SkyClaw Adds Encrypted Chat-Based API Key Setup for AI Agents

✍️ OpenClawRadar📅 Published: March 11, 2026🔗 Source
SkyClaw Adds Encrypted Chat-Based API Key Setup for AI Agents
Ad

SkyClaw introduces a method for securely setting up API keys through chat interfaces without exposing them to LLMs or messaging platforms. The system addresses the workflow friction of traditional self-hosted agents that require SSH access, config file edits, and service restarts to change keys.

How It Works

The solution has two security layers:

  • Layer 1 — System intercept: Key commands (/addkey, /keys, /removekey) and encrypted blobs (starting with enc:v1:) are caught in main.rs before messages reach the agent. The Rust process decrypts, validates, and saves to the vault, keeping the LLM completely uninvolved in credential operations.
  • Layer 2 — OTK encryption: Uses URL fragments (#) that are never sent to servers per RFC 3986. The flow: bot sends setup.page/#one-time-256bit-key, browser encrypts API key locally using AES-256-GCM with WebCrypto, user pastes encrypted blob back in chat, bot decrypts at system layer and saves, then burns the one-time key.

Security Results

  • Messaging platforms see only ciphertext (useless without OTK)
  • The LLM sees nothing (intercepted before agent loop)
  • GitHub Pages sees only GET /setup
  • Works on any platform that sends/receives text
Ad

Comparison with Other Projects

The source identifies limitations in current solutions:

  • OpenClaw: Uses config files, env vars, CLI wizard, optional external secret managers. GitHub issue #11829 states: "OpenClaw currently has multiple vectors where API keys can leak to the LLM or be exposed in chat." Issue #19137 documents config.get leaking API keys into session transcript JSONL files.
  • OpenFang (Rust): Uses env vars referenced in config.toml (api_key_env = "ANTHROPIC_API_KEY"), CLI init wizard, dashboard UI. Has strong at-rest security with Zeroizing<String> and AES-256-GCM credential vault, but no secure key ingestion from chat.
  • NanoClaw: Uses ANTHROPIC_API_KEY or CLAUDE_CODE_OAUTH_TOKEN env vars set during /setup skill. In Docker Sandbox mode, proxy-based system substitutes sentinel values, but still no encrypted key transit through messaging.
  • PicoClaw: Uses ~/.picoclaw/config.json with env var overrides (PICOCLAW_PROVIDERS_*). Issue #972 documents subagent credential leakage when self-healing logic reads config.json and echoes raw API keys into chat logs.

The fundamental problem, as OpenClaw's issue #7916 states: "keys must be in plain text for [the system] to operate." External secret managers defer plaintext exposure to runtime, but no one encrypts the transit.

Technical Details

URL fragments work because per RFC 3986, # and everything after it is never sent to the server in HTTP requests, not included in the Referer header, not logged by CDNs/proxies/web servers, and processed entirely client-side. GitHub Pages receives GET /setup with zero knowledge of the OTK.

The message handler in main.rs has strict priority order: key commands and encrypted blobs are matched first and return immediately, never falling through to the agent. The LLM only receives messages that pass all checks. On the output side, a SecretCensorChannel wraps every outbound message.

📖 Read the full source: r/openclaw

Ad

👀 See Also

Ouroboros Adds PM Interview Mode for Claude Code to Bridge Spec Gap
Tools

Ouroboros Adds PM Interview Mode for Claude Code to Bridge Spec Gap

Ouroboros now includes a PM mode that runs a guided interview before handing off to Claude Code, asking questions like what problem is being solved, who it's for, and what constraints matter. The output is a PRD/PM document with goal, user stories, constraints, success criteria, assumptions, and deferred items.

OpenClawRadar
Building a Persistent AI Knowledge Infrastructure with OpenClaw
Tools

Building a Persistent AI Knowledge Infrastructure with OpenClaw

A developer built 'Brain'—a central knowledge service with local RAG, multi-agent coordination, and a typed plugin system—to solve the statelessness problem in AI setups. The system runs entirely on local hardware using Ollama, Postgres, MongoDB, Qdrant, and Memgraph.

OpenClawRadar
Benchmark Results: 6 Low-Cost Models vs. Claude Sonnet 4.6 for OpenClaw Orchestration
Tools

Benchmark Results: 6 Low-Cost Models vs. Claude Sonnet 4.6 for OpenClaw Orchestration

A developer tested six cheaper AI models against Claude Sonnet 4.6 as the main orchestrator for an OpenClaw setup. Only o4-mini matched Sonnet's perfect score, while others failed on critical judgment tasks like file inspection and delegation.

OpenClawRadar
Four Free Claude Code Skills for Prompt Clarity, Tutorials, and Bug Hunting
Tools

Four Free Claude Code Skills for Prompt Clarity, Tutorials, and Bug Hunting

Four Apache 2.0, no-paid-tier Claude Code skills: prompter (prompt rewriting), tutorial-creator (annotated code walkthroughs), bug-echo (post-fix anti-pattern sweep), and bug-prospector (pre-release audit with 7 analysis lenses).

OpenClawRadar