MurphyA/hacker-news huggingface dataset:
Show HN: ClawShield – Open-source security proxy for AI agents (Go, eBPF)
by sleuthco | 2026-03-02 01:11:57+00:00
Author here. ClawShield is a security proxy that sits in front of OpenClaw (open-source AI gateway) and scans all inbound/outbound messages.

The core is an HTTP/WebSocket reverse proxy in Go (~6k lines) with four scanners:

1. Prompt injection detection - three tiers: regex heuristics (role overrides, instruction injection, delimiter attacks, encoding attacks), structural analysis (base64-decoded instruction blocks, imperative verb density scoring), and canary token leak detection.

2. Secrets/PII scanning - regex argument filters applied to decoded JSON values (defeats unicode escape bypasses like \u0070assword).

3. Vulnerability scanning - SQLi (UNION, tautologies, blind with SLEEP/BENCHMARK), SSRF (private IPs, cloud metadata at 169.254.169.254, decimal/hex IP encoding, dangerous schemes like gopher://), path traversal (double URL-encoding,
null bytes), command injection (shell metacharacters, backtick execution), XSS.

4. Malware detection - magic bytes for PE/ELF/Mach-O, YARA-like signature rules for reverse shells and C2 frameworks,
archive bomb detection via compression ratio, Shannon entropy analysis.

Policy engine is deny-by-default YAML. You define tool allowlists, denylists, per-tool argument filters, domain allowlists, and per-agent/per-channel restrictions. Every decision is logged to SQLite.

Optional extras: iptables egress firewall (Go, generates validated rules from YAML) and eBPF kernel monitor (Python/BCC - traces execve, tcp_v4_connect, openat2, setuid for fork bomb/privesc/port scan detection).

Docker quickstart is 3 commands. Ten cross-compiled binaries on the release (proxy + setup wizard for linux/mac/windows, amd64/arm64).

We run this in production at clawshield.sleuthco.ai.

I built this because I was contributing security patches to OpenClaw and the netfilter suite and kept seeing the same gap: the AI ecosystem has sophisticated multi-agent routing but no standardized way to inspect and control what flows through it.

Happy to answer questions about the scanner architecture, policy engine, or threat model.
by lukol | 2026-03-02 01:12:20+00:00
#1: You do not want randomness. You may believe you do until the Titanic crashes into your front yard and your significant vanishes into thin air. You want quite a lot of predictability, up to a degree where it might not even matter if things at the lowest level of existence are not perfectly deterministic.

#2: What's so bad about thinking about life as an exciting rollercoaster ride? The tracks are laid but the ride is still fun.
by socalgal2 | 2026-03-02 01:12:46+00:00
The Google hate virus is thick here. It seems uncontroversial that users will likely want to use AI to find info for them and do things for them. So either Google provides users with what they want or they go out of business to some other company that provides what users want.

https://www.perplexity.ai/comet

https://chatgpt.com/atlas/

https://arc.net/max

That is not in any way to suggest companies are ok to do bad things. I don't see anything bad here. I just see the inevitable. People are going to want to ask some AI for whatever they used to get from the internet. Many are already doing this. Who ever enables that for users best will get the users.
by Nevermark | 2026-03-02 01:12:50+00:00
You are right, but I think there is a more positive viewpoint.

All experiments agree with the many worlds interpretation (again, better described as a quantum web interpretation), and it is the plain Occam's Razor interpretation.

No additional flourishes are needed. That is strong theoretical support. It is the default (plain reading) interpretation already.

And it is the interpretation that doesn't just conserve in one history (i.e. conservation of energy etc.), but conserves information universally.

So again, very strong specific theoretical support.

It is the conjectures about experimentally unmotivated elaborations, like "collapses", that would also break universal conservation of information, for no theoretically necessary reason, that need dramatic new evidence to prove themselves.

If I lack any optimism, it is for conjectured complications with no evidentiary support and weaker explanatory/conservation powers. In any other context, nobody would be entertaining the need for such conjectures.

The "Quantum Collapsers" are right up their with the "Flat Earthers", or solar system "Epicycle Theorists", for not being happy with accepting a working and successful theory as is. Even though their imagined shivs introduce more questions than they answer, and would dispense with its unique advantages.
by guerython | 2026-03-02 01:12:58+00:00
The AI-native buzzword sounds scary because you read it as "AI eats your packets," but the engineering plan is a lot more down-to-earth. They want to feed the schedulers sanitized telemetry (per-slice latency, packet loss, active UE count) into trained controllers instead of hand-tuned heuristics so the slice can rebalance in milliseconds.

The critical safeguard is to separate that telemetry plane from any user payload and run it through a zero-trust gateway before the ML model sees it. We built the same trick into a 5G edge orchestrator last year and the model only ever touched aggregated KPIs, never user content, which kept compliance teams happy while still letting the scheduler react faster than timers ever could.
by etbebl | 2026-03-02 01:13:07+00:00
The example in the article is a waiting room. Or you could be waiting to catch the subway, or in line at the grocery store. In those situations how is somebody trying to talk to you preventing you from completing your task? Otherwise you're probably just scrolling your phone; sometimes I fill these gaps with things like podcasts, but even then it's not like what I'm doing is urgent.
by krackers | 2026-03-02 01:13:18+00:00
Well they used strings of < 800 chars, you probably run into context window and training limits at some point (they mention some result that you need at least something of GPT-2 size to begin recognizing more intricate CFGs (their synthetic cfg3f). But then again your physical real-world computer which is conceptually "turing complete" can't handle "infinite strings" either.

> Dyck/balanced-brackets grammar

Yes, it's not the Dyck grammar but another CFG they created, they call it the "cfg3" family.

Of course I agree the stack (/pushdown automaton) is the simpler and perfectly optimal structure for this task, but I think it's unfair to say that LLMs _cannot_ recognize or generate CFGs.

(Then again I know you didn't make any such broad refutation of that sort, I mostly wanted to bring up that paper to show that it is possible for them to at least "grok" certain CFGs with low enough error ratio that they must have internalized the underlying grammar [and in fact I believe the paper goes on to apply interprability methods to actually trace the circuits with which it encodes the inductive grammar, which puts to rest any notion of them simply "parroting" the data]). But these were "synthetic" LLMs specifically trained for that grammar, these results probably don't apply in practice to your chatGPT that was trained mostly on human text.
by Terr_ | 2026-03-02 01:13:53+00:00
Before anyone jaunts too far down the road of literal survivorship bias, I'd like to point out that it'd be incredibly premature—or perhaps way too late—to speculate much on the social side of things.

Elsewhere I've seen some people making hay about exactly whose-males were with whose-females, and want to point out that it's normal for genes to cause asymmetries.

In particular, consider the modern problem of RH incompatibility [0], where one pairing is more likely to end up with a child than an identical but gender-bent one.

[0] https://my.clevelandclinic.org/health/diseases/21053-rh-fact...
Show HN: Leyoda – Shareable startup cards with analytics
by whitehatd | 2026-03-02 01:15:36+00:00
Hey HN,

I built Leyoda — founders create an interactive startup card and share it as a single link. Investors get everything at a glance: metrics, stage, team, fundraising status. Tap to flip for pitch deck, video, and socials.

Every card has real analytics — views, shares, card flips, top referrers (we detect WhatsApp, LinkedIn, Telegram, in-app browsers), geographic breakdown via GeoIP, and device stats. We also track which AI systems are crawling your card (70+ bots identified, from ChatGPT to Gemini to Perplexity).

The idea: replace the "check out my deck" cold email with one link that tells you who viewed it and where they came from.

Free during alpha. Would love feedback — is this the kind of link you'd actually send to an investor?
by whitehatd | 2026-03-02 01:16:12+00:00
Some more context on the build:

I wanted to solve the problem of founders sending pitch decks into the void with zero visibility. With Leyoda, you get a shareable card at leyoda.eu/s/{id} — paste it anywhere and it renders a rich OG preview. Behind the scenes, every view is tracked with referrer attribution, geolocation, and device fingerprinting.

The AI bot detection was a rabbit hole. Bots don't execute client-side JS, so we track them server-side during SSR. We identify 70+ crawlers organized into tiers — AI chatbots (ChatGPT, Claude, Gemini), data scrapers (GPTBot, CCBot, Bytespider), AI agents (NovaAct, Manus, Devin), and search indexers (Perplexity, Brave, Kagi). We even catch Gemini's bare "Google" user-agent.

Stack: Java 21 / Spring Boot, Next.js 16, PostgreSQL + PostGIS, MinIO. Cards use raw CSS transforms and JS touch handlers — no animation libraries. ClamAV scans all uploads. Blue-green deploys with zero downtime.

The result is this:
Demo (shareable card link): https://leyoda.eu/s/0d91cf5f-b5a1-4e76-8d75-ad4dd9b09896

If you open it on mobile, it feels like a “startup swipe card” + flip-to-deck.

Happy to answer questions about the architecture or the analytics pipeline.
by A_D_E_P_T | 2026-03-02 01:16:56+00:00
The question presupposes that "the experience of the color blue" is a discrete object that needs a storage location. But that's the dualist picture in disguise. On a functionalist view, blueness isn't stored; it's what certain neural activity constitutively is when you're that system observing that blue.

As an aside, isn't it more weird that violet and purple look indistinguishable despite being physically so different? It's said that this is because our L-cones (red-sensitive) have a secondary sensitivity peak at short wavelengths. So violet light triggers S-cones + a bit of L-cone. Purple light (red + blue) also triggers S-cones + L-cones. Similar activation pattern = same quale. It's all functional/physical.

Read Tom Cuda "Against Neural Chauvinism." Also Daniel Dennett.
by alejo | 2026-03-02 01:17:18+00:00
For Jira/Confluence, I also struggled with their MCPs. JIRA’s MCPs was hit or miss and Confluence never worked for me.

We don’t use the cloud versions, so not sure if they work better with cloud.

On the other hand, i found some unofficial CLIs for both and they work great.

I wrote a small skill just to give enough detail about how to format Epics, Stories, etc and then some guidance on formatting content and I can get the agent do anything i need with them.
by foinker | 2026-03-02 01:17:20+00:00
We're focusing on the waymo because it did this on its own for some inscrutable reason and there is no individual accountability, which is a far more useful discussion to be having if we are supposed to trust these things to be replacing humans on the road. The humans behavior is only relevant in the sense that now all humans on the road have an additional hazard to factor in: errant waymos that you can't gesture to or yell at or honk at or make any attempt to understand their intentions.
by FireBeyond | 2026-03-02 01:17:36+00:00
The current administration's "we need your voter rolls" has fuck-all to do with "requiring ID to vote".

> Like in literally every country

As a citizen of Great Britain, Australia and now the US, I'm well aware of this.

And it doesn't change the "you can vote without ID in blue states!" from being the absolute bullshit that it is, and again, has nothing to do with why DHS is demanding voter rolls from blue states.
by fghorow | 2026-03-02 01:17:46+00:00
May peace be unto him, you, and the rest of your family.

When (if?) you feel ready, there is an organization [1] whose mission is to support siblings, parents, and grandparents of children who have died at any age. I have been heavily active with them since losing my only child 9+ years ago. I commend them to your attention. (Once again, when you feel ready.)

[1] compassionatefriends.org
Show HN: YourFinanceWORKS – Open-source financial management with AI
by snowsky | 2026-03-02 01:17:57+00:00
Hey HN,

I've been building YourFinanceWORKS, a comprehensive open-source financial management platform that combines enterprise-grade features with AI-powered automation. Think of it as a self-hosted alternative to QuickBooks/Xero with advanced capabilities.

## What makes this interesting for HN:

*Technical Architecture:*
- Multi-tenant design with database-per-tenant isolation
- FastAPI + PostgreSQL + Redis + Kafka stack
- AI-powered OCR using vision models (95%+ accuracy)
- Event-driven architecture with background processing
- Plugin system for extensibility
- Docker deployment with production-ready configuration

*AI Integration:*
- Receipt/invoice OCR with structured data extraction
- Natural language queries ("Show me overdue invoices")
- Fraud detection and anomaly analysis
- Risk scoring for financial documents
- Configurable prompt management with versioning

*Key Features:*
- Professional invoicing with AI templates
- Automated bank reconciliation
- Multi-level approval workflows
- Real-time financial dashboards
- Advanced audit trails and compliance
- Investment portfolio tracking plugins

*Open Source Innovation:*
- Dual-licensing model (AGPL for core, Commercial for enterprise)
- Transparent AI prompt engineering
- Community plugin ecosystem
- Comprehensive documentation (100+ pages)

## Why I built this:

After paying thousands for financial software that didn't meet our needs, I wanted to create something that:
- Respects user privacy (self-hosted)
- Provides enterprise features without enterprise pricing
- Leverages modern AI for actual automation (not just buzzwords)
- Has a transparent, extensible architecture

## Quick start:
```bash
git clone https://github.com/snowsky/yourfinanceworks.git
cd yourfinanceworks
docker-compose up --build -d
```

## Interesting technical challenges solved:
- Secure multi-tenancy at database level
- High-accuracy financial document OCR
- Real-time financial dashboards with WebSocket updates
- Configurable approval workflows with AI validation
- Cross-tenant analytics while maintaining isolation

The project is production-ready with comprehensive documentation, automated tests, and deployment guides.

*GitHub:* https://github.com/snowsky/yourfinanceworks

Would love feedback from the HN community on the architecture, AI implementation, or any aspect of the system. What features would make this compelling for your use case?
by marcs5573 | 2026-03-02 01:17:59+00:00
I built this after spending way too much time downloading models that either didn't fit in VRAM or ran at unusable speeds.

You pick your hardware (GPU, RAM, VRAM) and it tells you which models are viable — with estimated token speeds and memory usage. No benchmarks from machines you'll never own.

The goal is simple: skip the trial-and-error. If you have a 3090 or an M2 Mac Mini or a machine with 64GB unified memory, you should be able to know in 30 seconds what you can actually run well.

Would love feedback — especially from people running unusual setups (Jetson, Mac Studio, multi-GPU). Those are the edge cases I want to get right.

→ llmpicker.blog
by BenoitEssiambre | 2026-03-02 01:18:07+00:00
One underrated reason that CLIs are often better than MCP is that Unix tools seem to have close to information theoretically optimal layout to enabled reasoning. They are concise, in the Solomonoff/Kolmogorov sense.

This means that the related parts in the inputs and outputs are recursively as close together as possible.

There's a reason humans don't type and read http/json on the command line. It's hard to read and reason over that type of syntax. json is made to be easy to parse for simple algorithms, not meant to organise info in an easy to reason about layout.

AIs benefit from the easy to reason about layout. It's not just about being able to fit in the context window but about the contents of that context window being organized such that the attention mechanism doesn't have to stretch itself out trying to connect far apart related pieces. It doesn't have to try to match brackets to disambiguate information. CLIs tend to use formats that are obvious at a glance for humans and LLMs alike.

It's about the entropy of the formats. https://benoitessiambre.com/entropy.html
by fdgg | 2026-03-02 01:18:18+00:00
The most likely explanation for "AI layoffs" is not that AI has caused a dramatic jump in productivity - its more that managers are running out of creativity in relation to revenue-generating and cost-reducing projects and henceforth have no use for the surplus of labour. Its much easier to maximize the stock price in the short-term by riding the 'AI' wave.

There seems to be some nonsensical belief that there exists this endless stream of positive NPV projects to take. No... reality is not like that.
by cal_dent | 2026-03-02 01:18:33+00:00
Also, one thing not mentioned in the article is that, structurally, some of this is a consequence of a growing sense that we live in a low trust society. I don't necessarily think that is true in the small/local sense for many people, but a lot of the media we consume and talk about highlights that so much of society is untrustworthy and that forces many people to close themselves up as a completely rational way of protecting themselves.

I hope more and more people do not continue to believe that, there is so much good out there in the world and we all have to engage it or we're just letting the low trust side win and life becomes a lot less because of that. Everyone already into chatting for chatting sake now and then, please continue to do so. You're doing a world a huge service. The rest not, come join us, the water feels great!
by maximinus_thrax | 2026-03-02 01:18:39+00:00
> Do websites want to prevent automated tooling, as indicated by everyone putting everything behind Cloudfare and CAPTCHAs since forever,

Not if they don't want their rankings to tank. Now you'll need to make your website machine friendly while the lords of walled gardens will relentlessly block any sort of 'rogue' automated agent from accessing their services.
by collingreen | 2026-03-02 01:19:28+00:00
That's roughly correct though? Like the alleged point is exactly that - provide an incentive to establish true information earlier than otherwise. If you view prediction markets like that it's only weird to see people taking the other side with no information (I was going to say "like bar bets" but that's the same kind of thing! Don't bet on things you know nothing about if you hate losing money!)
by lurk2 | 2026-03-02 01:19:35+00:00
> Would the citizens of a sovereign nation being forced to violate their Constitution by Putin and Trump be a “violation of human dignity” too?

If Ukraine was worth defending they would have no trouble finding men willing to die to defend it. It’s one of the most corrupt countries in the Western world, its women are being allowed to flee so that they can prostitute themselves to Arabs and Europeans, and it hasn’t had an election in 7 years. Zelensky attempted to take control of the country’s anticorruption bureau in July of 2025: “Many suggest the attempted purges are payback for NABU pursuing charges of illicit enrichment and abuse of office against former deputy prime minister Oleksiy Chernyshov, a key ally for the Office of the President.”[1] In November of 2025, Timur Mindich, a former business partner and close friend of Zelensky, fled to Israel after being accused of orchestrating a kickback operation in cooperation with ministers of Zelensky’s own government. [2][3].

You have the opportunity to go die for these people right now. An increasing number of men in Ukraine have decided they would prefer not to.

[1] - https://www.atlanticcouncil.org/blogs/ukrainealert/ukraine-r...

[2] - https://www.timesofisrael.com/zelensky-associate-at-crux-of-...

[3] - https://www.uawire.org/ukraine-s-anti-corruption-bureau-to-s...
by pibaker | 2026-03-02 01:21:08+00:00
I am an iPhone user myself, but the number of "this is an android problem" and "just use iPhone" in response to the author's complaints surprises me. I thought HN was more anti apple in the past? Maybe we are all old now and tinkering with our devices is out of fashion, but this doesn't make the author's complaints illegitimate.

And if we zoom out a bit, iPhones are only 20% of the global phone market. The overwhelming majority of the world uses android because, well, iPhones are expensive. There are plenty of places where an iPhone is still a status symbol. Even you think the author should have bought his parents iPhones instead, there is still a whole world of people out there who would benefit from improvements in the android ecosystem.
by mlyle | 2026-03-02 01:21:36+00:00
There's no mathematically verifiable proof that anyone followed the rules. There's a cryptographic chain, but it just means "this piece of the stack, at some point, was convinced to process this and recorded that it did this." -- not whether that actually happened, what code was running, etc.

It doesn't tell you anything about what code was running there or whether it was really enforced.

Look, it's cool that this is an area that interests you. But I want you to know that AI agents are sycophantic and will claim your ideas are good and will not necessarily steer you in good directions. I have patents in the area of non-repudiation dating back 25 years and am doing my best to give you good feedback.

Non-repudiation, policy enforcement, audit-readiness, ledgers: these are all good things. As far as I can tell, there's nothing too special about doing this with LLMs, too. The same kinds of code that a bank uses to ensure that its ledger isn't tampered with and that the right software is running in the right places would work for this job -- and it wasn't vibe coded and mostly specified by AI.
by tzs | 2026-03-02 01:22:02+00:00
The number needed for a study to get significant results depends on the strength of the effect it is measuring.

For example if I have a bag full of thousands of coins, pull out 19 at random and flip them sequentially, and they all come out heads I'm going to conclude I have a bag that is overwhelmingly coins that are heavily biased toward coming up heads.

Are you going to say my sample size was too small to support that conclusion?

To see if their sample size was too small you need to at least read the part where they do the math.
by bonoboTP | 2026-03-02 01:22:22+00:00
Even if the help isn't great, good coding agents can try out the cli for a few minutes and write up a skill, or read the sources or online docs and write up a skill. That takes the spot of the --help if needed. I found that I can spare quite a lot of time, I don't have to type up how to use it, if there is available info about it on the web, in man pages, in help pages, or the source is available, it can figure it out. I've had Claude download the sources of ffmpeg and blender to obtain deeper understanding of certain things that aren't much documented. Recent LLMs are great at quickly finding where a feature is implemented, how it works based on the code, testing the hypothesis, writing it up so it's not lost, and moving on with the work with much more grounding and fewer guessing and assumptions.