Comparison
LyraShield AI vs Horizon3.ai
How LyraShield AI compares to Horizon3.ai for autonomous infra pentest. Approach, evidence model, coverage framework, and deployment model differences.
Last reviewed:
Core approach
| Aspect | LyraShield AI | Horizon3 NodeZero |
|---|---|---|
| Primary focus | Release assurance for AI-built apps | Continuous, autonomous production pentesting and exposure validation |
| Scanning approach | Agentic engine with coverage framework and evidence states; AI-pattern focus | Autonomous AI that pivots through networks, chaining weaknesses and safely exploiting them |
| Finding lifecycle | Detected → independently verified → retest-confirmed or inconclusive | Attack path → proven exploit with impact → prioritized → fix → Quick Verify retest |
| Control framework | Vibe Security 50 (43 code/URL review + 7 evidence-required) | No published control framework; threat-informed, attack-path prioritization |
| Environment focus | App-layer + AI-generated code; MCP/agent configs | Internal + external + cloud + Kubernetes + Active Directory + web apps + identity |
| Deployment model | Hosted + CLI + MCP + GitHub Action | Internal tests via Docker/OVA; external from Horizon3 cloud; no agents |
Capability comparison
| Capability | LyraShield AI | Horizon3 NodeZero |
|---|---|---|
| Agentic / AI-driven pentest | Yes (app-layer) | Yes (cross-environment) |
| Independent exploit validation | Yes (verified state) | Yes (proven attack paths with impact) |
| SCA (dependency scanning) | Yes (engine) | Not a primary focus |
| Secret scanning | Yes (engine + GitHub Action) | Detects exposed credentials/secret-related weaknesses |
| Evidence states (4-state lifecycle) | Yes | Findings carry exploit proof; no explicit multi-state lifecycle |
| Deterministic retest | Yes | Quick Verify re-test after fix |
| Coverage receipts | Yes (per-control) | No (attack-path + impact diagrams instead) |
| Assurance reports (immutable) | Yes | Executive/auditor reporting; CTEM-aligned evidence |
| MCP server integration | Yes (inside AI coding agents) | Yes (MCP server to accelerate remediation / find-fix-verify) |
| Approval-gated fix execution | Yes (PR blocked until patch bound to approval) | No (remediation guidance + verify) |
| Production-safe execution | App-layer scope | Yes (zero-downtime claim across production tests) |
| AI-generated-code focus | Built for AI-built apps | Not specific to AI-generated code |
Deployment and pricing
| Aspect | LyraShield AI | Horizon3 NodeZero |
|---|---|---|
| Deployment | Hosted + CLI + MCP + GitHub Action | SaaS; internal Docker/OVA + external cloud; AWS Marketplace + other clouds |
| Pricing | Open beta; pricing announced as it matures | Published on AWS Marketplace (per 12-mo, 500 assets): Core $25,000; Pro $32,500; Elite $42,500. NodeZero Flex one-time (1,000 assets) $15,000. 30-day free trial available; enterprise by quote |
| Compliance posture | Assurance-record orientation for release sign-off | Trusted by governments, Fortune 10, healthcare; FedRAMP High variant for federal |
When to use which
Use LyraShield AI when
- Your app is AI-built and you need AI-specific pattern coverage and a release-gate assurance record
- You need immutable assurance reports with coverage receipts for compliance or client handoff
- You want fixes approval-gated so a PR cannot execute until a server-generated patch is bound to an exact approval
- You want security checks inside your AI coding agent via MCP
- You need SCA + secrets + agentic pentest in one release-assurance loop
Use Horizon3 NodeZero when
- You want autonomous, production-safe pentesting across internal/external/cloud/Kubernetes/AD/identity, not just app-layer
- Your priority is continuous attack-path validation and proving production resilience
- You need to chain weaknesses across environments the way an attacker does, with impact diagrams
- You want a published, asset-based pricing model and a 30-day free trial
- You operate in federal/high-security environments needing FedRAMP-aligned validation
NodeZero proves production resilience across the environment; LyraShield AI gates AI-built-app releases. Read our comparison methodology and try the free browser-local tools at lyrashieldai.com.
Methodology and scope
Every claim on this page is drawn from publicly documented capabilities at the date above. Read how LyraShield tests, records evidence, and reports coverage for the assurance model behind the comparison, and treat anything not stated there as out of scope.
For the long-form version of this comparison, including the evidence model and where each tool fits a release gate, read LyraShield AI vs Horizon3.ai.
Frequently asked questions
- Does LyraShield replace Horizon3 NodeZero?
- No. NodeZero is an autonomous, production-safe pentest that chains weaknesses across internal, external, cloud, Kubernetes, Active Directory, and identity, with attack-path diagrams and Quick Verify retests. LyraShield in open beta is app-layer release assurance for AI-built apps with evidence states, coverage receipts, and approval-gated fixes.
- Can I use Horizon3 NodeZero and LyraShield together?
- Yes. Use NodeZero to prove production resilience across your environment and meet CTEM goals, and use LyraShield to gate releases of AI-built apps with an immutable assurance record. NodeZero offers Docker and OVA deploy for internal tests and publishes Core $25,000, Pro $32,500, Elite $42,500 per 500 assets per year plus a 30-day trial; LyraShield is live open beta.
- When should I choose Horizon3 NodeZero over LyraShield?
- Choose NodeZero when you need continuous exposure validation across networks, identities, and cloud, not just one app, with FedRAMP High options for federal environments. Its strength is proving what an attacker can actually achieve across environments. Choose LyraShield when your bottleneck is AI-specific patterns, MCP configs, and a ship or no-ship decision.