Incident Response Network
LeoYeAI/openclaw-master-skills
Network forensics evidence collection and analysis during security incidents.
Agent skill
Perform forensic analysis of network packet captures (PCAP/PCAPNG) using Wireshark, tshark, and tcpdump to reconstruct network communications, extract transferred files, identify malicious traffic…
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-network-packet-capture-analysis --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/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/performing-network-packet-capture-analysis .claude/skills/performing-network-packet-capture-analysis && 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 "performing-network-packet-capture-analysis" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysis into .claude/skills/performing-network-packet-capture-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-network-packet-capture-analysis", 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/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysisType 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 mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-network-packet-capture-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/performing-network-packet-capture-analysis .agents/skills/performing-network-packet-capture-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "performing-network-packet-capture-analysis" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysis into .agents/skills/performing-network-packet-capture-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-network-packet-capture-analysis", 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 mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-network-packet-capture-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/performing-network-packet-capture-analysis .cursor/skills/performing-network-packet-capture-analysis && 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 "performing-network-packet-capture-analysis" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysis into .cursor/skills/performing-network-packet-capture-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-network-packet-capture-analysis", 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/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/performing-network-packet-capture-analysis--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 mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-network-packet-capture-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/performing-network-packet-capture-analysis .gemini/skills/performing-network-packet-capture-analysis && 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 "performing-network-packet-capture-analysis" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysis into .gemini/skills/performing-network-packet-capture-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-network-packet-capture-analysis", 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 mukul975/Anthropic-Cybersecurity-Skills performing-network-packet-capture-analysisInstalls 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 mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/performing-network-packet-capture-analysis .github/skills/performing-network-packet-capture-analysis && 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 "performing-network-packet-capture-analysis" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysis into .github/skills/performing-network-packet-capture-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-network-packet-capture-analysis", 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 mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills performing-network-packet-capture-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/performing-network-packet-capture-analysis .opencode/skills/performing-network-packet-capture-analysis && 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 "performing-network-packet-capture-analysis" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/performing-network-packet-capture-analysis into .opencode/skills/performing-network-packet-capture-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performing-network-packet-capture-analysis", 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.
performing-network-packet-capture-analysisPerform forensic analysis of network packet captures (PCAP/PCAPNG) using Wireshark, tshark, and tcpdump to reconstruct network communications, extract transferred files, identify malicious traffic…
Performing Network Packet Capture Analysis is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Perform forensic analysis of network packet captures (PCAP/PCAPNG) using Wireshark, tshark, and tcpdump to reconstruct network communications, extract transferred files, identify malicious traffic, and establish evidence of data exfiltration or command-and-control activity. Use when a PCAP file from an incident needs to be examined to prove lateral movement, malware delivery, or unauthorized access.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).
It sits in Security, covering Red teaming and adversary simulation, Network security and Digital forensics. It works with Wireshark. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 54a7988. 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.
Ships 2 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
wireshark.orginsanecyber.comsans.orgnetresec.comFrom 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.
Performing Network Packet Capture Analysis loads about 2.3k tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 191 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); the scripts in this folder are not scanned.
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 191 words, ~2,260 tokens.
.claude/skills/performing-network-packet-capture-analysis/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Network packet captures (PCAP/PCAPNG files) represent the ultimate source of truth about network activity and provide irrefutable evidence of communications between hosts. PCAP files log every packet transmitted over a network segment, making them vital for forensic investigations involving data exfiltration, command-and-control communications, lateral movement, malware delivery, and unauthorized access. Wireshark is the primary tool for interactive analysis, while tshark provides command-line capabilities for automated processing and scripting. Modern PCAPNG format supports additional metadata including interface descriptions, capture comments, precise timestamps, and per-packet annotations.
# Capture all traffic on interface eth0
tcpdump -i eth0 -w capture.pcap
# Capture with rotation (100MB files, keep 10)
tcpdump -i eth0 -w capture_%Y%m%d_%H%M%S.pcap -C 100 -W 10
# Capture specific host traffic
tcpdump -i eth0 host 192.168.1.100 -w host_traffic.pcap
# Capture specific port traffic
tcpdump -i eth0 port 443 -w https_traffic.pcap
# Capture with BPF filter for suspicious ports
tcpdump -i eth0 'port 4444 or port 8080 or port 1337' -w suspicious.pcap# HTTP traffic
http
# DNS queries
dns
# SMB file transfers
smb2
# Specific IP communication
ip.addr == 192.168.1.100
# Failed TCP connections
tcp.flags.syn == 1 && tcp.flags.ack == 0
# Large data transfers (potential exfiltration)
tcp.len > 1000
# Specific protocol by port
tcp.port == 4444
# TLS handshakes (SNI extraction)
tls.handshake.type == 1
# HTTP POST requests
http.request.method == "POST"
# DNS queries to suspicious TLDs
dns.qry.name contains ".xyz" or dns.qry.name contains ".top"
# Beaconing detection (regular intervals)
frame.time_delta_displayed > 55 && frame.time_delta_displayed < 65# Extract HTTP URLs from capture
tshark -r capture.pcap -Y "http.request" -T fields -e http.host -e http.request.uri
# Extract DNS queries
tshark -r capture.pcap -Y "dns.flags.response == 0" -T fields -e dns.qry.name | sort -u
# Extract file transfers (HTTP objects)
tshark -r capture.pcap --export-objects http,exported_files/
# Extract SMB file transfers
tshark -r capture.pcap --export-objects smb,smb_files/
# Protocol hierarchy statistics
tshark -r capture.pcap -z io,phs
# Conversation statistics
tshark -r capture.pcap -z conv,tcp
# Extract TLS SNI (Server Name Indication)
tshark -r capture.pcap -Y "tls.handshake.type == 1" -T fields -e tls.handshake.extensions_server_name
# Top talkers by bytes
tshark -r capture.pcap -z endpoints,ip -q
# Extract credentials (FTP, HTTP Basic)
tshark -r capture.pcap -Y "ftp.request.command == USER || ftp.request.command == PASS || http.authorization" -T fields -e ftp.request.arg -e http.authorizationfrom scapy.all import rdpcap, IP, TCP, UDP, DNS, DNSQR, Raw
import os
import sys
import json
from collections import defaultdict, Counter
from datetime import datetime
class PCAPForensicAnalyzer:
"""Forensic analysis of PCAP files using Scapy."""
def __init__(self, pcap_path: str, output_dir: str):
self.pcap_path = pcap_path
self.output_dir = output_dir
os.makedirs(output_dir, exist_ok=True)
self.packets = rdpcap(pcap_path)
def get_conversations(self) -> list:
"""Extract unique IP conversations with byte counts."""
convos = defaultdict(lambda: {"packets": 0, "bytes": 0})
for pkt in self.packets:
if IP in pkt:
key = tuple(sorted([pkt[IP].src, pkt[IP].dst]))
convos[key]["packets"] += 1
convos[key]["bytes"] += len(pkt)
return [
{"src": k[0], "dst": k[1], "packets": v["packets"], "bytes": v["bytes"]}
for k, v in sorted(convos.items(), key=lambda x: x[1]["bytes"], reverse=True)
]
def extract_dns_queries(self) -> list:
"""Extract all DNS queries from the capture."""
queries = []
for pkt in self.packets:
if DNS in pkt and pkt[DNS].qr == 0 and DNSQR in pkt:
queries.append({
"query": pkt[DNSQR].qname.decode(errors="replace").rstrip("."),
"type": pkt[DNSQR].qtype,
"src": pkt[IP].src if IP in pkt else "unknown"
})
return queries
def detect_beaconing(self, threshold_seconds: float = 5.0) -> list:
"""Detect potential beaconing activity based on regular intervals."""
ip_timestamps = defaultdict(list)
for pkt in self.packets:
if IP in pkt and TCP in pkt:
key = (pkt[IP].src, pkt[IP].dst, pkt[TCP].dport)
ip_timestamps[key].append(float(pkt.time))
beacons = []
for key, times in ip_timestamps.items():
if len(times) < 5:
continue
deltas = [times[i+1] - times[i] for i in range(len(times)-1)]
if deltas:
avg_delta = sum(deltas) / len(deltas)
variance = sum((d - avg_delta) ** 2 for d in deltas) / len(deltas)
if variance < threshold_seconds and avg_delta > 1:
beacons.append({
"src": key[0], "dst": key[1], "port": key[2],
"avg_interval": round(avg_delta, 2),
"variance": round(variance, 4),
"connection_count": len(times)
})
return sorted(beacons, key=lambda x: x["variance"])
def get_protocol_distribution(self) -> dict:
"""Get protocol distribution statistics."""
protocols = Counter()
for pkt in self.packets:
if TCP in pkt:
protocols[f"TCP/{pkt[TCP].dport}"] += 1
elif UDP in pkt:
protocols[f"UDP/{pkt[UDP].dport}"] += 1
return dict(protocols.most_common(50))
def generate_report(self) -> str:
"""Generate comprehensive PCAP analysis report."""
report = {
"analysis_timestamp": datetime.now().isoformat(),
"pcap_file": self.pcap_path,
"total_packets": len(self.packets),
"conversations": self.get_conversations()[:50],
"dns_queries": self.extract_dns_queries()[:200],
"potential_beacons": self.detect_beaconing(),
"protocol_distribution": self.get_protocol_distribution()
}
report_path = os.path.join(self.output_dir, "pcap_forensic_report.json")
with open(report_path, "w") as f:
json.dump(report, f, indent=2)
print(f"[*] Total packets: {report['total_packets']}")
print(f"[*] Conversations: {len(report['conversations'])}")
print(f"[*] DNS queries: {len(report['dns_queries'])}")
print(f"[*] Potential beacons: {len(report['potential_beacons'])}")
return report_path
def main():
if len(sys.argv) < 3:
print("Usage: python process.py <pcap_file> <output_dir>")
sys.exit(1)
analyzer = PCAPForensicAnalyzer(sys.argv[1], sys.argv[2])
analyzer.generate_report()
if __name__ == "__main__":
main()© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 7 other files (scripts, references, assets) in skills/performing-network-packet-capture-analysis of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Performing Network Packet Capture Analysis 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 |
|---|---|---|---|---|---|---|
| Performing Network Packet Capture Analysis this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Incident Response NetworkLeoYeAI/openclaw-master-skills | 2.2k | — | ~5k | Automated safety check: Pass | Apache-2.0 | |
| Breach Forensicsmukul975/Privacy-Data-Protection-Skills | 297 | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| TShark Traffic AnalysisAgentSecOps/SecOpsAgentKit | 220 | 1 repos | ~4.8k | Automated safety check: Notes | Custom licence | |
| Dfirtransilienceai/communitytools | 562 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Protocol Reverse Engineeringwshobson/agents | 40k | 8 repos | ~3.2k | Automated safety check: Pass | MIT |
LeoYeAI/openclaw-master-skills
Network forensics evidence collection and analysis during security incidents.
mukul975/Privacy-Data-Protection-Skills
Conducts digital forensics investigations following a personal data breach, covering evidence preservation, chain of custody documentation, log analysis, scope determination, and root cause analysis.
AgentSecOps/SecOpsAgentKit
Guides authorized packet capture and analysis with TShark, Wireshark's command-line tool, for security investigations, malware detection and forensic examination of network traffic.
transilienceai/communitytools
Digital forensics and incident response - Windows event log analysis, PCAP forensics, filesystem artifact analysis, AD attack detection, and timeline correlation.
wshobson/agents
Master network protocol reverse engineering including packet analysis, protocol dissection, and custom protocol documentation.
yaklang/hack-skills
Traffic analysis and PCAP forensics playbook. An agent skill from yaklang/hack-skills.
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Works with
Categories
Perform forensic analysis of network packet captures (PCAP/PCAPNG) using Wireshark, tshark, and tcpdump to reconstruct network communications, extract transferred files, identify malicious traffic…. Performing Network Packet Capture Analysis is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Perform forensic analysis of network packet captures (PCAP/PCAPNG) using Wireshark, tshark, and tcpdump to reconstruct network communications, extract transferred files, identify malicious traffic, and establish evidence of data exfiltration or command-and-control activity.
Performing Network Packet Capture Analysis fits situations like: A PCAP file from an incident needs to be examined to prove lateral movement; malware delivery; unauthorized access.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a claude-code`. Or copy the skill folder (skills/performing-network-packet-capture-analysis in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/performing-network-packet-capture-analysis in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a codex`. Or copy the skill folder (skills/performing-network-packet-capture-analysis in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/performing-network-packet-capture-analysis 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 mukul975/Anthropic-Cybersecurity-Skills --skill performing-network-packet-capture-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performing-network-packet-capture-analysis, .gemini/skills/performing-network-packet-capture-analysis, .github/skills/performing-network-packet-capture-analysis and .opencode/skills/performing-network-packet-capture-analysis in your project.
Going by SKILL.md and its folder, Performing Network Packet Capture Analysis needs Python for the scripts in its folder. Our summary lists: Python 3.
SKILL.md names 4 domains. As links in the text: wireshark.org, insanecyber.com, sans.org and netresec.com. 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Performing Network Packet Capture Analysis is published under the Apache-2.0 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 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 651 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Performing Network Packet Capture Analysis: Incident Response Network (LeoYeAI/openclaw-master-skills, 2.2k stars), Breach Forensics (mukul975/Privacy-Data-Protection-Skills, 297 stars), TShark Traffic Analysis (AgentSecOps/SecOpsAgentKit, 220 stars) and Dfir (transilienceai/communitytools, 562 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,993 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.