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Keep API secrets out of plaintext config: layered .ranbval* env files, decrypt vault tokens only when used, with built-in repo-allowlist enforcement and automatic usage telemetry to the Live Monitor—minimal deps, your own HTTP/SDK stack.

Project description

PyPI Python License: MIT

Ranbval SDK v1.2.0

Keep API secrets out of plaintext config. Encrypt them in the Ranbval dashboard, store encrypted tokens in .ranbval files, decrypt only at runtime — AES-256-GCM with PBKDF2 key derivation, no plaintext ever touches source control.

pip install ranbval-sdk

Why Ranbval Exists

With so many LLM APIs and third-party services in use today, managing secrets has become a real operational problem. Someone shares an API key, it gets copied, forwarded, and committed — and suddenly the bill arrives with no way to trace which repo or person burned the tokens.

Problem Ranbval Solution
API keys committed to Git Encrypted .ranbval* files — plaintext never touches source control
Keys copied and shared freely Repo allowlist — enforced by the control plane; an unauthorized repo cannot decrypt, and it can't be skipped from the client
No idea who used what, when Live Monitor — every decrypt is reported automatically with machine, repo, model, tokens
load_dotenv() scattered everywhere One call: load_ranbval() — layered, mode-aware, zero side effects on import

Quick Start

from ranbval_sdk import load_ranbval, decrypt_key
import os, openai

# 1. Load encrypted config from .ranbval files (no network, no decryption)
load_ranbval()

# 2. Decrypt a vault token — returns a SecretString, never printable.
#    This also auto-reports the usage to your Live Monitor (no extra code).
api_key = decrypt_key("OPENAI_API_KEY")

# 3. Pass directly to the SDK — value is never exposed in logs or prints
client = openai.OpenAI(api_key=api_key.use())

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
)

.ranbval.local (never commit this file):

RANBVAL_PROJECT_SECRET=your_dashboard_project_secret
OPENAI_API_KEY=ranbval.4ii0a022aa.p1GOZ...ahsan

Module Reference

Symbol Description
load_ranbval() Merges layered .ranbval* files into os.environ
safe_decrypt() Decrypts a vault token string → SecretString
decrypt_key() Reads an env var and decrypts it in one call
SecretString Wrapper that blocks all display paths — value only via .use()
secure_client() Wrap a third-party SDK class for auto-decrypt + telemetry
build_secure_client() Same as secure_client() but returns a subclass instead of an instance
proxy_request() Route an HTTP request through the Ranbval proxy
emit_telemetry() Record a custom usage event (basic usage is auto-reported on every decrypt_key())
get_audit_log() Return the in-process audit log list
clear_audit_log() Clear the in-process audit log
get_project_key() Read RANBVAL_PROJECT_SECRET from env
find_ranbval_file() Locate the nearest .ranbval* file on disk
find_ranbval_directory() Locate the config root directory
resolve_ranbval_mode() Determine the active mode from env/args

Package Layout

Everything is organized by concern. You only import from the top level (from ranbval_sdk import …); the table shows where each piece lives.

ranbval_sdk/
├── __init__.py          # the public API (re-exports everything below)
├── exceptions.py        # RanbvalError hierarchy
├── py.typed             # ships type information (PEP 561)
├── config/              # your .ranbval configuration surface
│   ├── loader.py        #   load_ranbval, find_*, resolve_ranbval_mode, get_project_key
│   └── access.py        #   Vault, env, inject, secrets, iter_secrets, Secret, SecretConfig
├── crypto/              # cryptography & sealed secrets
│   ├── cipher.py        #   AES-256-GCM decrypt + project-secret resolution
│   ├── secret_string.py #   SecretString — the sealed, never-printable value
│   ├── audit.py         #   in-memory log of every .use()
│   └── repo_policy.py   #   git-remote provenance enforcement (the decrypt gate)
├── telemetry/           # usage reporting to the Live Monitor
│   ├── client.py        #   emit_telemetry / aemit_telemetry
│   └── decorators.py    #   @track / tracked()
├── integrations/        # calling your vendor SDKs safely
│   ├── factory.py       #   secure_client
│   ├── universal.py     #   build_secure_client
│   └── proxy.py         #   proxy_request / aproxy_request (key never leaves the server)
└── _internal/           # private cross-cutting utilities
    ├── defaults.py      #   shared constants
    └── transport.py     #   HTTPS via urllib + certifi

Function Reference

load_ranbval()

Loads configuration from .ranbval* files into os.environ. No network calls, no decryption, zero side effects on import.

from ranbval_sdk import load_ranbval

load_ranbval()                              # auto-discover from cwd upward
load_ranbval(mode="production")             # force a specific mode
load_ranbval(start="/path/to/project")      # start search from a custom directory
load_ranbval("/absolute/path/to/file")      # single file, skip layer discovery
load_ranbval(override=True)                 # file values overwrite existing os.environ

How it finds files

Walks from cwd upward until it finds a directory containing .ranbval or any .ranbval.* file. That becomes the config root.

Merge order (later file wins for duplicate keys):

.ranbval                   ← shared base
.ranbval.{mode}            ← e.g. .ranbval.production
.ranbval.local             ← machine-only, add to .gitignore
.ranbval.{mode}.local      ← highest priority

Mode resolution order:

  1. load_ranbval(mode="...") explicit argument
  2. RANBVAL_ENV environment variable
  3. ENVIRONMENT environment variable
  4. ENV environment variable
  5. Default: development

Returns: True if at least one file was read, False if none found.

Example .ranbval file:

# Plain values — safe to commit
APP_NAME=my-app
DATABASE_URL=postgresql://localhost/mydb

# Encrypted vault token — generated in the Ranbval dashboard
OPENAI_API_KEY=ranbval.4ii0a022aa.p1GOZ...ahsan

safe_decrypt()

Decrypts a ranbval.* vault token string using AES-256-GCM with PBKDF2 key derivation.

from ranbval_sdk import load_ranbval, safe_decrypt
import os

load_ranbval()

secret = safe_decrypt(
    os.environ["OPENAI_API_KEY"],          # the ranbval.* token string
    os.environ["RANBVAL_PROJECT_SECRET"],  # your project secret
)

client = openai.OpenAI(api_key=secret.use())

Returns: a SecretString — the decrypted value is never accessible via print, str, repr, f-strings, or logs.

print(secret)        # → [ranbval:secret]
str(secret)          # → [ranbval:secret]
f"key={secret}"      # → key=[ranbval:secret]
repr(secret)         # → SecretString(***)
len(secret)          # → 164  (safe — reveals only length)

# Only correct usage:
client = openai.OpenAI(api_key=secret.use())
headers = {"Authorization": f"Bearer {secret.use()}"}

Raises:

  • RepoNotAllowedError (a PermissionError) — this Git repo is not in the allowed list
  • RanbvalDecryptError (a ValueError) — wrong project secret or corrupted token

The repo allowlist is enforced by the control plane and cannot be skipped on the client — there is no local bypass flag. Manage the allowed repositories from the Ranbval dashboard.


decrypt_key()

Convenience wrapper: reads an env var and decrypts it in one call. The project secret is read from RANBVAL_PROJECT_SECRET automatically.

from ranbval_sdk import load_ranbval, decrypt_key

load_ranbval()

# Reads os.environ["OPENAI_API_KEY"] and os.environ["RANBVAL_PROJECT_SECRET"]
api_key = decrypt_key("OPENAI_API_KEY")

client = openai.OpenAI(api_key=api_key.use())

This is the recommended pattern for most applications — it reduces boilerplate and keeps the project secret out of your application code. Each call also auto-reports the usage to the Live Monitor.

Raises: RanbvalConfigError (env var not set / no project secret), RanbvalDecryptError (wrong secret or corrupt token), RepoNotAllowedError (repo not in the allowlist) — all subclasses of RanbvalError, and each also a subclass of the built-in it replaces (ValueError / PermissionError).


SecretString

A string wrapper that makes it impossible to accidentally expose a secret through print, logging, f-strings, or repr.

from ranbval_sdk import SecretString

# Created automatically by safe_decrypt() / decrypt_key()
# — but you can also wrap your own values:
secret = SecretString("sk-proj-super-secret-key", label="openai")

print(secret)           # [ranbval:secret]
repr(secret)            # SecretString(***)
f"key={secret}"         # key=[ranbval:secret]
str(secret)             # [ranbval:secret]
len(secret)             # 26  ← safe

# Only way to get the real value:
real_value = secret.use()

Why this matters:

# Old way — key leaks in logs/stdout
api_key = os.environ["OPENAI_KEY"]
print(f"Using key: {api_key}")           # key printed to console/logs

# Ranbval way — impossible to leak accidentally
secret = decrypt_key("OPENAI_KEY")
print(f"Using key: {secret}")            # → Using key: [ranbval:secret]
Method / Property Description
.use() Returns the raw string — the only access point
len(secret) Length of the secret (safe to log)
.label Optional name set at creation
== Compares two SecretString values securely

secure_client() / build_secure_client()

Wrap a third-party SDK class so it auto-decrypts the key and fires telemetry on every call.

from ranbval_sdk import load_ranbval, secure_client
import openai

load_ranbval()

# Returns an openai.OpenAI instance with auto-decrypt + telemetry
client = secure_client(
    openai.OpenAI,
    env_var="OPENAI_API_KEY",
    key_kwarg="api_key",
    method_path_to_patch="chat.completions.create",
)

# Use exactly like openai.OpenAI — telemetry fires automatically
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
)

build_secure_client() returns a subclass instead of an instance — use when you need to instantiate multiple times or pass to a factory:

from ranbval_sdk import build_secure_client
import anthropic

SecureAnthropic = build_secure_client(
    anthropic.Anthropic,
    env_var="ANTHROPIC_API_KEY",
    key_kwarg="api_key",
)

client = SecureAnthropic()

emit_telemetry()

Posts a usage event to the Ranbval Live Monitor.

You usually don't need to call this. decrypt_key() already reports usage to the Live Monitor automatically — and does it efficiently: the first use of a credential is sent immediately, then repeats are counted locally and flushed as one aggregated event (~every 30s and at process exit) carrying an item_count weight. So a hot loop that decrypts the same key 10,000× produces a handful of events, not 10,000 POSTs. Call emit_telemetry() only to record a richer custom event — e.g. model name and token counts after an LLM call.

from ranbval_sdk import emit_telemetry

emit_telemetry(
    vault_token_env="OPENAI_API_KEY",   # env var holding a ranbval.* token
    model_used="gpt-4o",
    prompt_tokens=512,
    completion_tokens=128,
    event_kind="llm.chat",
    background=True,                    # non-blocking daemon thread
)

Or pass the salt directly if you have it:

emit_telemetry(
    client_salt="4ii0a022aa",
    model_used="stripe.charge",
    background=True,
)
Parameter Type Description
vault_token_env str Env var name holding a ranbval.* token — salt extracted automatically
client_salt str Use instead of vault_token_env if you already have the salt
model_used str Label shown in the dashboard (e.g. "gpt-4o", "stripe.charge")
prompt_tokens int Input tokens (0 if not an LLM call)
completion_tokens int Output tokens (0 if not an LLM call)
event_kind str Event category (e.g. "llm.chat", "custom.request")
item_count int Aggregation weight — how many actual uses this event represents (default 1)
roundtrip_ms float Client-measured decrypt/round-trip latency, if you want to report it
background bool True = fire-and-forget in a daemon thread
host_url str Override RANBVAL_HOST for this call

If no client_salt can be resolved the call is a silent no-op — safe to call even with plain (non-ranbval) keys.

What each event sends. Only a non-reversible token salt (never the plaintext secret) plus operational metadata: SDK/Python version and platform, transport scheme, git branch and git config user.email (developer identity), a coarse timezone geo hint, decrypt latency, and a hashed, non-reversible device_id (a truncated SHA-256 of the machine ID — the raw MAC is never sent). The device_id is the signal the control plane uses for leak detection: the same credential appearing on multiple distinct devices/IPs raises an alert in the Live Monitor.


proxy_request()

Route an outbound HTTP request through the Ranbval secure proxy. The real API key is decrypted server-side and never returned to the caller. Raises ProxyError on failure.

from ranbval_sdk import load_ranbval, proxy_request, ProxyError
import os

load_ranbval()

try:
    result = proxy_request(
        token=os.environ["OPENAI_API_KEY"],        # ranbval.* vault token
        target_url="https://api.openai.com/v1/chat/completions",
        method="POST",
        inject_as="bearer",                         # Authorization: Bearer <secret>
        body={"model": "gpt-4o", "messages": [{"role": "user", "content": "Hello"}]},
    )
    print(result["status"])   # HTTP status from the target
    print(result["body"])     # parsed JSON response
except ProxyError as e:
    print(f"Proxy failed: {e}")

Inject modes: "bearer" · "basic" · "header:X-Api-Key" · "query:api_key"

Return value: dict with keys status (int), ok (bool), body (parsed JSON or str), headers (dict).

ProxyError is raised when the proxy rejects the request (bad credentials, unknown token) or is unreachable.


get_audit_log() / clear_audit_log()

The SDK records every decrypt and telemetry event in an in-process audit log. Useful for testing and compliance verification.

from ranbval_sdk import load_ranbval, decrypt_key, get_audit_log, clear_audit_log

load_ranbval()
decrypt_key("OPENAI_API_KEY")

log = get_audit_log()
# [{"label": "OPENAI_API_KEY", "timestamp": 1716000000.0, "caller": "app.py:12"}]

clear_audit_log()
assert get_audit_log() == []

.ranbval File Format

.ranbval files follow the same KEY=VALUE format as .env files. Lines starting with # are comments. Blank lines are ignored.

# Plain value — stored and used as-is
APP_NAME=my-app
DATABASE_URL=postgresql://localhost/mydb

# Encrypted vault token — generated in the Ranbval dashboard
# Format: ranbval.<client_salt>.<aes-gcm-blob>.<label>
OPENAI_API_KEY=ranbval.4ii0a022aa.p1GOZtBx...3Kq==.ahsan
STRIPE_SECRET_KEY=ranbval.7cc2b931ff.xYZabc...Pq==.stripe

Token format: ranbval.<client_salt>.<aes-gcm-blob>.<label>

Part Description
client_salt 10-character identifier used for session lookup and telemetry
aes-gcm-blob IV + ciphertext, base64url-encoded
label Human-readable tag shown in the dashboard

File Layout Example

my-project/
├── .ranbval                   ← shared defaults (safe to commit if no secrets)
├── .ranbval.production        ← production overrides (safe to commit)
├── .ranbval.local             ← machine secrets (gitignore this)
├── .ranbval.production.local  ← production + local overrides (gitignore this)
└── src/
    └── main.py

.gitignore:

.ranbval.local
.ranbval.*.local

.ranbval (committed, no secrets):

APP_NAME=my-app
RANBVAL_ENV=development

.ranbval.production (committed, encrypted tokens only):

OPENAI_API_KEY=ranbval.4ii0a022aa.p1GOZtBx...3Kq==.ahsan

.ranbval.local (never committed):

RANBVAL_PROJECT_SECRET=your_project_secret_from_dashboard

Environment Variables

Variable Default Description
RANBVAL_HOST https://api.ranbval.com Ranbval API base URL
RANBVAL_ENV development Active mode for layered config
RANBVAL_PROJECT_SECRET (required) Project secret for safe_decrypt() / decrypt_key()
RANBVAL_TELEMETRY_DEBUG 0 1 = print telemetry errors to stderr

Repo-allowlist enforcement and usage telemetry are always on and controlled by the Ranbval dashboard — there is no client-side flag to skip either. decrypt_key() reports each use to the Live Monitor automatically; call emit_telemetry() only when you want to record richer custom events.


n8n — HTTP Request + Telemetry

No Python needed. Use two HTTP Request nodes in your n8n workflow:

Node 1 — Your API call (OpenAI, Stripe, etc.) via HTTPS.

Node 2 — Telemetry log to Ranbval:

POST https://api.ranbval.com/api/telemetry
Content-Type: application/json

{
  "client_salt": "{{ $json.client_salt }}",
  "machine_name": "n8n",
  "repo_path": "{{ $workflow.name }}",
  "model_used": "openai.chat",
  "prompt_tokens": 0,
  "completion_tokens": 0,
  "security": {
    "event_kind": "custom.request",
    "transport": "https",
    "client_platform": "n8n"
  }
}

Extract client_salt from a ranbval.* token in a Code node:

const token = $json.apiKey;
const salt = token.startsWith("ranbval.") ? token.split(".")[1] : null;
return [{ json: { client_salt: salt } }];

Security Architecture

Your Code
    │
    ├── load_ranbval()          Reads .ranbval* files → os.environ (no network, no decrypt)
    │
    ├── decrypt_key("ENV_VAR")
    │       │
    │       ├── 1. Repo allowlist check  →  GET /api/public/repo-policy  (mandatory, server-controlled)
    │       ├── 2. AES-256-GCM decrypt   →  SecretString (value sealed, never printable)
    │       └── 3. Auto usage report     →  POST /api/telemetry → Live Monitor (automatic)
    │
    └── secret.use()            Only access point — pass directly to SDK / headers

AES-256-GCM encryption with PBKDF2 key derivation (100,000 iterations). The project secret never leaves your environment — the decryption itself happens on your machine. The repo allowlist check and usage reporting are always on and governed by the Ranbval control plane; there is no client-side flag to bypass either.

Network requirement: because the allowlist is verified server-side on every decrypt, resolving a vault token requires connectivity to the Ranbval control plane — the same as any cloud secret manager (HashiCorp Vault, Doppler, AWS/GCP Secrets Manager). Plain (non-ranbval.*) values in your .ranbval files resolve fully offline.


License

MIT — see LICENSE.


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