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LOCAL-FIRST · DETERMINISTIC · FAIL-CLOSED

Put a hard boundary in front of your AI agents.

Belay is a local security layer that sits at the tool-call boundary of your AI coding agents. It blocks the dangerous stuff outright, asks you about the rest, and never lets a single agent misstep leak your secrets or wreck your host — in under 100 milliseconds, with no LLM in the decision path.

Detect · Block · Notify — a defense and monitoring layer for AI coding agents.

curl -fsSL https://dl.belay.secblok.io/install.sh | bash
macOS (Intel + Apple Silicon)Windowsin progressLinuxx86_64
Diagram: an AI agent's tool call passes through Belay's boundary gate, which routes it to an Allow or Deny verdict

How Belay gates a tool call

One boundary, in front of everything the agent tries.

01

Gate at the tool-call boundary

Belay wires into your agents where it counts: every tool call, before it runs. Claude Code and Codex get native PreToolUse/PostToolUse hooks; any MCP server can be wrapped so its tools/call requests are gated too. One policy boundary, in front of everything the agent tries to do.

02

Deterministic, sub-100ms, no LLM

The decision engine is compiled-in rules, not a model. No network round-trip and no language model in the hot path — just a fast, repeatable verdict in under 100 milliseconds. And it is fail-closed: a timeout or an error becomes a deny, never an accidental allow.

03

You decide the gray areas

Clear-cut danger is blocked outright. For the ambiguous-but-risky calls, Belay pauses the agent and asks you — right in your terminal, browser, or chat app — with an inline Allow or Deny. Do not answer in time? It denies. Deny always wins.

04

Scan before you install

The static scanner inspects code before it ever runs on your machine — patterns, AST, taint, YARA, and OSV analyzers combine into a provenance-weighted score and an install/run recommendation. It emits SARIF 2.1.0, so it drops straight into your CI code-scanning. The same scanner also covers agent skills, so a malicious skill gets caught before it is trusted.

05

A log you can prove was not touched

Every verdict is written to a hash-chained audit log: each row is cryptographically linked to the one before it, so tampering is detectable. Build a signed evidence pack on demand, and let planted honeypot canaries trip a critical alert the instant anything reads or exfiltrates them.

06

Native firewall + a vuln DB with no keys

Host controls are built in, in pure Rust — a native firewall and a bundled vulnerability database, with no external tools to install and no NVD key to configure. Findings carry CISA KEV badges and EPSS exploit-probability percentages out of the box, and optional egress destination enrichment (reverse-DNS, ASN, owner, country) is display-only — it never gates.

07

Explain & Advise

Every verdict carries a plain-English explanation: why it is risky, and what to do instead. Turn on an optional BYOK AI explainer — local Ollama or a cloud provider of your choice — for a deeper look. Off by default, advisory only, and secrets/host paths are redacted before anything is sent.

08

Two-way approvals over chat

Answer Allow/Deny prompts from Telegram, Discord, WhatsApp, Matrix, Mattermost, or Slack — not just the terminal. ntfy, Teams, WeCom, and generic webhooks get notify-only alerts. Pairing-code enrollment keeps it owner-gated, and a prompt that goes stale is auto-denied.

Detect, protect, and watch it live.

1

Detect

belay detect

Finds the AI coding agents already installed on your machine and flags the risky settings they are running with.

2

Protect

belay protect <agent>

Wires Belay in at the tool-call boundary. Start with --observe to tune out false positives, then switch to enforcing.

3

Serve + Desktop UI

belay serve

Runs a local API + live event stream on your machine, and the desktop app renders it: posture at a glance, activity triage, and a live feed — with pending approvals surfaced for a one-click Allow/Deny.

OWASP ASI Top 10Every rule tagged to the Agentic Security Initiative Top 10
OWASP LLM Top 10Mapped to the LLM application risk categories
MITRE ATLASFindings tied to adversarial-ML techniques
SARIF 2.1.0Scanner output your CI already understands
Local-first · No phone-homeYour code and secrets stay on your machine