AI-native and traditional. One platform.
Most vendors bolt AI onto a legacy scanner — or sell you a chatbot without the foundational coverage your auditors need. Safeguard does both, on a single architecture, with one policy engine and one workflow surface.
Two halves. Shared everything.
Reasoning & the agent era
- Griffin AI (reachability + fix)
- MCP Server governance
- Guardrails (prompt-injection defense)
- AI-BOM
- Auto-Fix
- Zero-day eval harness
Foundational AppSec & supply chain
- SCA
- SBOM Studio
- IaC Security
- DAST
- Secure Containers
- Secret Detection
- TPRM
- Scanner Suite
Five layers. Single architecture.
Why findings, fix PRs, and evidence stay coherent across every product.
1. Unified ingest
Repos, registries, IaC, runtime, third-party SBOMs, MCP servers, AI agents — one normalized graph of every asset and dependency.
2. Griffin AI reasoning
Reachability, fix synthesis, zero-day eval, and AI-agent intent inference run continuously over the graph.
3. One policy engine
Policy-as-code across SCA, IaC, DAST, AI agents, and TPRM. Same gate logic in PRs, deploys, runtime, and procurement.
4. Single workflow surface
One PR check, one dashboard, one ticketing integration. Findings, fix PRs, evidence and exceptions all live together.
5. Evidence store
Continuous SBOM, VEX, scan logs, policy violations and attestations — exportable as framework-mapped audit packs.
Deploy where your data lives.
SaaS
Multi-tenant. Up and running in under an hour.
Private cloud
Dedicated VPC in your AWS / GCP / Azure account.
Sovereign / air-gapped
Self-hosted with full model weights — runs disconnected.