IAM Sentinel MCP Server
Enables auditors to scan cloud IAM policies for privilege-escalation paths, wildcards, and risky grants directly within Cursor or Claude Code, using a deterministic rule engine that runs entirely on local infrastructure.
README
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<h1 align="center">🛡️ IAM Sentinel</h1>
<p align="center"> <b>Air-gapped, deterministic cloud IAM privilege-escalation scanner — AWS · Azure · GCP.</b><br> Runs 100% on your own metal. Plugs into Cursor / Claude Code via MCP. Zero data egress. </p>
<p align="center"> <img alt="license" src="https://img.shields.io/badge/license-BSL%201.1-blue"> <img alt="docker" src="https://img.shields.io/badge/docker-compose-2496ED?logo=docker&logoColor=white"> <img alt="clouds" src="https://img.shields.io/badge/clouds-AWS%20%7C%20Azure%20%7C%20GCP-orange"> <img alt="offline" src="https://img.shields.io/badge/network-air--gapped-10b981"> <img alt="tests" src="https://img.shields.io/badge/tests-68%20passing-brightgreen"> <img alt="ci" src="https://img.shields.io/badge/CI-PR%20gate%20%2B%20SARIF-6d7dff"> </p>
<p align="center"> <a href="https://iam-sentinel-site.vercel.app">Website</a> · <a href="#quickstart">Quickstart</a> · <a href="INSTALL.md">Install (Mac/Win/Linux/WSL)</a> · <a href="#pricing">Pricing</a> </p>
Why
Cloud IAM scanners (Wiz, Snyk, GitHub Advanced Security) send your policies to their cloud.
Regulated teams can't do that. IAM Sentinel finds privilege-escalation paths, wildcards,
PassRole/roleAssignment abuse, public bindings, and data-exfil grants with a deterministic
rule engine — reproducible and auditable, not an LLM guess — entirely on your infrastructure.
- 🔒 Air-gapped — no telemetry, no outbound calls (except an optional local model).
- 🎯 Deterministic — version-stamped findings from a rule engine, not hallucinations.
- 🔌 In your IDE — native stdio MCP server for Cursor / Claude Code.
- 🧾 Auditable — every scan persisted with actor, timestamp, SHA-256, and rule-pack version.
- 🖥️ Runs anywhere — CPU-only core; a GPU is only for the optional written remediation.
Quickstart
git clone https://github.com/Pratikchandrathakur/IAM-Sentinel && cd iam-sentinel
cp .env.example .env # set API keys (Community tier needs no license)
docker compose up -d --build
open http://127.0.0.1:8080 # dashboard · API at /api/... · health at /api/health
Audit a policy (provider auto-detected):
curl -s http://127.0.0.1:8080/api/audit/iam -H "X-API-Key: $KEY" \
-H "Content-Type: application/json" \
-d '{"policy_json":"{\"Statement\":[{\"Effect\":\"Allow\",\"Action\":\"*\",\"Resource\":\"*\"}]}"}' | jq
No GPU / macOS? Set LLM_NARRATIVE_ENABLED=false — you still get every deterministic finding.
Full per-OS steps in INSTALL.md.
Use it inside your IDE (MCP)
{ "mcpServers": { "iam-sentinel": {
"command": "python3", "args": ["/abs/path/to/iam-sentinel/mcp_stdio.py"],
"env": { "AUTH_ENABLED": "false", "LLM_NARRATIVE_ENABLED": "false" }
}}}
Then ask your assistant: "Audit this IAM policy with iam-sentinel."
CI/CD guardrails — block privilege escalation on every PR
Scan the IAM inside a Terraform plan (or raw policy files) and fail the build when a new escalation path appears. Findings show inline on the PR via SARIF. No server needed.
# .github/workflows/iam-guardrails.yml (see examples/github-actions/)
- run: terraform show -json tf.plan > plan.json
- uses: Pratikchandrathakur/IAM-Sentinel@v1
with: { tfplan: plan.json, fail-on: HIGH }
Or run the gate locally / in any CI (pure stdlib, offline):
python3 guardrails.py --tfplan plan.json --fail-on HIGH # exit 1 = blocking findings
python3 guardrails.py policies/*.json --format sarif > iam.sarif
It extracts IAM from Terraform plans (AWS aws_iam_policy/roles, Azure azurerm_role_definition,
GCP custom roles/bindings) — no HCL parsing, using the resolved plan JSON.
No model required. Every scan returns a full deterministic remediation report (fixes + least-privilege skeleton) with zero external services. The optional local LLM is pure polish. Custom rules are a config drop-in — see
custom_rules.example.json(no code change).
What it detects
- AWS — 19 escalation techniques (Rhino/PMapper):
AttachUserPolicy,PutRolePolicy,CreateAccessKey,PassRole+compute,UpdateAssumeRolePolicy, …; wildcards,NotActiontraps, wildcard principals, unconditionedAssumeRole, data-exfil grants. - Azure —
roleAssignments/write,elevateAccess,Microsoft.Authorization/*, wildcard actions, scope breadth. - GCP — primitive roles,
allUsersbindings,setIamPolicy/serviceAccountTokenCreator/actAs.
Pricing
Open-core. Run it free; upgrade for seats, history, and enterprise controls (offline-licensed).
| Tier | Price | Seats | Scans/mo | Adds |
|---|---|---|---|---|
| Community | Free | 1 | 100 | AWS/Azure/GCP · MCP · audit trail |
| Team | $199/mo | 10 | 5,000 | Remediation diff |
| Enterprise | $4,999/yr | ∞ | ∞ | SSO/RBAC · TLS · SLA |
See the website or email krisprogrammer1@gmail.com for a pilot.
Tests
python3 tests/test_iam_engine.py # + test_multicloud / test_store / test_mcp / test_auth / ...
License
Business Source License 1.1 (see LICENSE). Source is open; Community use
is free (single user / evaluation). Team, CI/CD, and organization-wide production use
requires a commercial subscription — contact krisprogrammer1@gmail.com. Converts to
Apache-2.0 on 2030-07-25. You may not resell it or offer it as a competing hosted service.
<p align="center"><i>⭐ If this is useful, star the repo — it helps a lot.</i></p>
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