Honeypot activity, last 48 hours
—Collecting the hourly series…
An SSH honeypot and web sensors catch what the internet throws at one home machine. A local pipeline enriches every address, links it into an intelligence graph of 690,000+ relationships, finds the campaigns behind the noise, feeds collective blocking — and turns the strongest cases into published dossiers.
Refreshes every 15 minutes
Six stages run on their own, around the clock, on hardware in a Romanian home office. Nothing here waits for a vendor's cloud.
A deliberately exposed SSH honeypot records every session, credential, command and download. Web sensors log every request that reaches the lab.
556K sessionsEach new address is profiled from a dozen intelligence sources: reputation, ownership, open services, known vulnerabilities, Tor status.
21,120 deep-enrichedA graph engine connects addresses that share SSH fingerprints, credentials, commands, keys, malware and infrastructure.
692K linksClusters of related behaviour become actors and campaigns, scored by threat and tracked across time.
65 SSH · 748 webHigh-confidence findings flow into collective blocking at the edge, so the lab learns from every attempt.
48.9K IPs blockedLocal AI agents query the graph through hundreds of tools and draft evidence-backed dossiers a human reviews.
817 dossiersEverything below is rendered from the platform's public feed files. Attacker addresses are masked on this page; full indicators are available in the machine-readable feed.
Collecting the hourly series…
Scoring in progress…
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Passwords are partly masked. They are what attackers tried — never real accounts.
Typical: wipe and replace SSH keys, lock the account, fingerprint the CPU, fetch a miner or a bot.
Collecting…
Machine-readable feed: actor-clusters.json · licensed CC BY-NC-SA 4.0 with attribution.
Every request that reaches the lab's public sites is logged, the sender profiled, and the intent classified — scrapers, watchers, credential harvesters, CMS probes, shell uploads, AI crawlers. Coordinated behaviour becomes a web campaign.
AI crawlers are now the single largest class of automated visitors — ahead of search engines.
Findings don't stay in a database. They become blocking decisions at the edge of the network, merged with a community blocklist and curated threat feeds — and the lab's own indicator feed is published for anyone to use.
Dossier TI-2026-013 documented a coordinated campaign: a Mirai-family Go SSH scanner, a persistent backdoor and a libssh scanner fleet, operating through a bulletproof-hosting ecosystem.
The intelligence graph separated three actor clusters, traced infrastructure to newly registered networks and documented the staging servers — before public attribution existed. A later attack on the lab was matched to this dossier and an earlier one automatically. It remains one of the clearest examples of what the platform is for.
Published, evidence-backed reports on actors, campaigns and infrastructure, each with a verification page. Drawn from 1,997 investigations and 4,156 tracked actors.
A machine-readable feed of actor clusters, high-value indicators, hostile networks, attack tools and malware samples — refreshed every quarter hour, free for non-commercial use with attribution.
Vectors across 26 collections — sessions, actors, evidence, a 700,389-entry exploit and CVE corpus — so agents find related cases by meaning, not keywords.
Classification, enrichment triage and dossier drafting run on local language models behind a single router, on the same server that hosts everything else.
32 GB VRAM, ROCm
Qwen3.5-9B (speculative decoding) to Qwen3.6-35B, behind one llama.cpp router
plus 41 security-operations tools
67 namespaces · 88 CPU threads · 503 GiB RAM
Use the open feed, read the dossiers, or get in touch for deeper access to the graph and the tools behind it.