Back to browse
GitHub Repository

A team of Claude Code sub-agents that enforce security across the full SDLC, from ASVS requirements and threat modelling to SAST triage, IaC review, compliance attestation and release sign-off. Drop into any project. No security team required.

8 starsJavaScript

Secure SDLC Agents for Claude and Cursor (MCP)

by kirumachi·Apr 7, 2026·1 point·0 comments

AI Analysis

●●SolidNiche GemSolve My Problem

Eight specialist agents catch what Claude Code misses, but it's prompts not actual code analysis.

Strengths
  • Eight specialized agents cover full SDLC from requirements to release gate
  • MCP integration works directly in Cursor, Windsurf, and Claude Code
  • Concrete artifacts: GitHub Actions, git hooks, and document templates included
Weaknesses
  • Agents are structured prompts, not actual static analysis or code scanning
  • Security tooling space already crowded with Snyk, Semgrep, GitHub Advanced Security
Category
Target Audience

Developers using AI coding tools who need security guardrails

Similar To

Snyk · Semgrep · GitHub Advanced Security

Post Description

Hey HN,

I have been using Claude Code and Cursor lately and as we all know, they write code incredibly fast but a few times i have noticed they can introduce the same security flaws. For example, you ask the LLM to build a file upload feature, you will get working code in minutes, but it would almost always miss magic-byte validation or leaves you vulnerable to SVG XSS. The LLM optimizes for code that compiles not code that is secure.

To fix this for my own workflow, I made a set of 8 security-focused AI agents (AppSec, GRC, Cloud/Platform, etc) that you can drop into any MCP-compatible tool (Cursor, Windsurf) or use with Claude Code.

To clarify, the goal here is not to say that LLM/AI replaces AppSec or the Secure Software Development Cycle, instead the goal is to provide a series of structured prompts and concrete security artifacts (like STRIDE based threat models and ASVS mapped functional requirements) for developers who are already using AI to write code. The aim is to force the LLM to pause and sort of put on a security hat during specific phases of the SDLC.

What It Actually Is

It is an MIT licenced repo containing the agent prompts, document templates and an MCP server. You can install via Claude marketplace or globally via npm, which gives you a CLI to scaffold git hooks, CodeQL CI Gates and the MCP config. Also included are 3 full walkthroughs in the repo showing how the agents catch things.

I am an Application Security Engineer, and I am really curious to get feedback and critique. Please try it out without any signups using the URL. I will be around to answer any questions

Similar Projects

Security●●Solid

Agentsec – Security scanner for AI agent installations (MCP, OpenClaw)

Bundles CI-friendly scanners that target agent-specific risks: 17 patterned secret detectors, prompt-injection and instruction‑malware heuristics, tool/SSRF and MCP auth checks, plus SARIF/JSON outputs for integration. Findings map to the OWASP Top 10 for Agentic Applications (2026) and it adds 'harden' profiles to apply safer defaults to OpenClaw/MCP installs — practical, focused ops tooling rather than a generic secret-finder.

Niche GemSolve My Problem
debu_sinha_1
233mo ago