Comparison
LyraShield AI vs ZeroPath
How LyraShield AI compares to ZeroPath for AI-native SAST and auto-fix. Evidence states, deterministic retest, coverage framework, and deployment model.
Last reviewed:
Core approach
| Aspect | LyraShield AI | ZeroPath |
|---|---|---|
| Primary focus | Evidence-backed release assurance for AI-built apps | AI-native SAST plus SCA, secrets, IaC, and DAST validation in one platform |
| Scanning approach | Agentic engine, coverage framework, evidence states | LLMs combined with static analysis, taint tracking, and AI validation |
| Finding lifecycle | Detected → independently verified → retest-confirmed or inconclusive | Found → AI-validated for exploitability → fix PR generated |
| Control framework | Vibe Security 50 (43 code/URL review + 7 evidence-required) | No published control framework; convention-deviation and auth-predicate analysis |
| Fix model | Approval-gated; PR execution blocked until a server-generated patch is bound to exact approval | Fix PRs opened for one-click merge with natural-language refinement |
| AI-generated code focus | Built for AI-built apps; scans agent rules, MCP configs, AI patterns | Agent installer with stop hooks; scans uncommitted diffs at end of AI agent turns |
Capability comparison
| Capability | LyraShield AI | ZeroPath |
|---|---|---|
| Static analysis (SAST) | Via engine | Yes (AI-native flagship; business logic and auth flaws) |
| Custom rules | Not a primary feature | Natural-language policy engine |
| SCA (dependency scanning) | Yes | Yes (reachability-aware, exploitability fusion) |
| Secret scanning | Yes (engine + GitHub Action) | Yes (700+ detectors, rotation guidance PRs) |
| Agentic pentest | Yes (core) | Runtime validation of SAST findings against a live app (not open-ended pentest) |
| Evidence states | Yes (4 states) | Exploitation-setup metadata per finding |
| Deterministic retest | Yes | Auto re-scan verification after fix |
| Coverage receipts | Yes (per-control) | No |
| Assurance reports | Yes (immutable snapshots) | Compliance and audit reports; GRC sync |
| Approval-gated fixes | Yes (server-generated patch bound to approval) | One-click merge fix PRs; no formal approval gate |
| MCP server integration | Yes (23+ agents) | Yes (open-source MCP server for Claude, Cursor, Windsurf) |
| AI-BOM / AI inventory | Not a primary feature | Yes (17 AI component kinds, CycloneDX AI-BOM) |
| Open-source CLI | CLI is npm-published | Yes (zeropath-cli with SARIF output) |
Deployment and pricing
| Aspect | LyraShield AI | ZeroPath |
|---|---|---|
| Deployment | Hosted + CLI + MCP + GitHub Action | SaaS, on-prem (Enterprise), CLI, VS Code plugin, GitHub/GitLab/Bitbucket/Azure DevOps, MCP server, Claude Code plugin |
| Pricing | Open beta; pricing announced as it matures | Team $1,000/mo + $60/developer; Enterprise custom; usage-based option available |
| Languages | Language-agnostic | 15+ for SAST (Python, JS/TS, Java, C#, Go, Ruby, PHP, Rust, Swift, Kotlin, and more) |
When to use which
Use LyraShield AI when
- You need evidence-backed assurance with coverage receipts for release decisions
- Your app is AI-built and you want security checks inside your AI coding agent via MCP
- You need immutable assurance reports for compliance or client handoff
- You want fixes gated behind explicit approval before a patch is applied
- You want agentic pentest as a core capability, not runtime validation of scanner findings
Use ZeroPath when
- You want a unified AI-native SAST, SCA, secrets, and IaC platform that replaces multiple scanners
- You need deep business-logic and authorization-flaw detection with AI validation
- You want AI-BOM and AI-component inventory for AI-era supply-chain visibility
- You want fix PRs delivered with natural-language refinement and one-click merge
- You need broad multi-language SAST (15+) with taint and data-flow analysis
See the evidence approach in action.
Read the methodology or try the free browser-local tools at lyrashieldai.com.
Sources: ZeroPath homepage, ZeroPath SAST, ZeroPath pricing, ZeroPath runtime validation, ZeroPath AI inventory, ZeroPath docs, ZeroPath MCP server (GitHub), BusinessWire.
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 ZeroPath.
Frequently asked questions
- Does LyraShield replace ZeroPath?
- No. ZeroPath is a unified AI-native SAST plus SCA, secrets, IaC, and DAST-style runtime validation with taint tracking, natural-language policy, CycloneDX AI-BOM across 17 component kinds, and an open-source MCP server and CLI. LyraShield in open beta focuses on agentic pentest as core with SCA, secrets, evidence states, and approval-gated fixes.
- Can I use ZeroPath and LyraShield together?
- Yes. ZeroPath can serve as your broad AI-native scanner replacing multiple detectors, with Team pricing at $1,000 per month plus $60 per developer and an open-source CLI with SARIF. Add LyraShield for the release assurance loop that requires approval before fixes merge and produces an immutable snapshot. Both support MCP, so they can run inside AI coding agents.
- When should I choose ZeroPath over LyraShield?
- Choose ZeroPath when you need business-logic and authorization flaw detection, AI-component inventory, one-click fix PRs with natural-language refinement, and broad language coverage with 700+ secret detectors. Its strength is consolidating SAST, SCA, secrets, and runtime validation. Choose LyraShield when release proof and approval gates are the priority.