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AI · alternatives · 2026

24 alternatives to ReasonGate- An explainable gate that blocks LLM prompt injection

Explainable security gate for LLM apps — blocks prompt injection with an auditable reason for every decision. - cgrtml/reasongate

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.

    2023 · github.com · its alternatives →

  2. 2

    We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…

    Mar 2026 · github.com · its alternatives →

  3. 3

    Prompt injection and token savings - #1 in benchmarks

    Jul 2026 · constellationgate.ai · its alternatives →

  4. 4

    Security gateway for LLM agents

    Feb 2026 · cencurity.com · its alternatives →

  5. 5

    Protect your LLM applications with a few lines of code.

    2023 · lakera.ai · its alternatives →

  6. 6

    New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.

    2023 · github.com · its alternatives →

  7. 7

    A pre-answer safety gate for RAG and chatbots

    Dec 2025 · its alternatives →

  8. 8

    Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…

    2025 · archestra.ai · its alternatives →

  9. 9

    Hi there, me and some friends were inspired by Simon Willison's recent post on the "lethal trifecta" (https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/ ) and started building a gateway to defend against it. The idea: instead of connecting an LLM directly to multiple MCP servers, you point them all through a Gateway. The Gateway: - Connects to each MCP server and inspects their tools + requirements - Classifies tools along the "trifecta" axes (private data access, untrusted content, external comms) - When all three conditions are about to align in a…

    2025 · github.com · its alternatives →

  10. 10

    Prompt-injection firewall for prod LLM apps

    Jul 2026 · insightits.com · its alternatives →

  11. 11

    The CI gate that says no to unapproved AI code

    Aug 2026 · linebreakapp.com · its alternatives →

  12. 12

    Production grade prompt injection defense middleware for LLM

    Jul 2026 · its alternatives →

  13. 13

    Just stop jailbreaks & prompt hacks with one API call.

    2025 · expireddomains.com · its alternatives →

  14. 14

    Every other gateway is detect-and-block. You don't get a security grade. You don't get red team in CI. We built the one that does. PromptGuard is a proxy: change your base URL (one line with our SDK, or a few lines without), and every request gets checked for prompt injection, PII leaks, jailbreaks, and abuse. 20+ threat vectors, 39+ PII types. We also ship a red team suite and an autonomous agent that mutates attacks to find bypasses - you get a grade (A-F) and a GitHub Action that runs these tests on every PR. So you see where you're weak before you ship. Works with OpenAI, Anthropic,…

    Dec 2025 · promptguard.co · its alternatives →

  15. 15

    Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️ - arekusandr/last_layer

    2024 · github.com · its alternatives →

  16. 16

    Little tool that I made to understand how (un)reasonable my prompts are.

    Jan 2026 · github.com · its alternatives →

  17. 17

    Self-hosted LLM router. Cost effective, deterministic, and fast. Secure and private by default. - Northwood-Systems/millwright

    Jul 2026 · github.com · its alternatives →

  18. 18

    We’ve been building visual rule engines (clear spreadsheet interfaces -> API endpoints that map incoming data to a large number of potential outcomes), and had the fun idea lately to see what happens when we use our decision table UI with Claude’s PreToolUse hook. The result is a surprisingly useful policy/gating layer– these tables let your team: - Write conditional, exception-friendly policies beyond globs/prefixes (e.g. allow rm -rf only in */node_modules/*, deny / or $HOME, ask if --force or network call; gate kubectl delete / SQL DROP with a clear reason) -…

    Jan 2026 · github.com · its alternatives →

  19. 19

    A zero-trust security layer between your apps and LLMs

    Jan 2026 · its alternatives →

  20. 20

    A CLI tool for managing and semantically diffing LLM prompts. Goes beyond text diff by detecting meaning-level changes using embeddings (OpenAI or local). Useful for versioning, testing, and CI/CD workflows.

    2025 · github.com · its alternatives →

  21. 21

    Anti-LLM obfuscation via finger counting . Contribute to thebabush/llvm-jutsu development by creating an account on GitHub.

    Dec 2025 · github.com · its alternatives →

  22. 22

    I've built an app that extracts interpretable 'circuits' from models using the GPT-2 architecture. These circuits reveal how specific inputs influence the probabilities of the next token in a sequence. While some tutorials present theoretical examples of how feedforward layers and attention heads may produce predictions, this app provides concrete examples of how information flows through an LLM. You can see, for example, the formation of features that search for simple grammatical patterns and trace their construction back to the use of more primitive features. Feel free to reach out with…

    2024 · peterlai.github.io · its alternatives →

  23. 23

    Your LLM doesn't think. We make sure of it.

    Apr 2026 · tictacguy.github.io · its alternatives →

  24. 24

    Web tool to slice codebase clutter & save 50%+ on LLM tokens

    Jun 2026 · polar.sh · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →