Scan without the guesswork: AI SAST and LLM Scan Orchestration
Blog post from Harness
Harness argues that modern vulnerability management must accelerate because attackers can exploit newly disclosed flaws within hours while organizations often take weeks to remediate and deploy fixes. Citing industry reports and Project Glasswing testing, it highlights both the increased discovery capability of LLM-based security tools and their challenges, including false positives, inconsistent results, latency, and cost. The company’s launch combines deterministic AI-assisted static application security testing, orchestration for LLM scanners, function-level reachability analysis, and agents designed to prioritize exploitable findings, generate and validate fixes, and prepare human-reviewed pull requests within governed CI/CD pipelines. Its Zero-Day Agent is intended to identify affected artifacts and pipelines immediately after disclosures, while virtual patching through a web application and API protection service can shield production during permanent remediation. The overall approach positions integrated scanning, triage, remediation, deployment, and temporary protection as a way to reduce response times and maintain oversight through existing policy, approval, and audit controls.
No tracked trend matches for this post yet.
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.