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NOTES.md
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NOTES.md
@@ -54,60 +54,3 @@ This initial test doesn't seem to be working. Might be that I'm using WSL, so I
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# TODO
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## Core / Hardening
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- [ ] **Attacker fingerprinting** — Beyond IP logging: capture TLS JA3/JA4 hashes, TCP window sizes, User-Agent strings, SSH client banners, and tool signatures (nmap, masscan, Metasploit, Cobalt Strike). Build attacker profiles across sessions.
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- [ ] **Canary tokens** — Embed canary URLs, fake AWS keys, fake API tokens, and honeydocs (PDF/DOCX with phone-home URLs) into decky filesystems. Fire an alert the moment one is used.
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- [ ] **Tarpit mode** — Slow down attackers by making services respond extremely slowly (e.g., SSH that takes 60s to reject, HTTP that drip-feeds bytes). Wastes attacker time and resources.
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- [ ] **Dynamic decky mutation** — Deckies that change their exposed services or OS fingerprint over time to confuse port-scan caching and appear more "alive."
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- [ ] **Credential harvesting DB** — Every username/password attempt across all services lands in a queryable database. Expose via CLI (`decnet creds`) and flag reuse across deckies.
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- [ ] **Session recording** — Full session capture for SSH/Telnet (keystroke logs, commands run, files downloaded). Cowrie already does this — surface it better in the CLI and correlation engine.
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- [ ] **Payload capture** — Store every file uploaded or command executed by an attacker. Hash and auto-submit to VirusTotal or a local sandbox.
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## Detection & Intelligence
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- [ ] **Real-time alerting** — Webhook/Slack/Telegram notifications when an attacker hits a decky for the first time, crosses N deckies (lateral movement), or uses a known bad IP.
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- [ ] **Threat intel enrichment** — Auto-lookup attacker IPs against AbuseIPDB, Shodan, GreyNoise, and AlienVault OTX. Tag known scanners vs. targeted attackers.
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- [ ] **Attack campaign clustering** — Group attacker sessions by tooling signatures, timing patterns, and credential sets. Identify coordinated campaigns hitting multiple deckies.
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- [ ] **GeoIP mapping** — Attacker origin on a world map. Correlate with ASN data to identify cloud exit nodes, VPNs, and Tor exits.
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- [ ] **TTPs tagging** — Map observed attacker behaviors to MITRE ATT&CK techniques automatically. Tag events in the correlation engine.
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- [ ] **Honeypot interaction scoring** — Score attackers on a scale: casual scanner vs. persistent targeted attacker, based on depth of interaction and commands run.
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## Dashboard & Visibility
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- [ ] **Web dashboard** — Real-time web UI showing live decky status, attacker activity, traversal graphs, and credential stats. Could be a simple FastAPI + HTMX or a full React app.
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- [ ] **Pre-built Kibana/Grafana dashboards** — Ship dashboard JSON exports out of the box so ELK/Grafana deployments are plug-and-play.
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- [ ] **CLI live feed** — `decnet watch` command: tail all decky logs in a unified, colored terminal stream (like `docker-compose logs -f` but prettier).
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- [ ] **Traversal graph export** — Export attacker traversal graphs as DOT/Graphviz or JSON for visualization in external tools.
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- [ ] **Daily digest** — Automated daily summary email/report: new attackers, top credentials tried, most-hit services.
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## Deployment & Infrastructure
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- [ ] **SWARM / multihost mode** — Full Ansible-based orchestration for deploying deckies across N real hosts.
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- [ ] **Terraform/Pulumi provider** — Spin up cloud-hosted deckies on AWS/GCP/Azure with one command. Useful for internet-facing honeynets.
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- [ ] **Auto-scaling** — When attack traffic increases, automatically spawn more deckies to absorb and log more activity.
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- [ ] **Kubernetes deployment mode** — Run deckies as Kubernetes pods for environments already running k8s.
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- [ ] **Proxmox/libvirt backend** — Full VM-based deckies instead of containers, for even more realistic OS fingerprints and behavior. Docker for speed; VMs for realism.
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- [ ] **Raspberry Pi / ARM support** — Low-cost physical honeynets using RPis. Validate ARM image builds.
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- [ ] **Decky health monitoring** — Watchdog that auto-restarts crashed deckies and alerts if a service goes dark.
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## Services & Realism
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- [ ] **HTTPS/TLS support** — HTTP honeypot with a self-signed or Let's Encrypt cert. Many real-world services use HTTPS; plain HTTP stands out.
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- [ ] **Fake Active Directory** — A convincing fake AD/LDAP with fake users, groups, and GPOs. Attacker tools like BloodHound should get juicy (fake) data.
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- [ ] **Fake file shares** — SMB/NFS shares pre-populated with enticing but fake files: "passwords.xlsx", "vpn_config.ovpn", "backup_keys.tar.gz". All instrumented to detect access.
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- [ ] **Realistic web apps** — HTTP honeypot serving convincing fake apps: a fake WordPress, a fake phpMyAdmin, a fake Grafana login — all logging every interaction.
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- [ ] **OT/ICS profiles** — Expand Conpot support: Modbus, DNP3, BACnet, EtherNet/IP. Convincing industrial control system decoys.
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- [ ] **Printer/IoT archetypes** — Expand existing printer/camera archetypes with actual service emulation (IPP, ONVIF, WS-Discovery).
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- [ ] **Service interaction depth** — Some services currently just log the connection. Deepen interaction: fake MySQL that accepts queries and returns realistic fake data, fake Redis that stores and retrieves dummy keys.
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## Developer Experience
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- [ ] **Plugin SDK docs** — Full documentation and an example plugin for adding custom services. Lower the barrier for community contributions.
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- [ ] **Integration tests** — Full deploy/teardown cycle tests against a real Docker daemon (not just unit tests).
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- [ ] **Per-service tests** — Each of the 29 service implementations deserves its own test coverage.
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- [ ] **CI/CD pipeline** — GitHub/Gitea Actions: run tests on push, lint, build Docker images, publish releases.
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- [ ] **Config validation CLI** — `decnet validate my.ini` to dry-check an INI config before deploying.
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- [ ] **Config generator wizard** — `decnet wizard` interactive prompt to generate an INI config without writing one by hand.
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@@ -631,3 +631,9 @@ The test suite covers:
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| `test_cli_service_pool.py` | CLI service resolution |
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| `test_cli_service_pool.py` | CLI service resolution |
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Every new feature requires passing tests before merging.
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Every new feature requires passing tests before merging.
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# AI Disclosure
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This project has been made with lots, and I mean lots of help from AIs. While most of the design was made by me, most of the coding was done by AI models.
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Nevertheless, this project will be kept under high scrutiny by humans.
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