Black Duck Signal Enhances Application Security with Agentic AI

Black Duck unveiled Black Duck Signal, an agentic AI solution designed to protect software at the pace of AI-driven development. Leveraging Black Duck’s 20 years of software security expertise and proprietary knowledge, Signal uses LLM-powered analysis to autonomously identify and fix vulnerabilities in critical business applications.

As companies rapidly adopt AI coding assistants and agentic workflows, the need for application security solutions that can keep pace has never been greater. Black Duck Signal is purpose-built to work seamlessly with, and at the speed of, AI-native development, leveraging a collection of AI agents and MCP services to automatically find, prioritize, and fix vulnerabilities across source code, binaries, supply chain components, and running applications.

Unlike generic AI tools, Signal combines advanced, multi-model LLM technology with human-labeled application security intelligence from the Black Duck KnowledgeBase™ to deliver accurate, context-aware insights in real time—eliminating noise, hallucinations, and false positives. Its agentic architecture enables both developers and security teams to work more efficiently, integrating directly into popular AI coding assistants, IDEs, and other Black Duck application security products.

“AI is revolutionizing how software is built—and with Signal, Black Duck is redefining how you secure it by completely eliminating the noise of legacy tools,” said Jason Schmitt, CEO of Black Duck. “Developers are moving faster than ever, embracing AI to build and deliver software at unprecedented speed. Signal is the first programming language-agnostic security analysis product to combine the power of LLM-based code analysis with petabytes of human-labeled security data curated over our decades of analyzing real-world commercial and open-source software. Signal is designed to give developers the clarity, confidence, and control they need to innovate securely—without slowing down.”

Key Features and Benefits:

Real-time, incremental analysis of new, modified, and existing code, delivering accurate findings on real-time changes or complete applications
Direct integration with AI coding assistants (including Google Gemini, GitHub Copilot, Claude Code, Cursor, and more) for seamless security in code generation workflows
Role-based and task-based AI agents that extend developer and security team capabilities, automating complex workflows and specialized risk detection
Universal language support for modern and legacy programming languages, ensuring comprehensive coverage
Automated remediation with verified code fixes and library patching, reducing manual effort and accelerating secure development
Supply chain and license compliance analysis to manage open source and third-party risks
Noise reduction and prioritization through built-in exploitability analysis, helping teams focus on the most critical vulnerabilities
Business logic flaw vulnerability detection that goes beyond signature- and rule-based approaches to identify application-level zero-days