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u/Efficient-Simple480

r/micro_saas r/CIO r/AI_Agents r/n8n r/CFO r/SaaS r/founder r/Terraform r/n8n_ai_agents r/buildinpublic r/aisecurity
▲ 24 r/CFO+2 crossposts

If everyone’s “building” now, what’s the point of having a CEO, CFO, CISO, or CMO?

When leaders spend their time building instead of leading, they drift from the one thing they were hired to be great at.
That seems counterproductive for any organization. To be clear, I’m not saying they should stop. I’m trying to understand who does the actual leading while they’re heads-down building.

Titles like CEO, CFO and CISO exist because someone has to own those decisions.
And if the answer is “AI will handle it,” that’s a way bigger claim than anyone’s admitting. AI can draft the budget model, but it can’t own the call, answer to the board, or take the blame when things go wrong.

So genuinely asking: is building now part of the leadership job, or is something quietly falling through the cracks? Thoughts?

reddit.com
u/Efficient-Simple480 — 3 days ago
▲ 0 r/Terraform

Self-host the SecureVector engine on your cloud of choice with Terraform + connect any agent to deployed engine endpoint.

Deploy AI-agent security to your OWN cloud, any region (EU, US…), one Terraform module. 

SecureVector v4.9.0 runs the engine in your own cloud account.
Point any agent at it , every call monitored, exfil blocked live, governance posture mapped to EU AI Act / NIST / OWASP

Repo (EU demo): https://github.com/Secure-Vector/securevector-eu-demo

Terraform modules one per cloud, all Apache-2.0:

- AWS     https://github.com/Secure-Vector/terraform-aws-securevector
- Azure   https://github.com/Secure-Vector/terraform-azurerm-securevector
- GCP     https://github.com/Secure-Vector/terraform-google-securevector
- Oracle  https://github.com/Secure-Vector/terraform-oci-securevector

Full 4-min demo: https://www.youtube.com/watch?v=yogcCk_UjV0

u/Efficient-Simple480 — 3 days ago
▲ 2 r/founder+2 crossposts

Self-host the SecureVector engine on your cloud of choice with Terraform + connect any agent

Deploy AI-agent security to your OWN cloud, any region (EU, US…), one Terraform module. 

SecureVector v4.9.0 runs the engine in your own cloud account. Point any agent at it , every call monitored, exfil blocked live, governance posture mapped to EU AI Act / NIST / OWASP

Full 4-min demo: https://www.youtube.com/watch?v=yogcCk_UjV0
Repo (EU demo): https://github.com/Secure-Vector/securevector-eu-demo

Terraform modules one per cloud, all Apache-2.0:

- AWS     https://github.com/Secure-Vector/terraform-aws-securevector
- Azure   https://github.com/Secure-Vector/terraform-azurerm-securevector
- GCP     https://github.com/Secure-Vector/terraform-google-securevector
- Oracle  https://github.com/Secure-Vector/terraform-oci-securevector

Framework SecureVector Guard SDKs Apache-2.0:

- LangChain  https://github.com/Secure-Vector/securevector-sdk-langchain
- LangGraph  https://github.com/Secure-Vector/securevector-sdk-langgraph
- CrewAI     https://github.com/Secure-Vector/securevector-sdk-crewai
- Hermes    https://github.com/Secure-Vector/securevector-sdk-hermes

u/Efficient-Simple480 — 3 days ago
▲ 4 r/aisecurity+3 crossposts

SecureVector v4.8.0: now with Agent Governance posture + SDKs for LangChain, LangGraph & CrewAI

- Agent Governance posture: qualitative on-device (Strong/Weak), numeric Posture Score in the cloud console graded against NIST AI RMF + SOC 2 controls

- Cloud Connect is metadata-only; prompts stay on the device.

- EU data-residency lock +bring-your-own-cloud (Terraform) for in-region self-hosting

Open-Source: https://github.com/Secure-Vector/
Demo: https://www.youtube.com/watch?v=G8-JQ-nRmTY

Give it a try, comment or DM me with any feedback or questions.

- Coming soon!!
Terraform the engine into your own cloud → deploy our SDKs to your agents → point them at your own in-region endpoint. Your agents. Your engine. Your region.
Nothing leaves your cloud.

u/Efficient-Simple480 — 10 days ago
▲ 2 r/founder+1 crossposts

Fleet-Wide Agent Map & Runs across all your devices in a single view

Built a Fleet-Wide Agent Map & Runs view so you can monitor multiple agent runs from multiple devices in one app. It pairs with a local plugins that records what your agents do: every command, file edit and MCP call on a live map, with secret-leak + threat detection. Local tool as the funnel, cloud as the product.

u/Efficient-Simple480 — 20 days ago
▲ 4 r/aisecurity+2 crossposts

View Fleet-Wide Agent Map & Runs + SecureVector Cursor Plugin

Shipped SecureVector v4.7.1 today.

Built a plugin that records everything my Cursor agent does: every command, file edit and MCP call on a live map, with secret-leak + threat detection.

Agent Map, Agent Runs and Timeline now roll up across all my machines into a single view in the cloud app. Signed macOS .dmg or pip install securevector-ai-monitor[app].

Demo in the link

youtu.be
u/Efficient-Simple480 — 20 days ago
▲ 1 r/buildinpublic

SecureVector v4.6.0 ( Copilot CLI plugin + Guardian ML on-device threat detection)

Guardian ML - a lightweight ML model that runs threat detection entirely on-device. Scans alongside the regex rules, catches obfuscated / paraphrased / encoded attacks literal patterns miss. Every detection labeled Rule / ML / Rule+ML. Sub-millisecond. Ships enabled with an informed-consent banner — say what it is, where data goes (nowhere), offer the off switch right there.

Copilot CLI plugin - SecureVector Guard now covers GitHub Copilot CLI alongside Claude Code, OpenAI Codex, and OpenClaw. preToolUse allow/deny, tamper-evident audit, prompt-injection scanning. Copilot's hooks fail closed, so the Guard explicitly fails open — a stopped app never blocks your session.

https://github.com/Secure-Vector/securevector-ai-threat-monitor

Demo: https://youtu.be/CBrC3eBieeQ?si=9gQcMU0GkHp58xpo

u/Efficient-Simple480 — 24 days ago
▲ 4 r/n8n_ai_agents+3 crossposts

Built a visual map of AI agent behavior

Hey everyone, I recently added Agent Map and Agent Runs features in the tool that I've been building.

Agent Map renders every agent run as a live visual graph device, harness, session, every tool called, color-coded by risk class. One screen instead of grep. Still fully on-device.

Looking for feedback from people running AI agents in production. Claude Code users, Codex users, OpenClaw users, MCP server builders, LangChain or LangGraph folks: what's the first thing you wish you could see when your agent does something unexpected, would this Agent Map and Agent Runs help for your use case?

u/Efficient-Simple480 — 27 days ago
▲ 1 r/buildinpublic

SecureVector v4.5.0 ( Agent Map + Codex plugin + multi-harness coverage )

​​

  • Agent Map - live visual graph of every agent run. Device → harness → session → tool calls, color-coded by risk class. Replaces log-spelunking.
  • Codex plugin - SecureVector now covers OpenAI Codex CLI alongside Claude Code and OpenClaw. New enforcement vocabulary for exec_command / apply_patch / web_search.
  • Risk classification - shell, filesystem, web, MCP each rendered with distinct severity in the map.
  • https://github.com/Secure-Vector/securevector-ai-threat-monitor

Demo: https://youtu.be/9RByIHSV95s?si=09SOk\_bVqxLpzRpc

reddit.com
u/Efficient-Simple480 — 29 days ago
▲ 3 r/n8n_ai_agents+1 crossposts

built a security tool for AI agents because watching them call random tools felt like handing my laptop to a stranger

Hey everyone,

I recently shipped v4.3.0 of SecureVector. The reason is simple: when an AI agent runs on your machine, you lose visibility. The usual process is:

Install agent → connect MCP servers → let it call tools → hope.

But the questions that actually matter are:

* What MCP servers are even active right now?
* What tools have they called this week?
* Did any of them touch a secret?
* Did any of them return something that looked like a prompt-injection payload?
* Did any of them quietly leak a PEM private key in the response?
* Is this agent racking up a $400 LLM bill while I sleep?

So I built a local-first security layer for AI agents.

Instead of running the agent blind, every tool call and response is intercepted on-device. You can see which MCP servers and tools are active (a Bill of Tools view), what's flowing in and out of them, every secret the scanner catches (hashed, never raw), and a per-agent LLM cost meter with hard budget caps. It is designed for developers and teams who run AI agents locally and want their own visibility.

The current model is simple: open-source local app (Apache-2.0), with an optional cloud subscription for teams that want centralized MCP policy management across list of devices/machines where agents are running and ML-driven analytics.

I'm curious to hear feedback from people running AI agents in production Claude Code users, OpenClaw users, MCP server builders, anyone shipping LangChain or LangGraph in prod: what's the question you wish you could answer about your agent right now?

reddit.com
u/Efficient-Simple480 — 1 month ago
▲ 1 r/founder

I built a security tool for AI agents because watching them call random tools felt like handing my laptop to a stranger

Hey everyone,

I recently shipped v4.3.0 of SecureVector: https://github.com/Secure-Vector/securevector-ai-threat-monitor . The reason is simple: when an AI agent runs on your machine, you lose visibility. The usual process is:

Install agent → connect MCP servers → let it call tools → hope.

But the questions that actually matter are:

  • What MCP servers are even active right now?
  • What tools have they called this week?
  • Did any of them touch a secret?
  • Did any of them return something that looked like a prompt-injection payload?
  • Did any of them quietly leak a PEM private key in the response?
  • Is this agent racking up a $400 LLM bill while I sleep?

So I built a local-first security layer for AI agents.

Instead of running the agent blind, every tool call and response is intercepted on-device. You can see which MCP servers and tools are active (a Bill of Tools view), what's flowing in and out of them, every secret the scanner catches (hashed, never raw), and a per-agent LLM cost meter with hard budget caps. It is designed for developers and teams who run AI agents locally and want their own visibility.

The current model is simple: open-source local app (Apache-2.0), with an optional cloud subscription for teams that want centralized MCP policy management across list of devices/machines where agents are running and ML-driven analytics.

I'm curious to hear feedback from people running AI agents in production Claude Code users, OpenClaw users, MCP server builders, anyone shipping LangChain or LangGraph in prod: what's the question you wish you could answer about your agent right now?

u/Efficient-Simple480 — 1 month ago
▲ 1 r/buildinpublic

SecureVector v4.3.0 ( Bill of Tools + Secret Detections + Bidirectional scans )

→ MCP Tool Inventory (Bill of Tools) - SBOM-style supply-chain view along with export options.
→ Secret Detections - hash-only audit log
→ Bidirectional tool-response scans - IDPI + PII rules on MCP/WebFetch/Read/Grep responses.
→ PEM private-key + OpenSSH-binary detection (T1552.004)

https://github.com/Secure-Vector/securevector-ai-threat-monitor#audit-every-tool-catch-the-threats-all-locally

u/Efficient-Simple480 — 1 month ago
▲ 4 r/aisecurity+2 crossposts

SecureVector v4.2.1 - Claude Code plugin landed + MCP Policy management

Launched SecureVector v4.2.1

- SecureVector plugin for Claude Code — every MCP tool call in your statusline, audited locally.

- MCP Catalogue + Cloud Policies — author policies to allow/deny/audit tools, push it across every enrolled developer machine (or multiple devices) on next sync.

MCP policy + Claude code plugin Demo:
https://www.youtube.com/watch?v=V25yxqlAoY0
Device Enrollment Demo:
https://youtu.be/vHXWl38hRjM

Github:
https://github.com/Secure-Vector/securevector-ai-threat-monitor#-securevector

StatusLine

​

reddit.com
u/Efficient-Simple480 — 1 month ago
▲ 1 r/n8n

Finally shipped the latest version of the n8n community node for SecureVector. Got verified on n8n Cloud, so it shows up directly in the node picker.

Two modes:

  • Local App runs 100% on your machine, prompts never leave your network, tamper-evident audit chain
  • Cloud ML-driven detection

What you get:

  • Prompt scanning / monitoring — injection, jailbreaks, and more threat categories (input + output)
  • Tool permission gating — allow / block / log for AI Agent tool calls
  • Per-agent cost tracking with daily budgets

Main use case: AI Agent workflows where you want runtime policy enforcement on tool calls. The agent only sees a wrapper tool (e.g. secure_read_file), so the permission check is unavoidable — can't prompt-engineer around it.

Search SecureVector in the node picker. Demo workflows in the GitHub repo.

Happy to take feedback , would love to hear how you're thinking about AI agent security in your own workflows.

reddit.com
u/Efficient-Simple480 — 2 months ago
▲ 3 r/SaaS

Hello I am a solo founder and built an app that runs locally and sits between AI agents and their tools, scans every call, blocks threats, logs everything. SecureVector performs Threat scanning, tamper-evident tool audit logs, LLM cost tracking, and SIEM forwarding (Splunk, Datadog, Sentinel, any webhook).

Runs locally, open-source, and your data never leaves your machine. Cloud version is optional and will help B2B to get consolidated view of agent activity.

u/Efficient-Simple480 — 2 months ago