Openclaw Traffic Guardian logo

Openclaw Traffic Guardian

OrganizationPopular
prompt-security
openclaw-traffic-guardian

OpenClaw runtime traffic monitoring baseline for opt-in HTTP/HTTPS proxy inspection, egress detection, inbound injection detection, and social-account policy review.

Overview

Publisherprompt-security
Repositoryclawsec
Skill nameopenclaw-traffic-guardian
Stars
1.1K
Forks
112
Bundled files
3
LicenseAGPL-3.0-or-later
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by prompt-security on GitHub. Read the source before you install it.

Installation

Install the Openclaw Traffic Guardian AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/prompt-security/clawsec/tree/main/skills/openclaw-traffic-guardian
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/prompt-security/clawsec.git /tmp/clawsec
mkdir -p .claude/skills
cp -r /tmp/clawsec/skills/openclaw-traffic-guardian .claude/skills/openclaw-traffic-guardian
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openclaw Traffic Guardian in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Openclaw Traffic Guardian on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Openclaw Traffic Guardian is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OpenClaw Traffic Guardian

This is a baseline specification skill. It intentionally does not ship a proxy or runtime implementation yet.

Vercel Skills Installation

Install with the Vercel Skills CLI for this harness:

bash
npx skills add prompt-security/clawsec --skill openclaw-traffic-guardian -a openclaw -y

Release Artifact Verification

For standalone installs, verify the signed release manifest before trusting SKILL.md, skill.json, or the archive. The skill.json file is the package metadata/SBOM source, and the release pipeline signs checksums.json with the ClawSec release key.

bash
set -euo pipefail

SKILL_NAME="openclaw-traffic-guardian"
VERSION="0.0.1-beta5"
REPO="prompt-security/clawsec"
TAG="${SKILL_NAME}-v${VERSION}"
BASE="https://github.com/${REPO}/releases/download/${TAG}"
ZIP_NAME="${SKILL_NAME}-v${VERSION}.zip"
TMP_DIR="$(mktemp -d)"
trap 'rm -rf "$TMP_DIR"' EXIT

RELEASE_PUBKEY_SHA256="711424e4535f84093fefb024cd1ca4ec87439e53907b305b79a631d5befba9c8"

curl -fsSL "$BASE/checksums.json" -o "$TMP_DIR/checksums.json"
curl -fsSL "$BASE/checksums.sig" -o "$TMP_DIR/checksums.sig"
curl -fsSL "$BASE/signing-public.pem" -o "$TMP_DIR/signing-public.pem"
curl -fsSL "$BASE/$ZIP_NAME" -o "$TMP_DIR/$ZIP_NAME"
curl -fsSL "$BASE/SKILL.md" -o "$TMP_DIR/SKILL.md"
curl -fsSL "$BASE/skill.json" -o "$TMP_DIR/skill.json"

ACTUAL_PUBKEY_SHA256="$(openssl pkey -pubin -in "$TMP_DIR/signing-public.pem" -outform DER | shasum -a 256 | awk '{print $1}')"
if [ "$ACTUAL_PUBKEY_SHA256" != "$RELEASE_PUBKEY_SHA256" ]; then
  echo "ERROR: signing-public.pem fingerprint mismatch" >&2
  exit 1
fi

openssl base64 -d -A -in "$TMP_DIR/checksums.sig" -out "$TMP_DIR/checksums.sig.bin"
openssl pkeyutl -verify -rawin -pubin \
  -inkey "$TMP_DIR/signing-public.pem" \
  -sigfile "$TMP_DIR/checksums.sig.bin" \
  -in "$TMP_DIR/checksums.json" >/dev/null

hash_file() {
  if command -v shasum >/dev/null 2>&1; then
    shasum -a 256 "$1" | awk '{print $1}'
  else
    sha256sum "$1" | awk '{print $1}'
  fi
}

verify_manifest_file() {
  asset="$1"
  path="$2"
  expected="$(jq -r --arg asset "$asset" '.files[$asset].sha256 // empty' "$TMP_DIR/checksums.json")"
  if [ -z "$expected" ]; then
    echo "ERROR: checksums.json missing $asset" >&2
    exit 1
  fi
  actual="$(hash_file "$path")"
  if [ "$actual" != "$expected" ]; then
    echo "ERROR: checksum mismatch for $asset" >&2
    exit 1
  fi
}

expected_archive="$(jq -r '.archive.sha256 // empty' "$TMP_DIR/checksums.json")"
if [ -z "$expected_archive" ]; then
  echo "ERROR: checksums.json missing archive.sha256" >&2
  exit 1
fi
actual_archive="$(hash_file "$TMP_DIR/$ZIP_NAME")"
if [ "$actual_archive" != "$expected_archive" ]; then
  echo "ERROR: archive checksum mismatch" >&2
  exit 1
fi

verify_manifest_file "SKILL.md" "$TMP_DIR/SKILL.md"
verify_manifest_file "skill.json" "$TMP_DIR/skill.json"

echo "Signed release manifest, archive, SKILL.md, and skill.json verified."

Only install or extract the archive after this verification succeeds.

Scope

Builders should use this skill as the OpenClaw landing zone for runtime traffic monitoring:

  • operator-scoped HTTP proxy inspection
  • optional HTTPS inspection with per-process CA trust
  • outbound exfiltration detection
  • inbound injection detection
  • approval-sensitive social-account mutation review
  • redacted local threat logs
  • optional OpenClaw hook/status integration

Do not merge this capability into clawsec-scanner, openclaw-audit-watchdog, or soul-guardian. Those skills have different trust boundaries and safety contracts.

Safety Contract

  • Opt-in only.
  • Detect-and-log by default.
  • No automatic system CA installation.
  • No global HTTP_PROXY or HTTPS_PROXY changes.
  • No blocking in the first implementation.
  • Redact secrets before logs or conversation alerts.
  • Keep all state under OPENCLAW_TRAFFIC_GUARDIAN_HOME or ~/.openclaw/security/clawsec/traffic-guardian.

Builder Entry Points

Read SPEC.md before implementing. Use the placeholder folders as follows:

PathIntended use
lib/Detector rules, redaction, event schema, report formatting
scripts/Start, stop, status, config validation, log query helpers
hooks/openclaw-traffic-guardian-hook/Optional OpenClaw hook/status integration
test/Unit tests, proxy fixture tests, redaction tests, process-scope tests

Required First Implementation Behavior

  1. Validate config without starting the proxy.
  2. Start monitor in foreground or explicit background mode.
  3. Scope proxy environment variables to the target OpenClaw process.
  4. Inspect HTTP request/response text up to a bounded byte limit.
  5. Support optional HTTPS MITM only when the operator supplies per-process trust configuration.
  6. Flag requests matching SPEC.md's Outbound POLICY_REVIEW cases as operator-review findings, including TweetClaw or other X/Twitter automation writes and scheduler/background-runner repeats without a fresh operator-approval marker.
  7. Detect repeat/background-runner context from bounded request metadata such as paths, headers, user-agent, client context, tool invocation metadata, or scheduler identifiers.
  8. Emit JSONL findings with redacted snippets plus source type, mutation category, approval-marker presence, and direct-operator versus background-runner context.
  9. Provide a status command that reports mode, listener, CA fingerprint if present, and last findings.

Out of Scope for v0.0.1 Implementation

  • automatic system trust-store mutation
  • transparent network interception
  • default blocking
  • sending traffic to external services
  • collecting full request/response bodies

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Openclaw Traffic Guardian AI skill do?

OpenClaw runtime traffic monitoring baseline for opt-in HTTP/HTTPS proxy inspection, egress detection, inbound injection detection, and social-account policy review.

Why use Openclaw Traffic Guardian on TypingMind?

Because you install it once and use it with any model. Openclaw Traffic Guardian is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Openclaw Traffic Guardian in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/prompt-security/clawsec/tree/main/skills/openclaw-traffic-guardian. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Openclaw Traffic Guardian?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Openclaw Traffic Guardian?

As many as you like. As long as a model supports skills, you can use Openclaw Traffic Guardian with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Openclaw Traffic Guardian AI skill free?

Yes. It is published on GitHub by prompt-security under the AGPL-3.0-or-later license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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