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      GreatApe42069

      Safety Report

      Neverforget

      @GreatApe42069

      Automates Sovereign Local Vector Memory and Gemma-300M Embeddings. Manage local vector embeddings, model configuration, and memory health monitoring without...

      403Downloads
      3Installs
      2Stars
      5Versions
      Workflow Automation8,822Browser Automation5,375Search & Retrieval4,480AI & Machine Learning3,159

      Security Analysis

      high confidence
      Suspicious0.08 risk

      The skill's behavior largely matches a local-memory installer, but it requests very broad filesystem/network reach, writes to global OpenClaw config and user files, and contains contradictory guidance (symlink vs. no-symlink) — the footprint is larger than many users would expect and deserves careful review before install.

      Feb 18, 20265 files5 concerns
      Purpose & Capabilitynote

      The declared purpose (setup local embeddings with node-llama-cpp and Gemma-300M) matches the instructions to install node-llama-cpp, set the local provider, and download a Hugging Face model. However the package.json and SKILL.md ask for broad filesystem indexing (~/) and network access (huggingface, pnpm, npm registry, and an hf-mirror), which is functionally plausible for a full 'sovereign memory' system but is broad in scope and higher-privilege than many users would expect for a single skill.

      Instruction Scopeconcern

      Runtime instructions include writing/appending HEARTBEAT.md into ~/.openclaw/workspace, changing global OpenClaw config (agents.defaults.memorySearch.*), running openclaw gateway restart, and triggering openclaw memory index which will crawl user files. The skill's docs/templating give mixed guidance about symlinks (one file warns 'Do not use symlinks', another encourages creating symlinks to include external directories), which is an internal inconsistency that could dramatically expand what gets indexed. These instructions perform persistent, system-wide changes and can cause broad data collection if allowed.

      Install Mechanismnote

      This is instruction-only (no install spec), so nothing is automatically written by a packaged installer. The suggested install uses pnpm to add node-llama-cpp (standard package manager usage) and relies on downloading a model from Hugging Face via the provider path. No arbitrary IP/paste/shortener URLs are present, but package.json lists an additional network entry 'hf-mirror.com' (third-party mirror) — worth verifying the mirror's trustworthiness.

      Credentialsconcern

      The skill declares no required environment variables but the included openclaw manifest requests wide filesystem permissions (~/, ~/.openclaw, etc.) and network access to package/model registries. Indexing the entire home directory is disproportionate for many users because it can include secrets and private data; the manifest attempts to exclude common secret stores (.ssh, .aws, .env, .gnupg) but exclusion lists are error-prone and may miss other sensitive files. The ability to follow symlinks (documented elsewhere) could further expand access.

      Persistence & Privilegeconcern

      The instructions modify global OpenClaw configuration keys (agents.defaults.memorySearch.*), append content to the user's workspace HEARTBEAT.md, restart the gateway, and trigger indexing. Changing global agent defaults and restarting the gateway are system-wide operations that affect other agents and the host environment — this is beyond a purely local skill's internal scope and increases blast radius if misconfigured.

      Guidance

      Before installing, carefully consider the following: (1) This skill intends to index large parts of your home directory (~) and will change global OpenClaw memory settings and restart the gateway — review and backup ~/.openclaw/openclaw.json first. (2) Confirm the exclusion rules cover all places you consider sensitive; exclusions like **/.ssh/**, **/.aws/** and **/.env** are present but may be incomplete for your environment. (3) The skill will append a HEARTBEAT.md into your workspace and may follow symlinks (different files give contradictory guidance) — do not create symlinks to sensitive external stores if you want them excluded. (4) The install path uses pnpm and downloads a model from Hugging Face (and references an hf-mirror); verify network endpoints and mirror trust before allowing downloads. (5) Prefer running this skill first in an isolated account, container, or VM to observe behavior and disk usage (model downloads can be large). (6) When prompted to run the auto-install script, review the commands line-by-line and decline if you do not accept global config changes or broad indexing. If you want to proceed safely: restrict the filesystem permissions in package.json to only the specific project paths you need, remove symlink recommendations, and test indexing on a small sample directory first.

      Latest Release

      v1.0.4

      - Hardened exclusion rules for memory indexing by skipping secret directories such as .ssh, .aws, and .env - Improved compliance with ClawHub security audit requirements - Documentation and install script updated to reflect new exclusion logic - No changes to functional code; update focused on enhanced security configuration

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      Published by @GreatApe42069 on ClawHub

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