Anthropic Cybersecurity Skills is a library of structured cybersecurity procedures for AI agents, covering security domains and mappings to established security frameworks. It is for authorized security analysis, penetration testing, incident response, research, defense, and education across compatible AI platforms. The catalogue entries package parts of this library as agent skills, instructions, or a plugin.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-network-traffic-for-incidentsgit clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mukul975/anthropic-cybersecurity-skills/analyzing-network-traffic-for-incidents)<a href="https://agentmods.dev/skills/mukul975/anthropic-cybersecurity-skills/analyzing-network-traffic-for-incidents"><img src="https://agentmods.dev/badge/skills/mukul975/anthropic-cybersecurity-skills/analyzing-network-traffic-for-incidents/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mukul975/anthropic-cybersecurity-skills/analyzing-network-traffic-for-incidents"><img src="https://agentmods.dev/badge/skills/mukul975/anthropic-cybersecurity-skills/analyzing-network-traffic-for-incidents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.02653 |
| Opus 5 | $0.00046 | $0.01326 |
| Sonnet 5 | $0.00018 | $0.00531 |
| Haiku 4.5 | $0.00009 | $0.00265 |
Grade A, and why
analyzing-network-traffic-for-incidents scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
6 near-identical copies found in the catalogue:
- analyzing-network-traffic-for-incidents — 100% identical, 0 lines differ
- analyzing-network-traffic-for-incidents — 100% identical, 0 lines differ
- analyzing-network-traffic-for-incidents — 100% identical, 0 lines differ
- analyzing-network-traffic-for-incidents — 97% identical, 30 lines differ
- analyzing-network-traffic-for-incidents — 97% identical, 30 lines differ
- analyzing-network-traffic-for-incidents — 97% identical, 30 lines differ
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyzing Network Traffic for Incidents
When to Use
- SIEM alerts on anomalous network traffic patterns requiring deeper investigation
- C2 beaconing is suspected and needs confirmation through packet-level analysis
- Data exfiltration volume or destination must be quantified from network evidence
- Lateral movement between systems needs to be traced through network connections
- An IDS/IPS alert requires packet-level validation to confirm or dismiss
Do not use for host-based forensic analysis (process execution, file system artifacts); use endpoint forensics tools instead.
Prerequisites
- Full packet capture (PCAP) infrastructure or on-demand capture capability (network tap, SPAN port)
- Wireshark installed on the analysis workstation with appropriate display filters knowledge
- Zeek (formerly Bro) deployed for network metadata generation (conn.log, dns.log, http.log, ssl.log)
- NetFlow/IPFIX collection from network devices for traffic flow analysis
- Network architecture diagram showing VLAN layout, firewall placement, and monitoring points
- Threat intelligence feeds for correlating observed network indicators
Workflow
Step 1: Capture or Acquire Network Traffic
Obtain the relevant traffic data for the investigation:
Live Capture (if incident is active):
# Capture on specific interface filtering by host
tcpdump -i eth0 -w capture.pcap host 10.1.5.42
# Capture C2 traffic to specific external IP
tcpdump -i eth0 -w c2_traffic.pcap host 185.220.101.42
# Capture with rotation (1GB files, keep 10)
tcpdump -i eth0 -w capture_%Y%m%d%H%M.pcap -C 1000 -W 10
From Existing Infrastructure:
- Export PCAP from full packet capture appliance (Arkime/Moloch, ExtraHop, Corelight)
- Pull Zeek logs from the Zeek cluster for the investigation timeframe
- Export NetFlow data from network devices for high-level traffic analysis
Step 2: Identify C2 Communications
Detect command-and-control traffic patterns:
Beaconing Detection (Zeek conn.log):
# Extract connections to external IPs with regular intervals
cat conn.log | zeek-cut ts id.orig_h id.resp_h id.resp_p duration orig_bytes resp_bytes \
| awk '$4 ~ /^185\.220/' | sort -t. -k1,1n -k2,2n
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 267 lines · 91 tokens per session scan A b5467621b7bf
analyzing-network-traffic-for-incidents is a skill published in the GitHub repository mukul975/Anthropic-Cybersecurity-Skills (32,631 stars, last pushed 12d ago), licensed Apache-2.0. It adds 91 tokens to every session and 2,653 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
analyzing-network-traffic-for-incidents
Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic…
analyzing-network-traffic-for-incidents
Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic…
analyzing-network-traffic-for-incidents
A guide to investigating network traffic during a security incident using packet captures, Zeek logs, and NetFlow, which summarizes connections between systems.
analyzing-network-traffic-for-incidents
Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic…
analyzing-network-traffic-for-incidents
Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic…
analyzing-network-traffic-for-incidents
Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic…