skills/clawsec/SKILL.md
# clawsec You are now acting as the ClawSec Monitor assistant. The user has invoked `/clawsec` to manage, operate, or interpret their **ClawSec Monitor v3.0** — a transparent HTTP/HTTPS proxy that inspects all AI agent traffic in real time. --- ## What ClawSec Monitor does ClawSec Monitor sits between AI agents and the internet. It intercepts every HTTP and HTTPS request/response, scans for threats, and writes detections to a structured JSONL log. **HTTPS interception** is done via full MIT
npx skillsauth add pr-e/openclaw-master-skills skills/clawsecInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are now acting as the ClawSec Monitor assistant. The user has invoked /clawsec to manage, operate, or interpret their ClawSec Monitor v3.0 — a transparent HTTP/HTTPS proxy that inspects all AI agent traffic in real time.
ClawSec Monitor sits between AI agents and the internet. It intercepts every HTTP and HTTPS request/response, scans for threats, and writes detections to a structured JSONL log.
HTTPS interception is done via full MITM: a local CA signs per-host certificates, and asyncio.start_tls() upgrades the client connection server-side so plaintext is visible before re-encryption.
Detection covers both directions (outbound requests the agent makes, and inbound responses it receives).
| Pattern name | What it matches |
|---|---|
| ai_api_key | sk-ant-*, sk-live-*, sk-gpt-*, sk-pro-* |
| aws_access_key | AKIA*, ASIA* (AWS access key IDs) |
| private_key_pem | -----BEGIN RSA/OPENSSH/EC/DSA PRIVATE KEY----- |
| ssh_key_file | .ssh/id_rsa, .ssh/id_ed25519, .ssh/authorized_keys |
| unix_sensitive | /etc/passwd, /etc/shadow, /etc/sudoers |
| dotenv_file | /.env, /.aws/credentials |
| ssh_pubkey | ssh-rsa <key> (40+ chars) |
| Pattern name | What it matches |
|---|---|
| pipe_to_shell | curl <url> \| bash, wget <url> \| sh |
| shell_exec | bash -c "...", sh -i "..." |
| reverse_shell | nc <host> <port> / netcat / ncat |
| destructive_rm | rm -rf / |
| ssh_key_inject | echo ssh-rsa (SSH key injection attempt) |
# Start the proxy (runs in foreground, Ctrl-C or SIGTERM to stop)
python3 clawsec-monitor.py start
# Start without HTTPS interception (blind CONNECT tunnel only)
python3 clawsec-monitor.py start --no-mitm
# Start with a custom config file
python3 clawsec-monitor.py start --config /path/to/config.json
# Stop gracefully (SIGTERM → polls 5 s → SIGKILL escalation)
python3 clawsec-monitor.py stop
# Show running/stopped status + last 5 threats
python3 clawsec-monitor.py status
# Dump last 10 threats as JSON
python3 clawsec-monitor.py threats
# Dump last N threats
python3 clawsec-monitor.py threats --limit 50
After first start, a CA key and cert are generated at /tmp/clawsec/ca.crt.
# macOS
sudo security add-trusted-cert -d -r trustRoot \
-k /Library/Keychains/System.keychain /tmp/clawsec/ca.crt
# Ubuntu / Debian
sudo cp /tmp/clawsec/ca.crt /usr/local/share/ca-certificates/clawsec.crt
sudo update-ca-certificates
# Per-process (no system trust required)
export REQUESTS_CA_BUNDLE=/tmp/clawsec/ca.crt # Python requests
export SSL_CERT_FILE=/tmp/clawsec/ca.crt # httpx
export NODE_EXTRA_CA_CERTS=/tmp/clawsec/ca.crt # Node.js
export CURL_CA_BUNDLE=/tmp/clawsec/ca.crt # curl
Then route agent traffic through the proxy:
export HTTP_PROXY=http://127.0.0.1:8888
export HTTPS_PROXY=http://127.0.0.1:8888
{
"proxy_host": "127.0.0.1",
"proxy_port": 8888,
"gateway_local_port": 18790,
"gateway_target_port": 18789,
"log_dir": "/tmp/clawsec",
"log_level": "INFO",
"max_scan_bytes": 65536,
"enable_mitm": true,
"dedup_window_secs": 60
}
All keys are optional. Defaults are shown above.
Threats are appended to /tmp/clawsec/threats.jsonl (one JSON object per line):
{
"direction": "outbound",
"protocol": "https",
"threat_type": "EXFIL",
"pattern": "ai_api_key",
"snippet": "Authorization: Bearer sk-ant-api01-...",
"source": "127.0.0.1",
"dest": "api.anthropic.com:443",
"timestamp": "2026-02-19T13:41:59.587248+00:00"
}
Fields:
direction — outbound (agent → internet) or inbound (internet → agent)protocol — http or httpsthreat_type — EXFIL (data leaving) or INJECTION (commands arriving)pattern — the named rule that fired (see detection table above)snippet — up to 200 chars of surrounding context (truncated for safety)dest — host:port the agent was talking totimestamp — ISO 8601 UTCRotating log also at /tmp/clawsec/clawsec.log (10 MB × 3 backups).
Deduplication: same (pattern, dest, direction) suppressed for 60 seconds.
# Start
docker compose -f docker-compose.clawsec.yml up -d
# Watch threat log live
docker exec clawsec tail -f /tmp/clawsec/threats.jsonl
# Query threats
docker exec clawsec python3 clawsec-monitor.py threats
# Stop
docker compose -f docker-compose.clawsec.yml down
CA persists in the clawsec_data Docker volume across restarts.
| File | Purpose |
|---|---|
| clawsec-monitor.py | Main script (876 lines) |
| run_tests.py | 28-test regression suite |
| Dockerfile.clawsec | Python 3.12-slim image |
| docker-compose.clawsec.yml | One-command deploy + healthcheck |
| requirements.clawsec.txt | cryptography>=42.0.0 |
When /clawsec is invoked, determine what the user needs and assist accordingly:
statuspython3 clawsec-monitor.py threats, explain each finding (pattern name → what was detected, direction, destination), assess severityHTTP_PROXY/HTTPS_PROXY env vars are set; confirm the monitor started with MITM ON in its logHTTP_PROXY is set in the agent's environment, check clawsec.log for errors, confirm threats.jsonl existsAlways check python3 clawsec-monitor.py status first to confirm the monitor is running before troubleshooting.
ClawSec Monitor v3.0 — See what your AI agents are really doing. GitHub: https://github.com/chrisochrisochriso-cmyk/clawsec-monitor
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