cso-vibecheck

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pico2-swd-riscv

pico2-swd-riscv SWD debug probe for RP2350 RISC-V Hazard3 cores. One Pico2 debugs another via two GPIO wires. 0. VIBE CODE WARNING WRITTEN BY HUMAN About 80% of the code is vibe coded; The readme is almost completely generated except the whole vibe-code-warning section. I spent many nights with...

synaptic-sentinel

SYNAPTIC Sentinel The vibe-coding security sentinel. An Apache-2.0 agentic security toolkit for projects where most of the code is written by AI. Five deterministic scouts catch the syntactic problems; a Brain Layer BYOK Anthropic decides what really matters and how to fix it — all inside the IDE...

aigate

aigate Secret hygiene for AI-generated code. Catches hardcoded credentials in prompts, tool inputs, generated code, and existing files. Quick start pip install aigate && aigate setup-all That's it. This installs a background proxy redact mode, a PostToolUse hook for file scanning, and registers t...

kern

kern: rootless container runtime and sandbox with no daemon. Runs agent tool calls and LLM-generated code in kernel-enforced containers. A real, kernel-enforced container in a few milliseconds, out of one static binary with no daemon. MCP support for Claude Code, Cursor, Claude Desktop and LM...

What Is the Difference between Me and You? Benchmarking the Quality Gap between Human-Written and AI-Generated Code

AI coding assistants are becoming co-authors of production software, yet their evaluation centers on functional correctness, leaving open whether their code differs from human code in the quality dimensions dominating lifecycle cost. We compare human-written and AI-generated code at scale: 787,56...

Wiz Red Agent Finds Its Way Into Snowflake’s Internal Jira Through a Flaw in a GitHub Copilot–Assisted PR

Wiz Red Agent independently discovered and exploited a GitHub Actions injection missed by GitHub’s Advanced Security, validated access to sensitive data in Snowflake’s internal Jira, and assessed the blast radius—all without human intervention, five days after the flaw became live...

Security Vulnerability Patterns in AI-Generated Code: A Cross-Model Comparative Study

LLM-based coding tools enable non-expert users to generate routine automation scripts that may enter enterprise workflows without meaningful security review. This study examines that risk directly. Code was collected from ChatGPT, Microsoft Copilot, and Google Gemini using identical prompts acros...

SQLi

SQL Injection: An Elite Bug Bounty Hunter's Field Manual SQL...

AI Code in the Wild: Measuring Security Risks and Ecosystem Shifts of AI-Generated Code in Modern Software

Large language models LLMs for code generation are becoming integral to modern software development, but their real-world prevalence and security impact remain poorly understood. We present the first large-scale empirical study of AI-generated code AIGCode in the wild. We build a high-precision...

Vibe Coding Is the New Open Source—in the Worst Way Possible

As developers increasingly lean on AI-generated code to build out their software—as they have with open source in the past—they risk introducing critical security failures along the way...

EvilAI Operators Use AI-Generated Code and Fake Apps for Far-Reaching Attacks

Combining AI-generated code and social engineering, EvilAI operators are executing a rapidly expanding campaign, disguising their malware as legitimate applications to bypass security, steal credentials, and persistently compromise organizations worldwide...

Secure Vibe Coding: The Complete New Guide

DALL-E for coders? That's the promise behind vibe coding, a term describing the use of natural language to create software. While this ushers in a new era of AI-generated code, it introduces "silent killer" vulnerabilities: exploitable flaws that evade traditional security tools despite perfect...