Alternatives
Products that do what HoundDog.ai – Ultra-Fast Code Scanner for Data Privacy does
Hi HN, I'm one of the creators of HoundDog.ai (https://github.com/hounddogai/hounddog). We currently handle privacy scanning for Replit's 45M+ creators. We built HoundDog because privacy compliance is usually a choice between manual spreadsheets or reactive runtime scanning. While runtime tools are useful for monitoring, they only catch leaks after the code is live and the data has already moved. They can also miss code paths that aren't actively triggered in production. HoundDog traces sensitive data in code during development and helps catch risky flows (e.g., PII…
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Hello everyone. I've been working on this experimental editor called Huzzah. I've been working almost exclusively with coding agents since January of this year, and over the past few months I began to feel utterly exhausted by them. They're great, but I'm finding it more and more tedious to write full sentences for every change I want. Not only that, but it seems there's a complexity limit for codebases - beyond a certain point the agent begins confusing itself. I'd like to go back to writing code, but I don't want to go all the way back to fully manual coding. So I've come up with this…
17d ago · danielvaughn.dev
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Hi HN! We just launched Codacy Guardrails, an IDE extension with a CLI for code analysis and MCP server that enforces security & quality rules on AI-generated code in real-time. It hooks into AI coding assistants (like VS Code Agent Mode, Cursor, Windsurf), silently scanning and fixing AI-suggested code that has vulnerabilities or violates your coding standards, while the code it’s being generated. We built this because coding agents can be a double-edged sword. They do boost productivity, but can easily introduce insecure or non-compliant code. One recent research team at NYU found that 40%…
2025
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Hey HN, I’m Henry, cofounder and CTO at Span (https://span.app/). Today we’re launching AI Code Detector, an AI code detection tool you can try in your browser. The explosion of AI generated code has created some weird problems for engineering orgs. Tools like Cursor and Copilot are used by virtually every org on the planet – but each codegen tool has its own idiosyncratic way of reporting usage. Some don’t report usage at all. Our view is that token spend will start competing with payroll spend as AI becomes more deeply ingrained in how we build software, so understanding how…
Sep 2025 · code-detector.ai
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Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
2025 · infinitcode.ai
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Hi, I’m Kenny, I’ve been building aislop. I starting working on this after using Claude Code, codex and opencode several times and noticing some slops. They aren’t syntax and passes most tests, they are patterns like empty catch blocks, useless comments, duplicated helpers, dead code and many more. So I built a tool to scan and check for these patterns and wired it into hooks so after each tool call, the agent checks for the slops. You can try it out with npx aislop scan. It’s all local and no code is transferred. Thank you.
May 2026 · github.com
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OP here. I built this because I recently caught myself almost pasting a block of logs containing AWS keys into Claude. The Problem: I need the reasoning capabilities of cloud models (GPT/Claude/Gemini), but I can't trust myself not to accidentally leak PII or secrets. The Solution: A Chrome extension that acts as a local middleware. It intercepts the prompt and runs a local BERT model (via a Python FastAPI backend) to scrub names, emails, and keys before the request leaves the browser. A few notes up front (to set expectations clearly): Everything runs 100% locally. Regex detection…
Dec 2025 · github.com
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I originally was just messing with pi-autoresearch. Gave it a sample task to build the most portable coding agent. First cut was 6 KB of shell. Great for one-shots, unusable interactively. I was shocked it actually worked. Started building up -- adding features — but with a self-imposed rule: no new dependencies, and sub 500 LOC. This thing had to be truly portable. Just sh, curl, awk. System primitives only. Which means I did some genuinely disgusting things in awk, including JSON parsing and the OpenAI Responses tool loop with reasoning items carried across turns. It's now ~400 lines. In…
Apr 2026 · pu.dev
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I built this after seeing multiple teams accidentally ship API keys in their frontend code. The problem: Modern web development moves fast. You're vibe-coding, shipping features, and suddenly your AWS keys are sitting in a tag visible to anyone who opens DevTools. I've personally witnessed this happen to at least 3-4 production apps in the past year alone. KeyLeak Detector runs through your site (headless browser + network interception) and checks for 50+ types of leaked secrets: AWS/Google keys, Stripe tokens, database connection strings, LLM API keys (OpenAI, Claude, etc.), JWT…
Nov 2025 · github.com
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2024 · securelog.com
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I know we are very wary of AI slop but disclaimer: AI was used. I don't think that it is slop though and it was mostly used for formatting.
Jul 2026 · github.com
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Your AI has your code's text, never its map. Fix that.
Jun 2026 · luuuc.github.io
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I'm an "ideas person" who messes around with AI on a low budget. I got tired of watching my tokens vanish and context windows filling up while agents fumbled around trying to find the right thing. Agents don't flail like they used to with shell tools, but there are still weak/blind spots and back-and-forth episodes — especially when using tools in combination/sequence. So I built "tilth" today. Or rather, AI built it — every line is Opus 4.6. I spent a lot of my precious tokens getting it to "not shit" (at least several of the different vendors' AI overlords assure me it's not…
Feb 2026 · github.com
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We're open-sourcing Sighthound today, our rules-based static security scanner. What makes it special is that it's coded in rust and uses tree-sitter as it's AST making it very fast and easily extensible. Why build another scanner in 2026? We wanted to improve some of our detection outcomes but noticed the current open source scanners like Semgrep/Opengrep we're capped by a bunch of adoption limitations such as being written in OCaml, requiring a lot of work to add a language parser, and the rulesets were licensed differently and required paid offerings. It also felt that licensing was…
Jul 2026 · github.com
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I built an open-source AI agent for security testing to find and fix vulnerabilities in your code. I’ve noticed how bad security vulnerabilities have gotten with everyone shipping AI code slop, so I wanted to build something that allows for vibe-coding at full speed without compromising security. Traditional security tools aren’t effective, and manual pen-testing can’t keep up with the rapidly growing AI code This tool runs your code dynamically, finds vulnerabilities, and validates them through actual exploitation. You can either run it against your codebase or enter your (or someone…
2025 · github.com
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I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
2025 · github.com
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I'm an infrastructure architect who started using AI assistants to write code 3 months ago. After building several systems with Claude, I noticed a pattern: the code always had security issues I could spot from my ops background, but I couldn't fix them myself since I can't actually write code. Why I built this: I needed a way to verify AI-generated code was production-safe. Existing tools either required cloud uploads (privacy concern) or produced output too large for AI context windows. TheAuditor solves both problems - it runs completely offline and chunks findings into 65KB segments that…
Sep 2025 · github.com
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