Claude 24f816b6a3
Consolidate 22 sibling repos into layered organism structure
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):

- brain/        LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
                dispatch, A51 channels, and the OSINT cluster
- knowledge/    LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
                MITRE ATT&CK data
- reference/    defensive threat-reference (C3, shhbruh doc) + AdaYaml parser

License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.

Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.

https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2026-06-10 06:53:01 +00:00

2.0 KiB

name description domain subdomain tags version author license nist_csf
implementing-network-traffic-analysis-with-arkime Deploy and query Arkime (formerly Moloch) for full packet capture network traffic analysis. Uses the Arkime API v3 to search sessions, download PCAPs, analyze connection patterns, detect beaconing behavior, and identify suspicious network flows. Monitors DNS queries, HTTP traffic, and TLS certificate anomalies across captured traffic. cybersecurity network-security
implementing
network
traffic
analysis
1.0 mahipal Apache-2.0
PR.IR-01
DE.CM-01
ID.AM-03
PR.DS-02

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
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%)