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Local CLI for safer LLM workflows: redact code before pasting, generate verified obfuscated copies, enforce policy from your repo.

Project description

CLOAK

ci PyPI License: Apache 2.0 Python: 3.11+

Local CLI for safer LLM workflows. Redact code before pasting into ChatGPT or Claude. Generate verified obfuscated copies for sharing. Enforce policy from your repo.

[!IMPORTANT] CLOAK is alpha software in active development. APIs and policy format may change before 1.0. The three headline commands (scan, context, obfuscate) are functional for Python; JS/TS support arrives in Phases 3.5 and 5. See docs/BUILD_PLAN.md for the roadmap.

What CLOAK is

A command-line tool for developers who want to share code with LLMs without leaking proprietary IP or secrets. Runs locally — no server, no SaaS, no cloud — and is governed by a .cloakpolicy file checked into your repo, so engineering teams have an enforceable answer to "what code is allowed to reach an LLM?"

Three commands:

cloak scan ./repo
cloak context ./repo --out safe-context.md --copy
cloak obfuscate ./repo --out ./repo.cloaked --verify "pytest"
  • cloak scan — Find secrets and proprietary markers in code (wraps detect-secrets / gitleaks and layers your policy on top).
  • cloak context — Generate a redacted markdown view of a repo (function bodies hidden, signatures + docstrings kept) safe to paste into an LLM for architectural feedback. Use --strict to also alias enums and paraphrase docstrings.
  • cloak obfuscate — Produce a transformed copy of your code that still passes your test suite, for sharing with contractors or third parties. The --verify flag is the differentiator: if your tests don't pass against the transformed copy, the operation fails.

Why this exists

The "Shadow AI" problem is real: leadership says "don't paste code into ChatGPT" and developers do it anyway because they have deadlines. Existing solutions are either enterprise-grade network DLP (expensive, blunt, requires IT) or policy documents nobody reads.

CLOAK is the developer-side, repo-governed alternative. A CTO commits a .cloakpolicy once; developers run cloak context --copy before they paste; the right thing happens by default. Authority follows repo merge access — no separate permissions system to invent.

What CLOAK is NOT

Honest positioning matters in security tooling.

  • Not unbreakable. A motivated reader (human or LLM) given an obfuscated copy of your code can still extract logic. CLOAK reduces leak surface and creates friction; it does not provide cryptographic protection. Real protection comes from blocking, redacting, encrypting, compiling, or simply never sending the source.
  • Not a replacement for enterprise DLP. Network-layer enforcement (Lasso, Polymer, Cyberhaven, Prisma AIRS, etc.) operates at a different layer and is complementary. CLOAK lives in the developer's workflow, not the network egress.
  • Not a secret scanner from scratch. cloak scan wraps existing battle-tested OSS scanners (detect-secrets, gitleaks) and layers policy-aware rules on top. The reuse is intentional and disclosed.
  • Not magic for content the LLM has already seen. Once code is sent, it's sent. CLOAK helps before paste, not after.

Quickstart

The PyPI package is named cloak-cli (the simpler cloak name was already taken). The command on your $PATH is still just cloak.

# Install:
pip install cloak-cli

# Or from source:
git clone https://github.com/newtophilly/cloak.git
cd cloak
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

# First-time setup in a repo (one prompt, ~10 seconds):
cd your-repo
cloak policy init        # detects Python/JS/TS, scaffolds .cloakpolicy

# Then:
cloak scan .
cloak context . --copy                            # safe redacted markdown to clipboard
cloak obfuscate ./src --out ./src.cloaked --verify "pytest"

A real example

# 1. About to ask Claude for help on a sensitive file? Redact first:
$ cloak context src/pricing.py --copy
# Pasted into Claude: signatures + docstrings, bodies replaced with `...`,
# proprietary tables (UPPER_SNAKE = {...}) replaced with `... `.

# 2. Shipping a contractor a working module?
$ cloak obfuscate src/payments --out /tmp/payments.cloaked --verify "pytest tests/payments"
# Output is transformed AND verified — if your tests don't pass, exit 1.
# A cloak-manifest.json with sha256s + rename map sits in the output dir.

# 3. CI guardrail:
$ cloak scan . --json   # exits 1 if any secrets, JSON for parsing.

How .cloakpolicy works

The policy lives in a .cloakpolicy YAML file at the repo root. It's checked into git, versioned with your code, and reviewed via the same PR process as everything else. Authority = whoever has merge access.

version: 1

# Paths CLOAK treats with extra care
sensitive_paths:
  - "src/pricing/**"
  - "src/auth/**"

# Names that must NEVER be renamed by `cloak obfuscate`
public_api:
  - "QuoteEngine.calculate_quote"
  - "PaymentGateway.*"

# Custom secret-detection rules layered on top of the built-in scanner
secret_rules:
  - id: internal_api_endpoint
    pattern: 'https?://internal\..*\.corp\.example'
    severity: high

# Default behavior of `cloak context`
context_defaults:
  keep_docstrings: true
  redact_function_bodies: true
  alias_enums: false        # set true to behave like --strict by default

# Default behavior of `cloak obfuscate`
obfuscate_defaults:
  rename_private: true
  rename_public_api: false
  encode_strings: false
  profile: standard

A full annotated example is at .cloakpolicy.example.

Documentation

Integrations

CLOAK is designed to be called as a subprocess from other developer tools and AI agents. It runs cleanly headless: stable JSON output (--json), predictable exit codes, no interactive prompts.

  • fob — local AI workspace. When a fob project has a .cloakpolicy, fob can route context packets through cloak context to redact code before sending to an LLM. CLOAK works fine without fob; this is value-added, not load-bearing.
  • AI agents (Codex, Claude, custom) — see docs/AGENT_INTEGRATION.md for the agent-readable integration spec: when to call CLOAK, JSON output contracts, exit codes, and common patterns.

Status

Phase What Status
0 Validation experiment ✅ Done — strategy validated, two-tier redaction discovered
1 CLI scaffold + .cloakpolicy loader ✅ Done
2 cloak scan (wraps detect-secrets) ✅ Done
3 cloak context for Python ✅ Done
3.5 cloak context JS/TS via tree-sitter ✅ Done
4 cloak obfuscate Python with --verify ✅ Done (v1)
5 cloak obfuscate JS/TS via tree-sitter ✅ Done (v1)
6 cloak eval (LLM-prompt-based regression harness)

Contributing

Issues and PRs welcome. See CONTRIBUTING.md for development setup, code style, and how to report security issues.

License

Apache 2.0.

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