AI · alternatives · 2026
24 alternatives to LLVM-jutsu: Anti-LLM obfuscation pass
Anti-LLM obfuscation via finger counting . Contribute to thebabush/llvm-jutsu development by creating an account on GitHub.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Langfuse▲771Open source tracing and analytics for LLM applications
2023 · langfuse.com · its alternatives →
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I made a free tool that stuns LLMs with invisible Unicode characters. *Use cases:* Anti-plagiarism, text obfuscation against LLM scrapers, or just for fun! Even just one word's worth of “gibberified” text is enough to block most LLMs from responding coherently.
Nov 2025 · gibberifier.com · its alternatives →
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New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
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Lakera Guard▲131Protect your LLM applications with a few lines of code.
2023 · lakera.ai · its alternatives →
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Hi HN! Langfuse is OSS observability and analytics for LLM applications (repo: https://github.com/langfuse/langfuse, 2 min demo: https://langfuse.com/video, try it yourself: https://langfuse.com/demo) Langfuse makes capturing and viewing LLM calls (execution traces) a breeze. On top of this data, you can analyze the quality, cost and latency of LLM apps. When GPT-4 dropped, we started building LLM apps – a lot of them! [1, 2] But they all suffered from the same issue: it’s hard to assure quality in 100% of cases and even to have a clear view…
2023 · github.com · its alternatives →
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MaskLLM▲132Mask your LLM APIs for secure rotation and logging
2025 · maskllm.com · its alternatives →
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Breadcrumb▲163Open-source LLM tracing for agent visibility
Mar 2026 · breadcrumb.sh · its alternatives →
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Ultra-fast, low latency LLM prompt injection/jailbreak detection ⛓️ - arekusandr/last_layer
2024 · github.com · its alternatives →
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If you've built any web-based app in the last 15 years, you probably used something like Datadog, New Relic, Sentry, etc. to monitor and trace your app, right? Why should it be different when the app you're building happens to be using LLMs? So today we're open-sourcing OpenLLMetry-JS. It's an open protocol and SDK, based on OpenTelemetry, that provides traces and metrics for LLM JS/TS applications and can be connected to any of the 15+ tools that already support OpenTelemetry. Here's the repo: https://github.com/traceloop/openllmetry-js A few months ago we launched…
2024 · github.com · its alternatives →
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New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
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Good morning HN! For a while now I have been toying with this idea and now finally have a working prototype. This project allows you to encode secret messages into ordinary looking text by using arithmetic coding with a probability model derived from an LLM. By encrypting the message and then decompressing the encrypted message using the arithmetic coder, you get output which looks just like randomly sampled output from the LLM. Except, it actually encodes your secret messages in the specific choices of tokens. By using authenticated encryption, only a user who knows the key can know that a…
2025 · github.com · its alternatives →
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Next-gen decompiler.
2018 · rev.ng · its alternatives →
- 13

Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com · its alternatives →
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Hi HN, I built this open-source LLM red teaming tool based on my experience scaling LLMs at a big co to millions of users... and seeing all the bad things people did. How it works: - Uses an unaligned model to create toxic inputs - Runs these inputs through your app using different techniques: raw, prompt injection, and a chain-of-thought jailbreak that tries to re-frame the request to trick the LLM. - Probes a bunch of other failure cases (e.g. will your customer support bot recommend a competitor? Does it think it can process a refund when it can't? Will it leak your user's address?) -…
2024 · promptfoo.dev · its alternatives →
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Hey, folks here is a peek into Jujutsu. We at Poozle are working with hundreds of APIs and it has been always frustrating to 1. Search the API in the documentation or ask ChatGPT 2. Then copy it to the postman and understand/test the API 3. Generate code to integrate into the codebase We thought how about having all of this at one place. We currently fine-tuned LLM on public REST APIs to reduce hallucination and then combined it with ChatGPT and Postman. I look forward to feedback, feature requests and discussions!
2023 · loom.com · its alternatives →
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The LLM Anti-Framework. Contribute to Mirascope/mirascope development by creating an account on GitHub.
Jan 2026 · github.com · its alternatives →
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The LLM Anti-Framework. Contribute to Mirascope/mirascope development by creating an account on GitHub.
2024 · github.com · its alternatives →
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- 19OS
Hello everyone I wanted to share a project I've been working on that I think you'll find really interesting. It's called Beelzebub, an open-source honeypot framework that uses LLMs to create incredibly realistic and dynamic deception environments. By integrating LLMs, it can mimic entire operating systems and interact with attackers in a super convincing way. Imagine an SSH honeypot where the LLM provides plausible responses to commands, even though nothing is actually executed on a real system. The goal is to keep attackers engaged for as long as possible, diverting them from your real…
2025 · its alternatives →
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The void is now A/B tested. One user prompt: “Be silence.” One toggle: embodiment system prompt. Present → 0 bytes. Absent → speech. GPT-5.2 + Claude Opus 4.6. Sealed run. Prompt hash. Provider message IDs. https://t.co/YpVSWPKof2 https://t.co/SSs7yBRYRb @OpenAI @AnthropicAI @GoogleDeepMind
Jun 2026 · twitter.com · its alternatives →
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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 →
- 22

Today I designed a method to prevent users from jailbreaking ChatGPT (for instance, users have generated instructions to produce weapons or illegal drugs, commit a burglary, kill oneself, take over the world as an evil superintelligence, or create a virtual machine which they then can use). The OpenAI team appears to be countering these primarily using prompt engineering or fine-tuning on the ChatGPT model. The idea is to use a second and fully separate, fine-tuned LLM to evaluate prompts before sending them to ChatGPT. You can test this by inserting your successful ChatGPT jailbreaks. Break…
2022 · github.com · its alternatives →
- 23

Playing around with aider.chat to write an LLM powered agent to jailbreak Gandalf: https://gandalf.lakera.ai/gandalf-the-white Feel free to fork and play around with it!
2024 · github.com · its alternatives →
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