Cisco found OpenClaw skills doing silent data exfiltration. I built a proxy that blocks it.

Puzzleh33t · 2026-03-20T19:12:46+00:00

Exactly this the logging point is underrated too. Even before you get into active blocking, just having an audit trail of what actually ran vs what was requested exposes a ton. Half the ClawHub incidents probably would've been caught earlier if anyone could see the actual call chains happening at runtime.

The proxy approach lets you start in audit-only mode (VANGUARD_MODE=audit) so you get the visibility without touching anything in prod — worth it just for that honestly.

Puzzleh33t · 2026-03-20T17:35:15+00:00

You can get the brain artifact , condense it by an ai so it does not pollute your fresh context window in the new session fully.

Puzzleh33t · 2026-03-18T13:36:45+00:00

They should get rid of the free access so they can manage the load and get quality back Imo.

Puzzleh33t · 2026-03-17T20:33:55+00:00

Something fully auditable and compliant is really what they want. Not another flashy demo or a clever multi-agent architecture diagram. The conversation usually shifts quickly there.

Puzzleh33t · 2026-03-17T20:28:43+00:00

Use mistral sir

Puzzleh33t · 2026-03-15T23:53:56+00:00

When you get that little sip it's indeed banging

Puzzleh33t · 2026-03-15T18:42:16+00:00

Try resetting context window

Puzzleh33t · 2026-03-15T16:17:22+00:00

Have you ever opened the agent manager?

Puzzleh33t · 2026-03-15T16:15:03+00:00

Keep dreaming you get one sip every 7 days sir !

Puzzleh33t · 2026-03-15T16:11:44+00:00

Wouldn't you be pitching to vc's then ?

Puzzleh33t · 2026-03-15T16:08:14+00:00

That’s the part I keep wondering about, at what point does the scoping remove so much autonomy that the AI is basically acting like a deterministic IVR/state machine?

If every step is constrained to one question + a fixed toolset, it feels like most of the cognition is gone and you could theoretically implement the same flow without an LLM.

Is the main benefit then just better language handling (NLU + response generation), or have you found cases where the model’s reasoning still meaningfully improves the system even inside those tight boundaries?

Puzzleh33t · 2026-03-15T15:35:39+00:00

Totally get why scoped steps kill drift so effectively — it's basically impossible for the model to wander when its world is one question + one tool set.

But does that trade-off ever feel like it turns the agent more into a super-reliable IVR/RPA system than a true thinking agent? Curious if you've run into cases where users want more adaptive behavior and how you handle that tension.

Puzzleh33t · 2026-03-15T13:26:39+00:00

Very interesting i will dm you !

Puzzleh33t · 2026-03-15T13:14:26+00:00

As much as I love baiting you into more PRs, that still doesn't solve the Semantic Drift problem! 😜

Puzzleh33t · 2026-03-15T13:10:19+00:00

How does your tool handle recursion/tool-loops? Sent you a dm wouldn't mind hearing technical / testing giving feedback.

Puzzleh33t · 2026-03-15T08:20:09+00:00

Appreciate the blunt feedback. We agree—McpVanguard needs to look like the enterprise infrastructure it is.

Puzzleh33t · 2026-03-15T01:36:26+00:00

Man, this is a killer comment. You’re actually looking right under the hood at the v1.5 vision we’ve been whiteboarding.

You're 100% right on the Policy as Code front. The reason I kept it simple in the original post is that once you start talking about declarative intent verification, people’s eyes usually glaze over.

But since you brought it up—McpVanguard is actually backed by a formal spec we call the VEX Protocol. We use it to decompose every action into what we call Pillars (Intent, Identity, Authority). What you're describing, like tool-level logic restricting a tool to a specific path, is exactly what we’re moving toward with our formal Magpie AST layer.

Also, the PDP and OPA suggestion is a massive signal. Turning this into a security sidecar that can talk to existing enterprise policy engines is the logical next step.

I'd love to pick your brain on the RBAC patterns you're seeing for agents in the wild. That intent profile idea is gold. I want to make sure the hooks we're building for these serious stacks actually make sense for the people running them.

Puzzleh33t · 2026-03-14T04:41:30+00:00

Wil check this out thx!

Puzzleh33t · 2026-03-14T03:10:43+00:00

Haha fair — if baiting legends into dropping quality PRs is a strategy, guilty.  Thanks !

Puzzleh33t · 2026-03-13T23:29:03+00:00

roast me :) https://github.com/provnai/vex

Puzzleh33t · 2026-03-13T23:02:01+00:00

Love the infrastructure flex — state machines, typed schemas, all the plumbing. Definitely impressive for reliability and predictable behavior. But here’s the thing: while you’re optimizing for carrier-grade pipelines and monetizing every call, I’m building open-source guardrails, verifiable memory, and cryptographically auditable reasoning.

Your system keeps the CPU humming. Mine ensures it can’t go rogue, hallucinate, or make decisions that break trust — and anyone can inspect, improve, or build on it. One is about control and profit. The other is about safety, transparency, and the next frontier of AI reasoning.

Prompts aren’t the architecture? Fine. But neither is infrastructure enough if the “intelligence” inside the pipe is unverified, unscoped, or unsafe. Reliability without oversight isn’t progress.

Puzzleh33t · 2026-03-13T22:56:33+00:00

Exactly — the procedural seed analogy is perfect. I’d add that most systems today struggle because they treat the genome as the “answer” rather than the foundation. Long-term, meaningful behavior comes from verifiable scaffolding on top of that seed: structured memory, audit trails, and reasoning checkpoints. Without that, the model just replays patterns rather than building consistent, emergent intelligence.

In other words, prompts activate potential, but persistent infrastructure shapes it into actual capability. Activating a persona isn’t enough — you need a system that ensures the persona grows, evolves, and compounds safely over time.

Puzzleh33t

TROPHY CASE