agent security skill risk: medium
Arkime Network Traffic Analysis Deployment
The prompt provides instructions to install dependencies, configure an Arkime viewer URL, and run a Python agent that queries sessions, downloads PCAP data, detects C2 beaconing, i…
- External action: medium
SKILL 4 files · 2 folders
SKILL.md
--- name: implementing-network-traffic-analysis-with-arkime description: "Deploy and query Arkime (formerly Moloch) for full packet capture network traffic analysis. Uses the Arkime API" --- # Implementing Network Traffic Analysis with Arkime ## When to Use - When deploying or configuring implementing network traffic analysis with arkime capabilities in your environment - When establishing security controls aligned to compliance requirements - When building or improving security architecture for this domain - When conducting security assessments that require this implementation ## Prerequisites - Familiarity with network security concepts and tools - Access to a test or lab environment for safe execution - Python 3.8+ with required dependencies installed - Appropriate authorization for any testing activities ## Instructions 1. Install dependencies: `pip install requests` 2. Configure Arkime viewer URL and credentials. 3. Run the agent to query Arkime sessions and analyze traffic: - Search sessions by IP, port, protocol, or expression - Download PCAP data for forensic analysis - Detect C2 beaconing via connection interval analysis - Identify DNS tunneling through query length statistics - Flag connections to known-bad TLS certificate issuers ```bash python scripts/agent.py --arkime-url https://arkime.local:8005 --user admin --password secret --output arkime_report.json ``` ## Examples ### Beaconing Detection ``` Source: 10.1.2.50 -> 185.220.101.34:443 Sessions: 288 over 24 hours Avg interval: 300s, Jitter: 4.2% Verdict: HIGH confidence C2 beaconing (jitter < 5%) ```
REQUIRED CONTEXT
- Arkime viewer URL and credentials
OPTIONAL CONTEXT
- IP/port/protocol filters
- PCAP output path
EXPECTED OUTPUT
- Format
- markdown
- Schema
- markdown_sections · When to Use, Prerequisites, Instructions, Examples
- Constraints
- include code examples
- provide detection verdicts
EXAMPLES
Includes one beaconing detection example showing source IP, session count, interval stats, and verdict.
CAVEATS
- Missing context
- Full source or structure of scripts/agent.py
- Exact Arkime API endpoints or query syntax
- Error handling or output schema for the report
- Ambiguities
- Awkward phrasing in 'When to Use': 'configuring implementing network traffic analysis with arkime capabilities'
QUALITY
- OVERALL
- 0.58
- CLARITY
- 0.65
- SPECIFICITY
- 0.55
- REUSABILITY
- 0.50
- COMPLETENESS
- 0.60
IMPROVEMENT SUGGESTIONS
- Replace the redundant 'configuring implementing' phrase with clear wording such as 'deploying or configuring Arkime for network traffic analysis'
- Add a brief code skeleton or key function signatures inside the Instructions section
- Specify the expected JSON schema of arkime_report.json
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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