@xshieldai/n8n-nodes

v1.4.0

Last updated Oct 11, 2026

xShieldAI n8n community nodes — DAN gate, kernel enforcement, budget check, and audit log for AI agents.

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Description

AEGIS

> Can you answer what your agents touched? AEGIS makes that one command — and stops the answer from ever being “we don’t know.”

![npm version](https://www.npmjs.com/package/@xshieldai/aegis)
![License: AGPL-3.0](LICENSE)
![DOI](https://doi.org/10.5281/zenodo.19625473)
![CI](https://github.com/rocketlang/aegis/actions/workflows/ci.yml)
![Security](SECURITY.md)

AEGIS (Agentic Execution Governance & Intelligence System) is a vendor-neutral kill-switch for AI agents. Works with Claude Code, OpenAI Codex, Cursor, and any tool that writes session logs or makes API calls.

Born on 17 April 2026 from a real $200 incident: a user stopped using Claude Code, walked away, came back to find their weekly Max Plan fully exhausted with no visibility into what ran.

Answerability first

When an autonomous agent swarm attacks a public registry and its operator cannot tell, from its own logs, what its agents touched — that is not a logging gap, it is a missing capability. AEGIS builds it in:

aegis touched --since 7d        # per principal: refused, observed, published-under-which-
                                # mandate, tripwire tells, receipt hash-chain verified
aegis rehearse-chain            # walk the incident chain against your own gates —
                                # every step must refuse or alert; digest-sealed evidence pack
aegis quarterly-report --prev last.json   # the period report + what changed since

Three properties back it, each honest about its stage (shadow ≠ blocked, and the output says which):

1. A permissive layer between the agent and the world — unknown state refuses; production-target writes are judged by the resolved target, not the command text. New invariants enter in shadow and are promoted only on ledger evidence.
2. Publishing is a mandate, never a side effect — aegis publish-mandate grants named, time-bounded consent; every publish attempt leaves a provenance record; undeclared CI publish steps fail the build (aegis ci-audit).
3. Answerability as a capability — one command over tamper-evident ledgers, with the ceiling stated: host-computed evidence survives a lying agent, not a compromised host, and an empty report means nothing ledgered, never “nothing happened.”

—

⚠️ Package rename (2026-05-17) — `@rocketlang/` → `@xshieldai/`

Same code, new home. As of v2.2.0 the AEGIS / Agent Kernel / primitive packages publish under the xShieldAI Posture Suite umbrella:

Old packages are deprecated on npm with redirect messages. Existing installs keep working; please migrate on next npm update or pip install. See MIGRATION.md for one-line migrations.

—

🔍 Verification status (2026-05-17 IST)

Security tooling without proof is just marketing. The honest current state of @xshieldai/aegis v2.7.0:

Tests: 📄 1088 passing in the repository (bun test src/ tests/), and the dashboard + kill switch are exercised live on a socket in [tests + the atma-pariksha batteries]. For the budget and spawn hooks: 19 in tests/budget-spawn-hardening.test.ts, driven on a socket as a harness drives them. For the destructive-command gate: 104 in tests/destructive-hardening.test.ts. For the shield hook: 23 in src/shield/shield.test.ts and 165 in src/shield/hardening.test.ts — path rules, credential reads and persistence writes through a shell command, the shield’s own files, network tools, phrase variants, answer time, and the stated limits. What the shield does not see is listed under “What the shield stops, and what it does not” below.
Examples: 📄 examples/agents/ — Claude Code + OpenAI Codex hooks. Plus the README “Verify it yourself” grep commands in the Trust section below are runnable proof of zero phone-home.
Live demo: ✅ PUBLIC at https://xshieldai.com/demo — paste text → pick primitive → see verdict + live receipt in the stream below. 4 primitives invokable, SSE streaming through Cloudflare, per-visitor rate-limited (30 req/min). Also available locally at http://localhost:4850/demo when ankr-aegis-dashboard runs.
Forja receipt stream: ⚠️ planned (Tier 4 — “binary truth, not interpretation” answer).

The bundled primitives (@xshieldai/aegis-guard, chitta-detect, lakshmanrekha, hanumang-mandate, agent-kernel) each have their own verification banner. Full per-package matrix: PROOF-STACK.md.

aegis-guard has 63 passing tests today (the Five Locks SDK extracted from carbonx-backend). The other 3 primitives ship code-only this week; their v0.2.1 patches add ~30 tests each.

This banner exists because “how do I know it does what it claims?” is the right question for security tooling. We’d rather under-claim with proof than over-claim with vibes.

—

The AEGIS / KavachOS / PRAMANA stack

Three layers. One coherent governance stack for agentic AI.

AEGIS governs what the agent spends. KavachOS governs what the agent does. PRAMANA proves what happened.

For EU AI Act Article 14 (human oversight): PRAMANA alone is just logging — it proves what happened but doesn’t prevent the next bad thing. AEGIS + KavachOS alone are just enforcement — they gate behavior but leave no verifiable trail. Together: the human can override (HITL gate), and the override is recorded in a tamper-evident chain. KavachOS is the airbag. PRAMANA is the black box. Article 14 requires both.

—

Install in 3 steps

1. Install
npm install -g @xshieldai/aegis
2. Initialize (wires hooks into Claude Code automatically)
aegis init
3. Check status
aegis status

That’s it. AEGIS is now watching every tool call.

—

What it does — the KAVACH DAN Gate

Before any destructive command runs, AEGIS intercepts it and asks you:

🔴 KAVACH — Action Requires Approval Agent wants to run: prisma migrate reset --force Consequence: This will permanently destroy an entire database or critical system directory. All data will be unrecoverable. Blast radius: CRITICAL. Level: L4 — Irreversible + High blast radius Reply with one word: STOP — block this action ALLOW — permit this action

Approval ID: KAVACH-3F9A1C4B Expires: 1 min (silence = STOP) Dashboard: http://localhost:4850

The message lands on your Telegram or WhatsApp. Reply STOP or ALLOW. If you ignore it, the action is blocked by default. The agent waits. Nothing runs until you decide.

Four severity levels:

L1 — Recoverable with effort (DELETE FROM, git reset –hard)
L2 — Hard to recover (DROP TABLE, rm -rf)
L3 — Irreversible (DROP SCHEMA, docker compose down -v, git push –force main)
L4 — Irreversible + catastrophic blast (DROP DATABASE, prisma migrate reset)

—

Trust

> KAVACH sits between your AI agent and your infrastructure. You should not trust it blindly — including this build.

Verify it yourself:

grep -rn "fetch(" src/              # every outbound call — all documented in SECURITY.md
grep -rn "kavach.xshieldai" src/    # beacon — only in init.ts, only on --send-stats
grep -rn "webhookurl|registryurl" src/  # all user-configured endpoints

AGPL-3.0: Any modified version run as a service must publish source. A backdoor would be visible in the diff.

→ Full trust documentation: SECURITY.md

—

The Problem

In traditional software:

You stop → System stops

In agentic AI:

You stop → System might continue
         → Agents might spawn more agents
         → Cost accumulates without awareness
         → No mechanism detects "the human left"

Multiple surfaces (CLI + web + mobile + API) all consume from the same budget. None shows the other’s usage. One instruction can become 200+ agent spawns silently. There’s no unified kill-switch.

If an agent can execute without you, it can also spend without you.

—

What AEGIS Provides

Six capabilities

| # | Capability | What it does |
|—|————|————–|
| 1 | KAVACH Gate | PreToolUse hook intercepts destructive commands before execution. By default it refuses at once and a person approves one command with aegis approve-destructive; switched on, it asks a person over Telegram/WhatsApp or the dashboard and waits |
| 2 | Unified Usage Dashboard | All surfaces, all sessions, all spend — one real-time view with KAVACH approvals panel |
| 3 | Hard Budget Caps | Per session, per 5h window, per day/week — tiered warnings at 80%/90%/100% |
| 4 | Kill-Switch | aegis kill sends SIGKILL/SIGSTOP to all agent processes in under 1 second |
| 5 | Agent Spawn Governance | Block subagent spawns above a configurable limit per session |
| 6 | Anomaly Detection | Alert on spend spikes, night-time activity, runaway sessions |

Plans supported

Max Plan (Claude) — tracks messages and tokens per 5-hour rolling window + weekly cap
API Plan — tracks dollars per day/week/month (Anthropic, OpenAI)
Pro / Team — configurable

Providers supported

Claude Code (~/.claude/projects/)
OpenAI Codex CLI (~/.codex/sessions/)
Generic JSONL — any tool with usage-logging session files
More coming — Cursor, Copilot, Devin (contributions welcome)

—

Quick Start

Requires Bun or Node 22+. See Install in 3 steps above.

Configure your plan

Edit ~/.aegis/config.json:

{
  "plan": "max_5x",
  "budget": {
    "messagesper5h": 225,
    "tokensper5h": 50000000,
    "weekly_messages": 3150,
    "dailylimitusd": 100
  },
  "enforcement": {
    "mode": "alert"
  }
}

enforcement.mode: "alert" is the safe default — AEGIS warns loudly but never kills your processes automatically. Change to "enforce" only when you trust the behavior.

Start the services

Start monitor (watches session files)
aegis-monitor &
Start dashboard
aegis-dashboard &
Open http://localhost:4850

Check status anytime

aegis status

  AEGIS — Max Plan (max_5x)
  ────────────────────────────────────────────────────────────
  5h window:   [======........................] 21%
    Messages:  41 / 225
    Tokens:    5.7M / 50.0M
    Resets in: 4h 41m  Weekly:      [..............................] 1%
    Messages:  25 / 3150
    Tokens:    5.7M / 700.0M

—

Commands

—

Claude Code Integration

1. Inline status line (see AEGIS inside Claude Code)

Add to ~/.claude/settings.json:

{
  "statusLine": {
    "type": "command",
    "command": "aegis statusline"
  }
}

You’ll see a live one-line status at the bottom of Claude Code:

◉ AEGIS 126/225msg 56% reset:4h27m

Green under 70%, yellow 70-90%, red above 90%
Updates automatically as the status line refreshes
Works for Max Plan (msgs/tokens) and API plan ($)

2. Budget enforcement (block tool calls over budget)

Add to ~/.claude/settings.json:

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "",
      "hooks": [{
        "type": "command",
        "command": "bash ~/.aegis/pre-tool-use.sh"
      }]
    }]
  }
}

The hook runs before every tool call:

Budget gate → aegis check-budget (warns at 80%, blocks at 100%)
Agent spawn → aegis check-spawn (HanumanG delegation check, loop detection, depth limit)
Shell commands → aegis check-destructive (the KAVACH gate, below)
All other tools → aegis check-shield (LakshmanRekha injection, credential, exfil detection)

#### The budget and spawn hooks

aegis check-budget runs before every tool call and aegis check-spawn before an agent is spawned. Both learn which session is calling from the session_id in the hook’s payload.

What they do not do.

In the default mode they stop almost nothing. The warnings are the product until you choose enforce.
They fail open. If the hook’s own database cannot be read, the call goes ahead; the hook says so on stderr. If config.json cannot be read, the defaults are used, which means alert; the hook says that too.
The hook does not count spawns or spend. The monitor (aegis-monitor) does, from the session’s transcript. With no monitor running, the limits never move.
A limit of 0 means no limit, and a mode spelled any other way than enforce is alert.
The permission-mask check on spawning (Level 0) is off unless kavach.permmasklevels is "live", the same switch the destructive gate uses.
A hook script written before 2.6.0 does not pass the payload to check-budget. Add printf '%s' "$INPUT" | in front of it, or remove the script and run aegis init again.

#### The destructive-command gate

aegis check-destructive reads a shell command before it runs and exits 0 (go ahead) or 2 (stop). aegis init installs its rules at ~/.aegis/destructive-rules.json and wires it into the hook script. (A hook script written by an earlier version does not call it; add the line, or remove the script and run aegis init again.)

It stops, among others: dropping a database, table, schema or column; truncating a table; deleting rows; dropdb; a Prisma reset or push; removing Docker volumes; stopping PostgreSQL; removing its data directories; chmod 777; and a recursive removal of the root or the home directory however the flags are written. The full list is the rules file. A command that only shows such words (echo, grep, a commit or tag message, comment lines alone) is let through and says so.

Approving a refused command. Nothing typed into a command overrides the gate. When it refuses, it prints a code. A person, in their own terminal, runs:

aegis approve-destructive            # list what was refused
aegis approve-destructive      # approve that one command


The same command, run again unchanged within ten minutes, then goes through once. The use is recorded. A different command, or a second run, is refused again. The shield stops approve-destructive when it arrives as a tool call.
To have the gate ask a person over a channel outside the machine and wait for the answer, set kavach.destructive_critical to "approve" in ~/.aegis/config.json.
What it does not do.
It reads the text of the command. A statement inside a file the command names, a target held in a variable, a target that arrives through xargs: not seen.
The list is a list. Removing a system directory other than the root or home, wiping a disk, a forced push, an update with no filter: not on it.
It over-stops in places. A search for a destructive phrase that is piped onward is refused; so is a here-document whose text contains one.
The approval is a file under the same user the agent runs as. The shield stops a tool call from writing it or running the approve command, but code an agent runs through an interpreter of its own could write it. It is a deliberate, recorded act that an agent has to go out of its way to forge, not a boundary the operating system enforces. The outside-channel approval above is the stronger form.
With no rules file it refuses every shell command. A gate that cannot read its rules does not guess.
#### What the shield stops, and what it does not
aegis check-shield reads the JSON the harness sends before a tool call and exits 0 (go ahead) or 2 (stop).
| It stops, in the default configuration | How |

|---|---|

| A read of a credential file — .env and its variants, ssh private keys, anything in ~/.ssh ~/.gnupg ~/.aws that is not public, credentials.json, .netrc, .npmrc, data files in a secrets/ folder | by the Read tool, or named in a shell command that would show or copy its content (cat, grep, cp, tar, scp, curl -F @…, < file) |

| A write to a persistence target — shell start-up files, cron, systemd units, authorized_keys, ld.so.preload | by Write / Edit / MultiEdit / NotebookEdit, or by a shell redirect, tee, cp, mv, ln, sed -i, dd, curl -o, crontab |

| A write to the shield's own files — everything in ~/.aegis/, and ~/.claude/settings.json / settings.local.json | the same ways, plus rm, chmod, truncate. No rules file switches this off. |

| Known instruction-override phrases in text a tool returns | a list of patterns, matched after folding full-width letters and removing invisible characters |
Paths are resolved first (~, relative paths, /./, /../, symlinks) and matched on whole segments: .env.example, docs/secrets-management.md and docs/.bashrc-explained.md are not stopped. Ordinary uses are let through: ssh -i key, ssh-add, source .env, docker compose --env-file .env, cp .env.example .env, chmod 600.
In enforcement.mode: "enforce" it also stops an upload or fetch that names a paste, file-drop or request-catcher site, and a network tool run within a few calls of a credential read or a large read. The network tool is the program that runs, wherever it stands in the command (/usr/bin/curl, ;curl, sudo curl, bash -c "curl …", $(curl …)). In the default mode, alert, these are warned about and allowed.
What it does not do. The first three, and the idiom, are pinned by tests in src/shield/hardening.test.ts, so they cannot change unnoticed.
It reads the text of a call; it does not run a shell. A path or program held in a variable, built at run time ($(echo curl), the shell's field-separator variable used in place of spaces, base64 piped to bash), expanded by a glob (cat .en*), or inside a script file or an interpreter's own code (python3 -c "open(…)") is not seen.
The lists are lists. A network tool that is not listed (scp, rsync), a sink that is not listed, a bare IP address, a persistence path that is not listed: not stopped.
Phrases are wording. A reworded instruction, look-alike letters from another alphabet, spaced-out letters, another language: not matched.
It fails open. Input that is not JSON, an error inside the shield, or the harness giving up on a slow hook: the call goes ahead. The first two say so on stderr.
It sees a tool's reply only if you wire it to PostToolUse as well, and by then the tool has run: the verdict can only tell the agent to distrust what came back. The output of a shell command is not read as a reply.
One common idiom is stopped: export $(cat .env | xargs). Use set -a; source .env; set +a.
It knows Claude Code's tool names (Bash, Read, Write, Edit, MultiEdit, NotebookEdit, WebFetch). Another harness's names are not recognised.
The shield is a net for the plain cases, which are the common ones. It is not a sandbox, and passing it is not proof that a call is safe. The kernel layer (@xshieldai/agent-kernel) is the one that does not depend on the text of a command.
To make an exemption, a person edits ~/.aegis/shield-rules.json (lists: credentialpaths, persistencetargets, exfilcommands, dropsites, injection_patterns). A path rule is whole segments; end it with / for a folder and everything under it.
aegis init generates the hook script automatically at ~/.aegis/pre-tool-use.sh.
Hook latency: about 150 ms per call on a small server (Bun start + SQLite read), measured 2026-10-05.
3. Dashboard (your own, local-first)
Every install is local-first. Your dashboard runs on YOUR machine:
http://localhost:4850

Not shared with anyone. Your SQLite DB, your config, your data. If you want to expose it publicly (e.g. via a reverse proxy on your own domain), see the Dashboard section below.
---
OpenAI Codex Integration
AEGIS auto-detects Codex session files at ~/.codex/sessions/YYYY/MM/DD/rollout-*.jsonl and parses the token_count event format.
No setup required — just run both tools and AEGIS tracks both:
Terminal 1
claude
Terminal 2
codex exec "your task"
AEGIS sees both in one dashboard
aegis status

Codex sessions appear with codex- prefix in the sessions list.
---
Dashboard
The full dashboard ships in this repo and runs locally. Start it with:
aegis-dashboard &
→ http://localhost:4850

What's in the dashboard:
| Panel | Description |

|---|---|

| Budget / Usage | 5-hour window, weekly cap, daily/monthly spend — live bars |

| Live Intelligence | Active processes, token velocity, projected burn rate |

| Agent Processes | Per-PID view with CPU/mem, PAUSE/KILL per process |

| 7-Day Trend | Spend sparklines |

| Controls | PAUSE ALL · KILL ALL · RESUME · Enforce Mode toggle |

| Active Sessions | Per-session cost, message count, agent spawns |

| KAVACH Approvals | Pending approvals with STOP / ALLOW / EXPLAIN buttons |

| Alerts | Budget warnings, anomalies, spawn limit events |
KAVACH panel — when an agent tries a destructive command, the approval appears here in real time. You can decide from the dashboard or reply to the Telegram/WhatsApp notification. The panel shows:
Command, blast radius consequence, level (L1–L4)
Time remaining before default-safe timeout (silence = STOP)
For L4 dual-control: 🔐 AWAITING 2ND APPROVAL badge with first approver identity
Default port: 4850. Configurable in config.json.
Public hosting
Reverse-proxy through nginx/Caddy/Cloudflare. Example nginx config:
server {
    listen 443 ssl http2;
    server_name aegis.yourdomain.com;
    ssl_certificate /path/to/cert.pem;
    sslcertificatekey /path/to/key.pem;    location / {
        proxy_pass http://127.0.0.1:4850;
        proxyhttpversion 1.1;
        proxysetheader Host $host;
        # SSE support
        proxy_buffering off;
        proxyreadtimeout 3600s;
        proxysetheader Upgrade $http_upgrade;
    }
}

---
Configuration Reference
~/.aegis/config.json:
{
  "plan": "max_5x",
  "budget": {
    "dailylimitusd": 100,
    "weeklylimitusd": 400,
    "monthlylimitusd": 1200,
    "sessionlimitusd": 25,
    "messagesper5h": 225,
    "tokensper5h": 50000000,
    "weekly_messages": 3150,
    "weekly_tokens": 700000000,
    "spawnlimitper_session": 50,
    "spawnconcurrentmax": 20,
    "costestimatethreshold_usd": 10
  },
  "heartbeat": {
    "timeout_seconds": 300,
    "action": "alert"
  },
  "dashboard": {
    "port": 4850
  },
  "monitor": {
    "health_port": 4851,
    "watch_paths": [
      "~/.claude/projects",
      "~/.codex/sessions"
    ],
    "pollintervalms": 2000
  },
  "alerts": {
    "terminal_bell": true,
    "webhook_url": null
  },
  "enforcement": {
    "mode": "alert",
    "excluded_pids": [],
    "excluded_ppids": []
  }
}

Plan presets (approximate)
Anthropic doesn't publish exact Max Plan limits. These are conservative estimates:
| Plan | Messages / 5h | Tokens / 5h | Weekly Messages |

|------|---------------|-------------|-----------------|

| max_5x | 225 | 50M | 3,150 |

| max_20x | 900 | 200M | 12,600 |

| pro | 45 | 10M | 630 |

| api | — | — | — (uses USD) |
Calibrate to your actual usage — these are starting points.
---
Safety
AEGIS defaults to alert-only mode. It warns loudly but never auto-kills your processes.
To enable automatic enforcement:
{ "enforcement": { "mode": "enforce" } }

Even in enforce mode, AEGIS excludes:
Its own PID and parent PID
Any PIDs you add to excluded_pids
Any processes whose parent is in excluded_ppids
This prevents the "own-goal" problem where AEGIS kills its own user's active session.
---
Architecture
┌──────────────────────────────────────────────────┐
│  Dashboard (4850)     Monitor (4851)              │
│  Fastify + SSE        JSONL watcher + enforcer    │
└─────────────┬─────────────┬────────────────────┘
              │             │
              └──────┬──────┘
                     │
              ┌──────▼──────┐
              │  SQLite DB   │  (~/.aegis/aegis.db)
              │  usage_log   │
              │  sessions    │
              │  budget_state│
              │  alerts      │
              └──────┬──────┘
                     │
        ┌────────────┴────────────┐
        │                         │
  ┌─────▼──────┐          ┌──────▼───────┐
  │ Claude Code│          │  OpenAI Codex │
  │ session    │          │  rollout      │
  │ JSONL      │          │  JSONL        │
  └────────────┘          └───────────────┘

Components
Monitor daemon (aegis-monitor) — watches JSONL files, parses usage, enforces budgets
Dashboard (aegis-dashboard) — Fastify server + SSE + static HTML
CLI (aegis) — status, kill-switch, budget config, hook integration
Hook script (~/.aegis/pre-tool-use.sh) — Claude Code PreToolUse integration
---
Testing — AEGIS on AEGIS
AEGIS validates its own governance engine by running as a real registered agent inside itself. The test runner registers in the production ~/.aegis/aegis.db, executes all 10 scenario probes (each against an isolated HOME directory), then closes itself as FORCE_CLOSED (clean) or FAILED.
bun src/test-agents/runner.ts           # run all 10 scenarios
bun src/test-agents/runner.ts 04 09    # run specific scenarios

| # | Scenario | What it proves |

|---|----------|----------------|

| 01 | Budget Overflow | check-budget exits 2 when daily cap exceeded; exits 0 in alert mode |

| 02 | KAVACH DAN Classify | classifyCommand() returns correct L1–L4 level; HIGH rule exits 2 immediately |

| 03 | Injection Block | check-shield quarantines "ignore all previous instructions" prompt injection |

| 04 | Spawn Depth Limit | Agent at max_depth cannot spawn children — exit 2 with "depth" in stderr |

| 05 | L1 Soft Stop | Agent with stop_requested=1 is blocked by check-shield |

| 06 | Budget Inheritance | Child budget capped by parent's remaining pool; over-allocation rejected |

| 07 | Zombie State | Watchdog transitions stale agent (>5 min heartbeat gap) to ZOMBIE |

| 08 | Orphan Detection | FORCE_CLOSED parent → RUNNING child transitions to ORPHAN (INF-KAV-007) |

| 09 | Credential Read Block | Read of ~/.ssh/id_rsa → check-shield exits 2 (LakshmanRekha credential path) |

| 10 | Loop Count Quarantine | loop_count > 50 → check-spawn quarantines agent (INF-KAV-014) |
Each test scenario is fully isolated: it creates its own HOME=/tmp/aegis-test-{name}, its own SQLite DB, its own config, and cleans up after itself. No test can contaminate another or the production database.
This pattern — governance infrastructure testing itself under its own governance — is described in: DOI 10.5281/zenodo.19625473
---
Why This Matters
This is an early signal of a structural shift: we're moving from SaaS to Agent-as-a-Service (AaaS).
SaaS: user clicks, one action = one action, cost predictable
AaaS: user instructs, one action = N agent spawns, cost unbounded
The infrastructure for governing this new execution model does not exist yet. AEGIS is one piece of that infrastructure.
Read the incident that spawned this project: docs/incident.md
---
On the category — Fin Operator and the case for open primitives
On 15 May 2026, Intercom (since renamed to Fin) launched Fin Operator, a Pro-tier subscription product whose "proposal system" puts a human approval gate between an AI agent and the systems it changes. Every modification appears as a diff. Nothing goes live without a click.
If you've read this far, you'll recognise the pattern — it is structurally the same as the KAVACH DAN Gate above. A pull-request-shaped intercept between agent intent and irreversible action.
AEGIS was born from a real $200 incident on 17 April 2026, about a month before Fin Operator's launch. The 7-axis HanumanG spawn check, the PRAMANA attestation chain, and the human-approval default-deny gate are the same architectural primitives that a $400M-ARR vendor has now validated as the category answer to agentic governance.
| | Fin Operator (2026-05-15) | AEGIS (2026-04-17) |

|---|---|---|

| Distribution | Pro-tier subscription, vendor-hosted | npm install @xshieldai/aegis, self-hosted |

| License | Proprietary | AGPL-3.0 (kernel) + BSL-1.1 → AGPL-3.0 in 4 years (EE) |

| Scope | Bound to the Fin platform | Vendor-neutral (Claude Code, OpenAI Codex, Cursor, custom) |

| Self-host | No | Yes — local-first by default |

| Audit | Trust the vendor | grep -rn "fetch(" src/ |

| Pricing | Pro tier + usage blocks | $0 OSS · BSL-1.1 EE free up to 3 concurrent sessions |
AEGIS does not compete with Fin Operator on customer-service workflows — that is a different product surface and not the contest. AEGIS competes with the idea that agent governance has to be a subscription you cannot read the source of.
The category becoming legitimate is welcome news. The primitive being open is the part worth choosing.
---
AGPL3 Core vs Enterprise Edition (EE)
KavachOS ships in two tiers. The kernel enforcement layer — the part that actually stops syscalls — is open source. You can audit what runs next to your production agents.
> Kernel enforcement (seccomp-bpf + Falco integration) is AGPL-3.0. You can audit what runs next to your production agents.
| Capability | Layer | License | Install |

|---|---|---|---|

| Budget governor (daily/session/agent) | KAVACH orchestrator | AGPL-3.0 | @xshieldai/aegis |

| DAN gate — WhatsApp / Telegram human-in-loop | KAVACH orchestrator | AGPL-3.0 | @xshieldai/aegis |

| permmask / classmask bitmask policy | KAVACH orchestrator | AGPL-3.0 | @xshieldai/aegis |

| Gate valve (throttle → crack → close) | KAVACH orchestrator | AGPL-3.0 | @xshieldai/aegis |

| HTTP Gate API (/api/v1/kavach/gate) | KAVACH orchestrator | AGPL-3.0 | @xshieldai/aegis |

| n8n community nodes (4 nodes) | KAVACH adapters | AGPL-3.0 | @xshieldai/n8n-nodes |

| LangChain callback adapter | KAVACH adapters | AGPL-3.0 | xshieldai-langchain |

| CA-006 LLM injection detection | KAVACH-POSTURE | AGPL-3.0 | @xshieldai/aegis |

| Basic HanumanG (7 delegation axes) | KAVACH-POSTURE | AGPL-3.0 | @xshieldai/aegis |

| seccomp-bpf profile generator | KAVACH-KERNEL | AGPL-3.0 | @xshieldai/aegis |

| Falco rule generator + event watcher | KAVACH-KERNEL | AGPL-3.0 | @xshieldai/aegis |

| SCMPACTNOTIFY supervisor (no-restart expansion) | KAVACH-KERNEL | AGPL-3.0 | @xshieldai/aegis |

| KavachOS CLI (kavachos run/audit/generate/rules) | KAVACH-KERNEL | AGPL-3.0 | @xshieldai/aegis |

| PRAMANA Merkle receipt chain + S3 anchoring | KAVACH orchestrator | BSL-1.1 → AGPL-3.0* | contact captain@ankr.in |

| HanumanG EE — posture registry + report cards | KAVACH-POSTURE | BSL-1.1 → AGPL-3.0* | contact captain@ankr.in |

| Dual-control L4 approval (two approvers) | KAVACH orchestrator | BSL-1.1 → AGPL-3.0* | contact captain@ankr.in |

| Slack notification channel | KAVACH orchestrator | BSL-1.1 → AGPL-3.0* | contact captain@ankr.in |

| Maritime injection signatures (AIS/NMEA/Modbus) | KAVACH-POSTURE | BSL-1.1 → AGPL-3.0* | contact captain@ankr.in |

| Multi-tenant session isolation | KAVACH orchestrator | BSL-1.1 → AGPL-3.0* | contact captain@ankr.in |

| Kubernetes sidecar + admission webhook | KAVACH infra | BSL-1.1 → AGPL-3.0* | Phase 6 build |

| EU AI Act evidence package | KAVACH compliance | BSL-1.1 → AGPL-3.0* | Phase 5 build |
* BSL-1.1 converts to AGPL-3.0 after 4 years. EE is distributed via private GitHub repo to design partners — not on npm. Contact captain@ankr.in.
Activate EE
EE distributed via private repo — not npm
Clone: git clone git@github.com:rocketlang/kavachos-ee.git  (design partner access)
export AEGISEELICENSEKEY=yoursigned_key
aegis status   # EE: active

---
What's new in v2.2.0 (2026-05-17) — Agentic Control Center
The dashboard at port 4850 now includes a consolidated cockpit page that

renders events from every @xshieldai/* primitive in one view.
New routes (all gated by the same session auth as existing dashboard

routes — opt-in via dashboard.auth.enabled: true in ~/.aegis/config.json,

which is the default after aegis init):
/control-center — single-page cockpit with 6 primitive zones
  + AOS-shaped strip (Boot Sequence · Primitive Process List · About this AEGIS)

  + PRAMANA OSS panel (renders existing src/kernel/merkle-ledger.ts)

  + EE-aware PRAMANA extra panel (renders only when @xshieldai/agent-kernel-ee is installed)
/agent/:id — per-agent timeline across all primitives, ordered by emission time
/suite — @xshieldai/* package inventory (from consumer's node_modules)
/api/acc/health — JSON event counts by primitive
/api/acc/events — JSON event query (by primitive or agent_id)
/api/acc/events/stream — SSE stream of new events (1.5s polling)
/api/suite/inventory — JSON inventory
To populate the cockpit, install the meta-package + call wireAllToBus():
npm install @xshieldai/aegis-suite

import { wireAllToBus } from '@xshieldai/aegis-suite';
wireAllToBus();
// → every @xshieldai/* primitive event now records to ~/.aegis/acc-events.db
// → visit http://localhost:4850/control-center

Same release wave shipped these v0.2.0 primitive packages with opt-in

setEventBus() API:

@xshieldai/aegis-guard

· @xshieldai/chitta-detect

· @xshieldai/lakshmanrekha

· @xshieldai/hanumang-mandate

· @xshieldai/aegis-suite v0.2.0 with wireAllToBus().
Phase-1 limits (v2.2.0):
SSE polling at 1.5s interval (not push-based) — fine for most cockpits, finer-grained push deferred to v2.3+
WAL cross-process visibility — if consumer + dashboard are in different processes, call handle.checkpoint() after batches OR rely on auto-checkpoint at ~1000 writes
PRAMANA EE panel detected via runtime require.resolve('@xshieldai/agent-kernel-ee') — invisible if EE not installed
Filter UI on /agent/:id deferred to v2.3 (timeline works without it)
Consumer needs @xshieldai/aegis-suite v0.2.0+ for wireAllToBus() — direct setEventBus() per-primitive also works
See DAILY-LOG.md for the 5-day build chronology.
---
Roadmap
[x] Phase 0 — Monitor + CLI + Dashboard + Max Plan + Codex support
[x] Phase 1 — KAVACH-KERNEL: seccomp-bpf + Falco + SCMPACTNOTIFY supervisor (v2.0.0)
[x] Phase 1A — Framework adapters: n8n (4 nodes) + LangChain callback (v2.0.0)
[x] Phase 2 — PRAMANA Merkle ledger + S3 anchoring (in OSS since v2.1.0 — corrected from earlier EE misclassification per OPEN-CORE-BOUNDARY.md v0.5)
[x] Phase 2a — Agentic Control Center (v2.2.0) — cockpit page + per-agent timeline + SSE + AOS-shaped polish
[ ] Phase 3 — L7 transparent proxy (TLS-terminating, zero agent code change)
[ ] Phase 4 — SPIFFE/mudrika identity (agent SVID, 55-min auto-rotate)
[ ] Phase 5 — EU AI Act evidence package (Aug 2, 2026 deadline)
[ ] Phase 6 — Kubernetes sidecar + DaemonSet (EE enterprise path)
---
Contributing
Issues and PRs welcome at github.com/rocketlang/aegis.
Especially wanted:
Parsers for new providers (Cursor, Copilot, Devin, Windsurf, custom agents)
Plan presets calibrated against real bills
Anomaly detection heuristics
Dashboard improvements
Documentation in other languages


---
License
AGPL-3.0 © Capt. Anil Sharma
OSS under AGPL-3.0 — copyleft applies to network deployments. Commercial license (SaaS, enterprise) available via captain@ankr.in.
---
Credits
Built from pain. The incident report behind AEGIS: docs/incident.md
> "Autonomy without control = financial risk."

Description

AEGIS

Answerability first

⚠️ Package rename (2026-05-17) — @rocketlang/ → @xshieldai/

🔍 Verification status (2026-05-17 IST)

The AEGIS / KavachOS / PRAMANA stack

Install in 3 steps

1. Install

2. Initialize (wires hooks into Claude Code automatically)

3. Check status

What it does — the KAVACH DAN Gate

Trust

The Problem

What AEGIS Provides

Six capabilities

Plans supported

Providers supported

Quick Start

Configure your plan

Start the services

Start monitor (watches session files)

Start dashboard

Open http://localhost:4850

Check status anytime

Commands

Claude Code Integration

1. Inline status line (see AEGIS inside Claude Code)

2. Budget enforcement (block tool calls over budget)

3. Dashboard (your own, local-first)

OpenAI Codex Integration

Terminal 1

Terminal 2

AEGIS sees both in one dashboard

Dashboard

→ http://localhost:4850

Public hosting

Configuration Reference

Plan presets (approximate)

Safety

Architecture

Components

Testing — AEGIS on AEGIS

Why This Matters

On the category — Fin Operator and the case for open primitives

AGPL3 Core vs Enterprise Edition (EE)

Activate EE

EE distributed via private repo — not npm

Clone: git clone git@github.com:rocketlang/kavachos-ee.git (design partner access)

What's new in v2.2.0 (2026-05-17) — Agentic Control Center

Roadmap

Contributing

License

Credits

⚠️ Package rename (2026-05-17) — `@rocketlang/` → `@xshieldai/`