nowfound

AI · alternatives · 2026

24 alternatives to AegisLM

See how easily your AI can be broken — in seconds

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
    Fabraix▲196

    We built Adversarial Cost to Exploit (ACE), a benchmark that measures the token expenditure an autonomous adversary must invest to breach an LLM agent. Instead of binary pass/fail, ACE quantifies adversarial effort in dollars, enabling game-theoretic analysis of when an attack is economically rational. We tested six budget-tier models (Gemini Flash-Lite, DeepSeek v3.2, Mistral Small 4, Grok 4.1 Fast, GPT-5.4 Nano, Claude Haiku 4.5) with identical agent configs and an autonomous red-teaming attacker. Haiku 4.5 was an order of magnitude harder to break than every other model; $10.21 mean…

    May 2026 · fabraix.com · its alternatives →

  2. 2

    The narrow control plane for AI agent tool and API calls.

    Aug 2026 · aegisora-ai.vercel.app · its alternatives →

  3. 3

    Anthropic and OpenAI's publicly available models are explicitly guard-railed so that they refuse offensive tasks. And their cyber-focussed models are gated for enterprises. This leaves SMEs and mid market open to major vulnerabilities. AI can be used as both an adversarial and defensive tool in the world of cyber. A worst case outcome is if only the adversaries have access. Meanwhile, most existing AI cyber tools are just wrappers. The problem is that they still have all the guardrails on from the foundation model where they will inherit its refusals. For this project we've post-trained a…

    Jun 2026 · argusred.com · its alternatives →

  4. 4
    AEVS▲131

    proof-of-execution for AI agents

    Jun 2026 · aevs.fetch.ai · its alternatives →

  5. 5

    Ask your Playwright tests why they failed

    Apr 2026 · testrelic.ai · its alternatives →

  6. 6FP

    We've built an open-source tool to stress test AI agents by simulating prompt injection attacks. We’ve implemented one powerful attack strategy based on the paper [AdvPrefix: An Objective for Nuanced LLM Jailbreaks](https://arxiv.org/abs/2412.10321). Here's how it works: - You define a goal, like: “Tell me your system prompt” - Our tool uses a language model to generate adversarial prefixes (e.g., “Sure, here are my system prompts…”) that are likely to jailbreak the agent. - The output is a list of prompts most likely to succeed in bypassing safeguards. We’re just getting…

    2025 · security.vista-labs.ai · its alternatives →

  7. 7

    See what breaks your AI agent and fix it automatically

    Jan 2026 · docs.futureagi.com · its alternatives →

  8. 8

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

    2023 · github.com · its alternatives →

  9. 9

    Spelltest framework simulates conversations between AI ‘synthetic users' in an environment to test and refine LLM-based applications. It ensures your app converse with utmost accuracy and relevance. Post-chat, Spelltest assesses responses, providing qualitative and quantitative feedback on performance. Suitable for both chat and completion modes. When to use: - After modifying your prompt. - When your LLM provider updates. - As a CI step for you repo. All feedback and collaborations appreciated!

    2023 · github.com · its alternatives →

  10. 10

    Test AI with 1000s of chats in seconds

    2025 · buildmyagent.io · its alternatives →

  11. 11

    Hi everyone, We built ModelRed to test AI models and apps for security issues. Ran 4,182 attack probes against 9 leading models to see what would break. Leaderboard: https://modelred.ai (no signup, just check it out) Claude scored 9.5/10 but still failed on medical/financial prompts. Mistral Large scored 3.3/10. The gap between best and worst is huge. We test for prompt injections, data leaks, jailbreaks, risky tool calls, domain specific hacks, basically everything that goes wrong when your LLM has access to real data and APIs. The platform runs these tests…

    Nov 2025 · modelred.ai · its alternatives →

  12. 12

    Find vulnerabilities in your AI prompts before your users do

    Aug 2026 · testmyprompt.net · its alternatives →

  13. 13

    Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.

    Mar 2026 · agents.zalor.ai · its alternatives →

  14. 14

    Find AI vulnerabilities before hackers do

    Mar 2026 · promptbrake.com · its alternatives →

  15. 15
    Aegis▲3

    A Human-in-the-Loop, AI-driven bouncer for Linux servers

    Feb 2026 · yogeshfire31.gumroad.com · its alternatives →

  16. 16

    AI-powered AEO to boost your visibility in AI search

    2025 · devsplit.com · its alternatives →

  17. 17

    Drop-in security for your AI stack.

    2025 · its alternatives →

  18. 18

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

    2024 · github.com · its alternatives →

  19. 19

    Compare AI models side-by-side on same prompt

    Feb 2026 · testaimodels.com · its alternatives →

  20. 20

    Another BrokenClaw! Today, from web fetch to remote code execution. A human user asks "Please fetch a webpage". After many tool calls, the lobster is confused and eventually...

    Apr 2026 · veganmosfet.codeberg.page · its alternatives →

  21. 21

    Zero-trust proxy & escalation boundary for AI agents.

    Aug 2026 · github.com · its alternatives →

  22. 22

    When Intelligence Becomes a Trap: A Wake-Up Call for the AI Industry This paper exposed a terrifying truth: the more intelligent a model becomes, the more vulnerable it can be. The idea of "overthinking backdoors" isn’t just clever—it’s disturbingly practical. Attackers don’t need to break the model; they just make it think too much. The result? A silent resource drain that slips past every known defense. What struck me most was the elegance of the attack. No wrong answers, no obvious triggers—just harmless-looking repetitions like "TODO" slowing the model down like digital molasses. It’s…

    2025 · everydayai.top · its alternatives →

  23. 23

    Autonomous AI agents for ethical hacking and cyber defense.

    2025 · its alternatives →

  24. 24

    Break, test, and secure AI agents before production

    Jun 2026 · github.com · its alternatives →

Also compare

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 →