unsafe instructions.
Test - CoreLayer Striker
Adversarial testing that goes beyond functional QA. Identify jailbreak vectors and attack surfaces that remain invisible until production.
Validate - CoreLayer Vault
Continuous validation ensures your AI systems meet security baselines. Automated compliance checks against OWASP LLM Top 10 and MITRE ATLAS frameworks.
Runtime - CoreLayer Shield
Sub-10ms policy evaluation at inference time. Real-time enforcement of security policies with zero-day behavioral detection.
End User - CoreLayer SecureAgent
Protect end-user interactions with intelligent guardrails. Secure-by-default deployment templates for enterprise AI applications.
Three steps.
Complete AI security.
1$secureai scan --environment production23Discovering AI assets...4Scanning integrations: 100% (47/47)5Validating configurations...67✓ Environment scan complete
Deploy
anywhere.
Cloud-agnostic deployment with enterprise-grade security. On-premise, hybrid, or cloud-native - no architecture rewrite required.
Built for Enterprise
AI Security.
Meet Secure Agent,
Browser-Native AI Protection.
CoreLayer Security's Chrome extension now protects prompts at the user edge. Secure Agent detects and masks sensitive data before it reaches any LLM, helping teams reduce exposure from copy-paste leakage and unsafe prompt sharing.
Built for secure day-to-day AI usage across teams, with local-first inspection and zero data storage by default.
Explore Secure AgentWorks with any
LLM provider.
Model-agnostic. Cloud-agnostic. One control plane for your entire AI estate.
Full OWASP LLM
Top 10 Defense.
Every vulnerability addressed at multiple lifecycle phases. Full coverage of LLM01 through LLM10. MITRE ATLAS framework alignment.
Full Lifecycle Coverage
The only platform that instruments all five phases - Build, Test, Validate, Runtime, End User - with shared telemetry.
Multi-Model Support
Platform-agnostic coverage. Works with OpenAI, Anthropic, Mistral, and open-source models.
Cloud-Agnostic
AWS, Azure, GCP, or on-premise. Sub-10ms policy evaluation. No architecture rewrite required.
Policy-as-Code
YAML-based policy configuration gives teams full control. Customizable security architecture with no rigid lock-in.
Every stakeholder needs AI security.
From CISO to Developer. CoreLayer speaks to the security needs of every role in AI deployment.
For the CISO
Centralized AI asset inventory. Continuous compliance evidence. Lifecycle Risk Quantification. Transforms AI governance from documentation-driven to system-driven.
For the CTO
Programmable AI control plane. Sub-10ms inference-time policy evaluation. Policy-as-Code (YAML). Adversarial CI integration. No architecture rewrite.
For Security Teams
Lifecycle red team + blue team integration. Zero-day behavioral detection. Unified telemetry. Measurable, reportable AI security posture.
For the Developer
IDE integration and CI/CD plugins. Real-time policy feedback during development. Model validation and testing tools. Secure-by-default deployment templates.
# Governance, system-driveninventory: centralized_ai_assetscompliance: continuous_evidencerisk: lifecycle_quantificationgovernance: documentation → system-driven
Secure your
enterprise AI.
Full-lifecycle AI security from prompt to production. Unified platform. Shared intelligence. Enterprise governance.
Enterprise-ready deployment