Alternatives
Products that do what Beating GPT5.5-xhigh for Coding agent security with SLMs and IRM does
Coding agents craft arbitrary code so securing them is more complicated than red-teaming. We post trained a cyber-security small llm, changed how it reasons and supplemented our controls using program analysis techniques such as inline reference monitoring to outperform GPT5.5-xhigh on hard benchmarks like LinuxArena and SleightBench. Free product available at harden.run and full benchmarks in the blog post.
- 1

- 2

Fast and efficient models optimized for coding and subagents
Mar 2026 · openai.com
- 3

- 4

- 5

- 6

- 7

- 8

- 9

- 102C
Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
- 11

- 12MS
Author here! Some context: I published this 48 hours ago and it was auto-listed on MCPMarket (the MCP tools directory). Got 700+ organic downloads with zero marketing—developers were actively searching for exactly this solution. The "Git Accelerator" optimization story: Initially used a file walker that took 6.6s on Chromium. Profiling showed 90% was filesystem I/O. The fix: git ls-files returns 480k paths in ~200ms. Added smart heuristics for untracked files (only scan dirs <50k files), bringing total to 0.46s. Why this matters: Agents can't wait 10 seconds for search. Sub-500ms makes…
Jan 2026 · github.com
- 13EY
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
- 14OM
I built OpenSwarm because I wanted an autonomous “AI dev team” that can actually plug into my real workflow instead of running toy tasks. OpenSwarm orchestrates multiple Claude Code CLI instances as agents to work on real Linear issues. It: • pulls issues from Linear and runs a Worker/Reviewer/Test/Documenter pipeline • uses LanceDB + multilingual-e5 embeddings for long‑term memory and context reuse • builds a simple code knowledge graph for impact analysis • exposes everything through a Discord bot (status, dispatch, scheduling, logs) • can auto‑iterate on existing PRs and…
Feb 2026 · github.com
- 15IB
The only way to go fast is full YOLO mode in your coding agent. I've got the local sandbox figured out (pro tip: Incus VMs work great) but I wanted to keep my agents from doing things like inadvertently blowing up my cloud services or chasing a prompt to POST to some random website. I struggle most with this on my side projects where my permission model isn't quite as robust as it is at the office. I started with a firewall on the Incus container but every time the agent needed access to something new, I was poking more holes in it - and it didn't differentiate between HTTP verbs. I've been…
Jul 2026 · trollbridge.dev
- 16IS
Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…
2025
- 17IB
Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
- 18OS
We built an open-source library of 125 GTM (go-to-market) skills that plug into AI coding agents like Claude Code, Codex, and Cursor. With these skills an AI agent can automatically: - Find ICP leads from conference speakers, LinkedIn activity, or job boards - Generate personalized cold email sequences - Monitor competitor blogs, pricing pages, and hiring signals - Generate programmatic SEO pages from keyword lists - Track where your brand appears in ChatGPT, Perplexity, and Claude answers --- How skills work Each skill is a structured markdown file containing instructions, scripts, and tool…
Mar 2026 · github.com
- 19

- 20SR
Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…
Jul 2026 · shikigami.dev
- 21

Security-first AI that reviews entire repo, not just diffs
Jul 2026 · looksgoodtomeow.in
- 22AR
Hi HN. I'm the founder of Phoenix Labs (ex TikTok, Applied AI) and we're open sourcing our internal tooling today which is like a toolchain / meta-harness for CLI agents useful for really scaling eng and creative work. We are a very small team who's building a very ambitious product so we had to find ways to squeeze every ounce of efficiency that we could get our hands on. Harness strengths of different models (Claude, GPTs) and CLI-harnesses (Claude Code, Codex), safe/robust browser integration to speed up UX/QA testing, teams cli to speed up security reviews and parallelize…
May 2026 · agents-cli.sh
- 23AR
If you're interested in exploring what LLM-based agent systems these days actually do to solve certain benchmarks such as SWEBench or WebArena, we created a small leaderboard with our team, that allows to view a lot of public and OSS agent results including all the runtime traces (the step-by-step reasoning behind the scenes). Looking at traces is actually quite interesting, as they reveal a lot about the inner working and shortcomings of current agent system, e.g. see https://explorer.invariantlabs.ai/u/invariant/webarena--SteP... for an example trace.
2024 · explorer.invariantlabs.ai
- 24

Ranked by how close each launch is in meaning, then by votes. Refine with a description →