Detecting Beaconing Patterns With Zeek

What it does

When your agent uses it

• Hunting for command-and-control callbacks in network data
• Tasks that involve DataFrames
• Tasks that involve Red teaming and adversary simulation

Example prompts

• “Use the detecting-beaconing-patterns-with-zeek skill to perform statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing…”
• “/detecting-beaconing-patterns-with-zeek”

Requirements

• Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Parse Zeek conn.log into DataFrame with ZAT LogToDataFrame
2. 2Group connections by source IP and destination IP pairs
3. 3Calculate inter-arrival time intervals between consecutive connections
4. 4Compute standard deviation and coefficient of variation
5. 5Flag pairs with low coefficient of variation as potential beacons

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

• Tool permissions

  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.

• Runs code

  Ships 1 file in scripts/ (Python), which the agent can run.

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Detecting Beaconing Patterns With Zeek loads about 662 tokens when it runs, and up to ~1.1k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 151 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~92

When it runs · the whole SKILL.md, loaded when a task matches

~662

With references · SKILL.md plus every file in references/, read only if the agent opens them

~1.1k

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.

Safety

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.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 151 words, ~662 tokens.

name

detecting-beaconing-patterns-with-zeek

description

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

domain

cybersecurity

subdomain

security-operations

tags

network-security, zeek, c2-beaconing, conn-log-analysis, zat, threat-hunting, statistical-analysis

version

1.0

author

mahipal

license

Apache-2.0

nist_csf

DE.CM-01, RS.MA-01, GV.OV-01, DE.AE-02

mitre_attack

T1071.001, T1071.004, T1573, T1008, T1095

from zat.log_to_dataframe import LogToDataFrame
import numpy as np

log_to_df = LogToDataFrame()
conn_df = log_to_df.create_dataframe('/path/to/conn.log')

# Group by src/dst pair and calculate inter-arrival time
for (src, dst), group in conn_df.groupby(['id.orig_h', 'id.resp_h']):
    times = group['ts'].sort_values()
    intervals = times.diff().dt.total_seconds().dropna()
    if len(intervals) > 10:
        std_dev = np.std(intervals)
        mean_interval = np.mean(intervals)
        # Low std_dev relative to mean = likely beaconing

from zat.log_to_dataframe import LogToDataFrame
log_to_df = LogToDataFrame()
df = log_to_df.create_dataframe('conn.log')
print(df[['id.orig_h', 'id.resp_h', 'ts', 'duration']].head())

© 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

Files

SKILL.md and 3 other files (scripts, references) in skills/detecting-beaconing-patterns-with-zeek of mukul975/Anthropic-Cybersecurity-Skills.

• SKILL.md
• LICENSE
• references/api-reference.md
• scripts/agent.py

Open the folder on GitHubat commit 54a7988