ZeroPath vs. GuardRails

ZeroPath is the AI-native SAST that finds vulnerabilities traditional tools miss. We built it because security shouldn't overwhelm developers with noise. Unlike pattern-matching tools that flood you with false positives, ZeroPath understands your code's intent and business logic. We find authentication bypasses, IDORs, broken auth, race conditions, and business logic flaws that actually get exploited and missed by traditional SAST tools. We auto-generate patches and pull requests that match your project's style. 75% fewer false positives, 200k+ scans run per month, and ~120 hours saved per team per week. Over 750 organizations use ZeroPath as their new AI-native SAST. Our research has uncovered critical vulnerabilities in widely-used projects like curl, sudo, OpenSSL, and Better Auth (CVE-2025-61928). These are the kinds of issues off-the-shelf scanners and manual reviews miss, especially in third-party dependencies. ZeroPath is an all-in-solution for your AppSec teams: 1. AI-powered SAST 2. Software Composition Analysis with reachability analysis 3. Secrets detection and validation 4. Infrastructure as Code scanning 5. Automated PR reviews 6. Automated patch generation and more...

Contemporary development teams are equipped to discover, rectify, and avert vulnerabilities across various domains, including source code, open-source libraries, secret management, and cloud configurations. They are also capable of detecting and addressing security weaknesses within their applications. The implementation of continuous security scanning accelerates the deployment of features while minimizing cycle durations. Our sophisticated system significantly reduces false positives, ensuring that you are only alerted to pertinent security concerns. Regularly scanning software across all product lines enhances overall security. GuardRails seamlessly integrates with popular Version Control Systems like GitLab and GitHub, streamlining security processes. It intelligently selects the most appropriate security engines based on the programming languages detected in a repository. Each security rule is meticulously designed to assess whether it presents a significant security threat, which effectively decreases unnecessary alerts. Additionally, a proactive system has been created to identify and minimize false positives, continuously evolving to enhance its accuracy. This commitment to precision not only fosters a more secure development environment but also boosts the confidence of the teams involved.