Harness Your Mechs: What to build & what to buy when you bring AI into AppSec

Endor Labs’ “Harness Your Mechs” campaign promotes a resource kit on scaling application security for agentic software development lifecycles, arguing that security agents that perform well in a single repository can become costly and difficult to verify across thousands of repositories and pull requests. Citing surveys and internal research, the company says agentic AI initiatives often falter because of growing token costs, unclear value, false positives, and limited security correctness, while precomputed code context and reachability evidence can reduce token use and improve consistency. Its playbook describes four maturity levels spanning governed AI code generation, purpose-built security agents, custom organizational security skills, and orchestrated multi-agent systems, with separate tracks for securing AI-generated code and using AI for AppSec tasks. The company recommends that teams build policies, workflows, risk models, and organization-specific expertise while buying or adopting a maintained foundation for code context, verification, evidence, and scalable analysis. Endor Labs positions its AURI platform, including code context graphs, AI SAST, reachability-based dependency analysis, and coding-agent governance, as that underlying foundation, and offers related research, benchmarks, an ROI calculator, educational materials, and events to help teams assess and advance their security programs.

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