Introducing Automated Authentication Issue Remediation: From Detection to Pull Request in Minutes

Practically every modern web application contains authentication and authorization logic, and it's one of the most sensitive areas of the code. A single misconfigured endpoint, missing authorization check, or improperly validated JWT can expose sensitive data to unauthorized users.

Today we're excited to introduce Automated Authentication Issue Remediation in API eNVy, a feature that finds authentication vulnerabilities, automatically generates fixes, and opens pull requests for your review.

Authentication Security Bottleneck

Let's consider a traditional SAST-driven application security workflow. A typical authentication security review may look like this:

1. Discovery (minutes to hours): Configure and run SAST tools, then manually audit API endpoints.
2. Triage (1-2 days): The security team reviews hundreds of potential findings, traces data flows, and determines which issues are truly exploitable.
3. Remediation (1-2 weeks): Developers receive tickets, context-switch from current work, research proper fixes, and implement changes.
4. Review (2-3 days): The security team reviews proposed fixes, requests changes, and waits for updates

For a medium-sized application with 200+ API endpoints, this process can take 2-3 weeks from the initial scan to deployed fixes. During that time, vulnerable endpoints remain in production, the security backlog grows, and developers lose context on the issues they need to fix.

How LLM-Powered Automated Remediation Works

Our new feature transforms authentication security from a weeks-long manual process into an automated workflow that takes minutes. Here's how it works.

Step 0: API Specification Extraction Powered by Static Analysis

Our API extraction engine analyzes your application’s source code to identify all available endpoints, along with their authentication requirements and contextual info, without the need for an OpenAPI specification or active crawling. 

Powered by a state-of-the-art static analysis engine, it supports multiple programming languages and most popular web frameworks.

Step 1: API-Aware LLM-Powered Vulnerability Scanning

Traditional SAST tools scan code line by line, looking for pattern matches. Our approach instead leverages your application's OpenAPI specification - the architectural blueprint that defines available endpoints, accepted parameters, and the security schemes meant to protect them. 

We use a Large Language Model (LLM) to analyze every API endpoint with full contextual awareness, evaluating whether each one is adequately protected.

This API-aware approach allows us to understand the context of potential vulnerabilities, not just detect superficial patterns.

Step 2: Intelligent Triaging and Remediation Planning

For each potential vulnerability discovered in the previous step, we perform a deep analysis to determine whether it’s truly exploitable. Using an LLM assisted by MCP tools, we examine endpoint inputs, authentication flows, and surrounding logic to assess exploitability and risk. The system then generates a concrete remediation plan tailored to the specific codebase.

Step 3: Automated Fix Generation and Pull Request Creation 

In this step, an LLM configured for context-aware code editing implements the planned remediation steps across the relevant files. The result is a set of multi-file, production-ready code changes that:

• Add missing authentication checks, 
• Fix weak password policies, 
• Hide exposed credentials, 
• Fix session invalidation issues, and more. 

Through our GitHub integration, these code changes are automatically converted to ready-for-review pull requests. Each PR includes a clear description of the vulnerability, affected endpoints, potential exploitation paths, and detailed remediation notes.

Your developers receive a complete pull request they can review, test, and merge, rather than a ticket asking them to figure out the fix themselves. And it all happens in minutes, not days or weeks. 

Conclusion

Automated authentication remediation represents a fundamental shift in how we approach application security. Instead of security teams acting as gatekeepers by identifying issues and passing them to developers, security tooling can now participate directly in the remediation process.

This feature doesn't eliminate the need for security expertise. Thorough code review remains essential, and security architecture decisions will always require human judgment. However, automated scanning and remediation of authentication issues enable organizations to address vulnerabilities far more quickly, allowing security engineers and developers to focus on the complex architectural challenges that truly demand human expertise.

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