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 Mikaru0Mystic/sectinel --skill analyzing-network-traffic-for-incidentsgit clone --depth 1 https://github.com/Mikaru0Mystic/sectinelWrote 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/mikaru0mystic/sectinel/analyzing-network-traffic-for-incidents)<a href="https://agentmods.dev/skills/mikaru0mystic/sectinel/analyzing-network-traffic-for-incidents"><img src="https://agentmods.dev/badge/skills/mikaru0mystic/sectinel/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/mikaru0mystic/sectinel/analyzing-network-traffic-for-incidents"><img src="https://agentmods.dev/badge/skills/mikaru0mystic/sectinel/analyzing-network-traffic-for-incidents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 12d 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.
This is a copy
100% identical to analyzing-network-traffic-for-incidents — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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.
- 12d 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 Mikaru0Mystic/sectinel (11 stars, last pushed 2mo 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. It is 100% identical to analyzing-network-traffic-for-incidents, differing in 0 lines, and is treated as a copy.
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…