Blog

Shift-Left isn’t dead—it’s just leveling up with AI. By blending AI with Shift-Left, developers get real-time security insights, fixing flaws faster while AI handles the heavy lifting.

Runtime reachability truly transforms the way we manage vulnerabilities in open-source and third-party dependencies. By identifying which flagged vulnerabilities are actually exploitable in production, this approach helps us reduce false positives.

This blog explores why large language models (LLMs) hallucinate—generating plausible but false information—and highlights strategies like RAG, fine-tuning, and prompt engineering to improve AI reliability in critical fields.

Retrieval-Augmented Generation (RAG) combines generative AI with external knowledge retrieval, enabling more accurate and contextually rich outputs. It is ideal for applications needing real-time updates or domain-specific data but faces challenges in latency and data security. Advances like Graph-RAG and tools like LangChain are shaping its future use in diverse fields.

Unlock the full potential of AI with fine-tuning—where pre-trained models are customized to excel in tasks like code generation, application security, and more. By conquering challenges with smart techniques like PEFT and quantization, fine-tuning transforms AI into a powerful, domain-specific problem solver.

This blog explores how application security evolved from manual methods to AI-powered defenses, using techniques like RAG, AI agents, and predictive modeling to create adaptive, real-time threat protection for the future.

Organizations are struggling to keep up with application vulnerability remediation due to the complexity of modern development practices. This blog explores the shortcomings of current remediation efforts and offers insight into new strategies that can help streamline the process.

This blog explores the shift from package-level to function-level reachability analysis in software security, highlighting how deeper scanning improves accuracy and efficiency in detecting vulnerabilities while addressing the remaining challenges.