Bright STAR
Business Profile
Core Value Proposition
Bright STAR provides autonomous, AI-powered application security testing and remediation that auto-detects vulnerabilities, auto-remediates them, and validates fixes throughout the SDLC.
Target Customer
Developers, DevSecOps and Application Security (AppSec) teams in enterprises building and delivering software, APIs, and AI-driven applications.
Key Differentiator
Zero false positives; automated remediation; dynamic validation; closed-loop, AI-powered testing that auto-generates tests and fixes and integrates directly into CI/CD workflows; supports both human-written and AI-generated code.
Implementation Timeline
Value can be realized quickly after integrating Bright STAR into CI/CD pipelines and developer workflows; customers report rapid remediation and substantial time savings (up to ~95% in some cases) and high automatic remediation rates.
Pain Points
- 1Security testing and remediation slow software delivery due to manual effort and complex tooling
- 2High false positives and noise from traditional SAST/DAST approaches
- 3Difficulty securing and testing AI-generated code and maintaining security within modern CI/CD workflows
Key Features
- 1AI-generated security tests that match code and context
- 2Automated remediation that delivers ready-to-merge code fixes
- 3Dynamic validation to confirm fixes actually work end-to-end
- 4CI/CD and developer workflow integration with tools like Jira and code-generation utilities
- 5Broad coverage for web apps, APIs, and AI/LLM-based applications
Target Customer Industries
Decision Makers
- 1Head of Application Security
- 2Chief Technology Officer
- 3Security Team Lead
- 4AppSec Leader
Client Results
- 198% improvement in vulnerabilities remediation
- 210x more vulnerabilities fixed within the development process
- 3Less than 3% false positives
- 4Automatic remediation rates of approximately 85% (as cited for Bright STAR deployments)
- 5Over 95% time savings in finding and fixing vulnerabilities
Competitive Advantages
- 1Automated, scalable security that minimizes false positives
- 2End-to-end automation: test generation, remediation, and dynamic validation
- 3Developer-centric and CI/CD-friendly, reducing friction in software delivery
- 4Broad coverage including web apps, APIs, and AI/LLM vulnerabilities
- 5Zero-noise security testing with continuous updates and AI-driven insights
Key Benefits
Case Studies & Success Stories
SentinelOne case study – empowering developers with Bright Security’s DAST
Head of Application Security stated Bright Security’s DAST empowers developers and helps embed security as part of development, driving innovation and efficiency.
SXI, Inc. case study – seamless CI/CD integration and actionable insights
Chief Technology Officer highlighted seamless CI/CD integration, advanced scanning, and actionable insights that help catch vulnerabilities early and reduce remediation costs.
ProCircular case study – efficiency gains in scanning
Security team lead reported significant time savings, noting reductions in wall clock hours and man hours spent on preliminary scans by about 70%.
Prominent Midwestern Bank – runtime scanning efficiency and support
AppSec Leader described improved runtime scanning efficiency and highly responsive customer support.
Additional Product Information
Product Description
Bright STAR is an AI-powered Autonomous Application Security Testing and Remediation platform that automates security testing, remediation, and validation across web apps, APIs, and AI-driven (LLM) applications, integrated into CI/CD workflows.
Target Market
Enterprises delivering software at scale, needing rapid, secure development across web apps, APIs, and AI-enabled software; developers and AppSec/DevSecOps teams.
Unique Value Proposition
Autonomous, AI-driven, closed-loop AppSec that automatically generates tests, remediates vulnerabilities, and dynamically validates fixes end-to-end within modern development workflows, reducing noise and accelerating delivery.
Technical Requirements
Integration into CI/CD pipelines; compatibility with Jira and code-generation tools (e.g., GitHub Copilot); supports developer-centric workflows
Pricing Model
Not disclosed in the provided content
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