LyraShield AI vs Corgea

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Core approach

Capability comparison

Deployment and pricing

When to use which

Use LyraShield AI when

• You need evidence-backed assurance with checksum-bound reports for release decisions
• Your app is AI-built and you want security checks inside your AI coding agent via MCP
• You want recorded fix proposals before your team applies a patch
• You need coverage receipts mapping to a control framework
• You want detected candidates and retest outcomes clearly distinguished

Use Corgea when

• You want one platform spanning SAST, SCA, secrets, IaC, containers and AI pentest
• You need business-logic and auth-flaw detection with review-ready fix PRs
• You want pre-code security design reviews of PRD/architecture documents
• You need a fast, compliance-oriented AI pentest with SOC 2 / ISO 27001 evidence
• You want published, per-developer pricing with a free tier

See the evidence approach in action

Read the methodology or try the free browser-local tools at lyrashieldai.com.

Sources: Corgea homepage, Corgea pricing, Corgea AI SAST, Corgea AI pentest, Corgea secrets scanning, Corgea dependency scanning, Corgea docs, Corgea on GitHub Marketplace.

Where Corgea is genuinely strong

Corgea is built around the idea that a scanner should adapt to your codebase. Its Auto-Discovery and Learning announcement describes how it studies the code before scanning: it detects frameworks, languages and architecture, identifies existing security controls such as auth decorators and ORM usage and generates project-specific false-positive and fix policies. Its Learning feature turns developer feedback into approved policies over time, grouped by project, CWE and language.

Its AI Pentesting announcement describes a multi-agent architecture where coordinator agents assign specialised sub-agents such as an auth discovery agent or an API exploration agent. The same page says the agents validate exploitability during the test, confirming a finding can be triggered, capturing evidence and explaining business impact. The same page says the platform supports continuous retesting after remediation.

Its Security Design Reviews announcement describes catching design-level threats at the PRD stage, including the example of a vendor payout API design that lacked an authorization check linking the authenticated user to the vendor they were paying. The security page describes issuing pull requests with fixes for engineering approval.

Sources

• Corgea introduction
• Corgea Auto-Discovery and Learning
• Corgea AI Pentesting
• Corgea Security Design Reviews
• Corgea BLAST documentation
• Corgea security documentation

Methodology and scope

This comparison describes published capabilities, not an independent test of either product. Client workflow availability and commercial terms can change. Read how LyraShield tests, records evidence and reports coverage for its assurance model and verify vendor details before a purchasing decision.