From Theory to Practice: Code Generation Using LLMs for CAPEC and CWE Frameworks
From Theory to Practice: Code Generation Using LLMs for CAPEC and CWE Frameworks explores A novel dataset of vulnerable code snippets linked to CAPEC and CWE, generated by LLMs, to train automated vulnerability detection systems.. Commercial viability score: 7/10 in Security Vulnerability Detection.
Use This Via API or MCP
Use the canonical paper page as a proof artifact
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisLLM-Enabled Open-Source Systems in the Wild: An Empirical Study of Vulnerabilities in GitHub Security AdvisoriesViability: 5.0
- Builds On ThisBroken by Default: A Formal Verification Study of Security Vulnerabilities in AI-Generated CodeViability: 4.0
- Prior WorkVulnScout-C: A Lightweight Transformer for C Code Vulnerability DetectionViability: 7.0
- Prior WorkDetecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented ScanningViability: 7.0
- Prior WorkBridging Code Property Graphs and Language Models for Program Analysis