Tag: LLM security
Are LLMs Equally Good (or Bad) at Building Secure Software?
Pieter Danhieux | | agentic AI, AI agents, AI code security, AI coding assistants, AI coding costs, AI coding models, AI Development, AI model benchmarking, AI-generated code, application security, Developer Security, framework security, LLM security, OWASP Top 10, SAST, secure code generation, secure coding, software development, software security, token costsAn SCW study finds a large variance in how frontier and budget LLMs perform across different frameworks, and explains the striking cost variance ...
The MLSecOps Era: Why DevOps Teams Must Care about Prompt SecurityÂ
Alex Vakulov | | AI attack surface, AI chaos testing, AI Governance, AI supply chain risk, autonomous agent security., CI/CD pipeline security, CodeShield, DevOps AI, ISO 42001, LlamaFirewall, LLM security, MLSecOps, model drift, NIST AI RMF, prompt injection, prompt validation, PromptGuard, PromptOps, RBAC for AI, red team AI, runtime monitoring, secure AI pipelinesAI-driven software delivery introduces new risks, especially prompt manipulation within CI/CD workflows. This article details the emerging fields of PromptOps and MLSecOps and offers practical strategies for securing prompts, models, and pipelines ...
JFrog Adds Ability to Track Usage of AI Coding Tools
Mike Vizard | | AI API management, AI code auditing, AI coding tools, AI compliance tracking, AI Governance, AI in DevOps, AI model inventory, AI risk mitigation, AI-generated code, application security, code risk detection, devsecops, Large Language Models, LLM security, MLOps, SCA, secure coding practices, Shadow AI detection, software composition analysis, software provenance, Software Supply Chain Security, software vulnerabilities, source code scanningJFrog introduces AI-Generated Code Detection and Shadow AI Detection tools to identify AI-created code, track model usage, and enhance DevSecOps governance across software supply chains ...
