Corgea - AI-powered code security platform with automated vulnerability fixing

Corgea: The AI-Native Application Security Platform

Modern development teams face a critical security paradox. As software delivery cycles accelerate, traditional application security tools struggle to keep pace—generating thousands of alerts, overwhelming developers with false positives, and fundamentally failing to detect the most dangerous vulnerabilities: those hidden in business logic. Static Application Security Testing (SAST) tools built on pattern matching can identify known vulnerability signatures, but they cannot comprehend the contextual intent behind code. Authentication bypasses, authorization flaws, and privilege escalation vulnerabilities slip through undetected because these tools lack the ability to understand what the code is actually trying to accomplish.

Corgea represents a paradigm shift in application security. As a 2024 Y Combinator-backed company (W24 batch), Corgea has built an AI-native AppSec platform that leverages Large Language Models to understand code context and business logic—the same way a human security expert would analyze code. This approach enables detection of vulnerabilities that traditional SAST tools simply cannot find, combined with AI-powered automatic remediation that generates context-aware fixes with 90%+ accuracy.

The platform has already earned recognition from industry analysts. Latio Tech founder James Berthoty describes Corgea as "groundbreaking stuff," while leading Silicon Valley companies including Airbyte and Metalware have integrated the platform into their security workflows. Sherif Nada,创始工程师 at Airbyte, calls it "magic wand" for the way it transforms security from a bottleneck into an automated process.

The investor backing further establishes credibility: YouTube co-founder Jawed Karim, SecurityScoreCard co-founder Sam Kassoumeh, former Google security engineer Ian Eldred Pudney, and Airbnb's former security lead Mahmoud Ali are among the notable backers. Perhaps most significantly, Stephen Singam, CISO at a Fortune 500 company, offers this endorsement: "In my career, rarely have I come across solutions that solve fundamental problems in security. Corgea has proven to me that automatically fixing code is possible."

Core Capabilities

Corgea's platform delivers comprehensive application security through eight integrated modules, each designed to address specific security challenges while maintaining developer productivity.

AI-Native SAST (BLAST)

The flagship capability, internally代号BLAST, represents a fundamental departure from traditional static analysis. Where conventional SAST tools rely on signature matching and predefined rules, Corgea's AI engine understands the semantic meaning of code—its business logic, data flows, and intended functionality. This enables detection of authentication flaws, authorization issues, and other business logic vulnerabilities that rule-based scanners consistently miss. The system supports over 20 programming languages and maintains a false positive rate under 5%, dramatically reducing the noise that overwhelms security teams.

SAST Auto-fix

Perhaps the most differentiated capability: automated vulnerability remediation. When Corgea detects a security issue, it doesn't just flag it—it generates a context-aware fix tailored to the specific codebase, framework, and security controls in use. The AI analyzes code patterns, understands the framework being used, and produces patches that integrate seamlessly with existing code. With fix accuracy exceeding 90%, developers can confidently apply recommendations or use them as starting points for manual refinement.

Dependency Scanning (SCA)

The platform automatically identifies known vulnerabilities in third-party dependencies across more than 25 programming languages and ecosystems. Each detected vulnerability includes CVE details, CVSS severity scores, and actionable remediation guidance including dependency upgrade recommendations.

Secrets Detection

Corgea scans repositories for hardcoded credentials, API keys, tokens, and sensitive information using a multi-layered approach combining pattern matching, entropy analysis, and AI-powered context understanding. The detector identifies AWS Keys, Azure Keys, OpenAI Keys, authentication credentials, database connection strings, private keys and certificates, OAuth tokens, personal access tokens, encryption keys, environment variables, internal endpoints, and payment credentials—preventing costly secret leaks to production.

Container & IaC Scanning

Security scanning extends beyond application code to infrastructure. Corgea analyzes Kubernetes configurations, Terraform definitions, Dockerfiles, CloudFormation templates, Azure ARM Templates, and Helm charts for misconfigurations and security weaknesses, ensuring infrastructure-as-code follows security best practices.

Auto-triage

AI-driven automatic prioritization dramatically reduces alert fatigue. The system analyzes each vulnerability considering the underlying infrastructure, existing security controls, and code context to distinguish genuine threats from false positives. This enables security teams to focus on actual risks rather than wading through thousands of low-priority alerts.

PolicyIQ

A natural language policy engine that allows security teams to define custom security rules without writing code. Users can express requirements in plain English—"require encryption for all database connections in production"—and PolicyIQ translates these into enforceable policies. This eliminates the need for custom rule writing while enabling organization-specific security requirements.

Corgea Agent

An autonomous AI agent that integrates directly into development workflows, automating routine security tasks including automated code review, security patch management, and vulnerability tracking. The agent operates within existing CI/CD pipelines to provide continuous security validation.

Use Cases

Corgea addresses security challenges across the entire software development lifecycle, with particular strength in scenarios where traditional tools fall short.

Detecting Business Logic Vulnerabilities

Traditional SAST tools excel at identifying known vulnerability patterns—SQL injection, cross-site scripting, command injection—but they fundamentally cannot reason about what code is supposed to do. Authentication bypasses, broken access control, and business logic flaws require understanding the intent behind code. Corgea's AI analyzer comprehends the business logic context, recognizing when authentication checks are missing, authorization boundaries are improperly enforced, or privilege escalation is possible. Organizations have discovered critical vulnerabilities that evaded years of traditional scanning.

Reducing Security Scan Noise

Development teams frequently abandon security tools because the signal-to-noise ratio is unworkable. A single codebase scan can generate thousands of alerts, most of which represent false positives or low-severity issues. Corgea's AI-driven auto-triage evaluates each finding against the actual infrastructure, security controls present, and code context. The system suppresses false positives automatically while highlighting genuine risks. With false positive rates under 5%, security teams can actually review and act upon findings rather than ignoring the noise.

Automating Vulnerability Remediation

Manual remediation of security vulnerabilities is time-consuming and error-prone. Developers must understand the vulnerability, research the correct fix, implement it correctly, and test thoroughly. Corgea automates this entire process by generating ready-to-apply patches that account for the specific codebase, framework, and security environment. Organizations report reducing remediation time from days to minutes, enabling developers to maintain velocity while improving security posture.

Preventing Secrets Leakage

Accidental commit of API keys, passwords, or certificates to version control represents one of the most common—and most critical—security incidents. Corgea continuously monitors for hardcoded secrets, detecting credentials before they reach production. The system identifies over 30 types of sensitive information including AWS keys, Azure credentials, database connection strings, and private keys, providing immediate alerts and remediation guidance.

Managing Dependency Vulnerabilities

Modern applications incorporate hundreds of open source dependencies, each potentially containing known vulnerabilities. Corgea scans dependency trees across 25+ languages, correlating findings with vulnerability databases to provide CVE details, severity scores using CVSS, and specific upgrade paths. Security teams gain visibility into their complete dependency attack surface with actionable remediation steps.

CI/CD Security Integration

Security scanning must occur where developers work—within their IDEs and CI/CD pipelines. Corgea provides native integrations with GitHub, GitLab, Azure DevOps, and BitBucket. Pull request scanning triggers automatically, providing immediate feedback before code merges. IDE extensions for VS Code and JetBrains IDEs bring security feedback directly into the development environment. CLI tools and MCP Server support enable custom automation workflows.

Getting Started

Onboarding to Corgea takes minutes, with the platform designed for immediate productivity without extensive configuration.

Account Creation: Visit corgea.com and sign up using GitHub or Google authentication. The registration process requires no credit card for the free tier, enabling immediate exploration.

Repository Connection: Navigate to the dashboard and connect your first repository. Corgea supports GitHub, GitLab, Azure DevOps, and BitBucket. The platform requests only read access necessary for security scanning; it never modifies your code without explicit permission.

Initial Scan Configuration: Choose scan scope—full repository or specific paths—and select security policies to apply. Options include SAST scanning, dependency vulnerability detection, secrets detection, and infrastructure-as-code scanning. Default configurations work out of the box, but teams can customize policies using PolicyIQ's natural language interface.

Pull Request Scanning: Configure automatic scanning for pull requests to catch vulnerabilities before they reach main branches. Set notification rules to alert relevant team members when issues are detected.

Integration Setup: For complete workflow coverage, install the IDE extension (VS Code or JetBrains), configure the CLI for local development, or set up the MCP Server for custom automation. These integrations bring security feedback directly into existing development workflows.

Remediation Workflow: When vulnerabilities are detected, review findings in the dashboard. Each issue includes severity, description, and an AI-generated fix. Apply fixes directly with one click, or copy the suggestion for manual modification before committing.

Technical Architecture

Understanding the underlying technology helps security decision-makers evaluate fit and integration requirements.

AI-Native SAST Architecture (BLAST)

Corgea's core innovation lies in its AI-native static analysis engine. Rather than relying exclusively on pattern matching and predefined vulnerability signatures, the system employs Large Language Models to understand code context semantically. When analyzing a function handling authentication, the model comprehends what the code is attempting to accomplish—verifying user identity, validating session tokens, enforcing access controls—rather than simply matching against known vulnerable patterns.

This architectural approach delivers several technical advantages. First, the system identifies business logic vulnerabilities that pattern-based tools cannot recognize. Second, contextual understanding enables intelligent false positive suppression—the model recognizes when code includes compensating controls that mitigate the theoretical risk. Third, the same contextual awareness enables generation of highly accurate fixes that maintain code functionality while addressing security concerns.

Context-Aware Detection

The detection engine analyzes multiple dimensions of code: business logic intent, data flow paths, control flow sequences, and the presence of security controls. This multi-faceted analysis produces findings that reflect actual risk rather than theoretical vulnerabilities. Each detected issue includes context explaining why the finding represents genuine risk in the specific code context.

Fix Generation Algorithm

When generating remediation suggestions, the AI considers the codebase's existing patterns, the framework in use, and surrounding security controls. The model has been trained on extensive datasets of secure code patterns and vulnerability fixes, enabling production of corrections that integrate seamlessly. Fix accuracy exceeds 90%, and each suggestion includes explanation of the vulnerability and the rationale behind the proposed fix.

Security Infrastructure

Corgea operates on AWS cloud infrastructure with enterprise-grade security controls. Data in transit uses TLS 1.3 encryption; data at rest employs AES-256 encryption. Daily backups with 30-day retention provide disaster recovery capability. The platform is currently preparing for SOC 2 compliance certification.

Code submitted for analysis is used solely for vulnerability detection purposes. The platform does not store code for training AI models, and all analysis occurs in isolated environments. Customers retain full ownership of their intellectual property.

Language and Tool Support

The platform supports over 25 programming languages including Java, JavaScript, TypeScript, Go, Ruby, Python, C#, C, C++, and PHP, along with infrastructure-as-code tools including Kubernetes, Terraform, Docker, CloudFormation, Azure ARM Templates, and Helm charts.

Integration Ecosystem

Comprehensive integrations enable security to operate within existing workflows: GitHub App for pull request scanning, GitLab integration, Azure DevOps support, BitBucket connectivity, IDE extensions for VS Code and JetBrains, CLI tools for local development, and MCP Server for custom automation. These integrations ensure security feedback reaches developers where they work.

Frequently Asked Questions