How to evaluate ADLC security solutions: A buyer's checklist

Agentic development lifecycle (ADLC) security addresses both vulnerabilities in AI-generated code and risks created by coding agents that can install packages, modify CI configurations, execute commands, and access repositories or external tools. Organizations evaluating security products should first map their own agents, languages, repositories, pull-request volume, permissions, and required integrations, then jointly define criteria with AppSec and platform engineering teams. Vendor assessments should use representative internal code and test multi-layer logic flaws such as broken access control, reachable dependency and container vulnerabilities, validated secrets, malicious packages, and policies governing agent actions. Rather than relying on broad accuracy claims, teams should require evidence including source-to-sink data flows, call paths, written classification reasoning, and repeatable results from scans of the same commit. Effective tools should fit developer workflows by delivering actionable findings and fixes directly to coding agents, supporting fast incremental pull-request scans, and blocking only high-confidence issues. A short proof of concept across several representative repositories, supported by established ground truth and safe test cases, can help organizations assess coverage, reliability, remediation quality, governance, and operational impact before adoption.

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.