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Show HN: Watch bots interact with an SSH honeypot in real time
- tusksm 3mo agoHi HN, I maintain several web servers and kept seeing a constant stream of SSH login attempts. At some point I became curious: what do these bots actually try to do after they get in? I set up a Cowrie SSH honeypot and built a small live dashboard around its JSON logs. Cowrie listens on port 22, a Python service follows the log and streams events over WebSockets, and Nginx serves the frontend. The whole thing currently runs on a 1 vCPU / 1 GB Debian VPS. The dashboard groups activity by source IP, with individual SSH sessions nested underneath. It shows authentication attempts, commands, SSH client fingerprints, file writes and downloads, and tunneling requests in real time. Initially I thought the interesting part would be simply watching commands appear. After looking at the collected data, I realized that recurring behavior is much more interesting than individual events. In one roughly 8-hour sample, the honeypot recorded about 1,950 sessions from 213 source IPs. 327 sessions reached command execution. Some recurring patterns included: - the same SSH public key being installed 152 times from 11 source IPs - a system fingerprinting script that appears designed to distinguish a real shell from a honeypot - a downloader requesting payloads for several CPU architectures - attempts to use SSH forwarding as a proxy - distributed credential probes that connect, test one value, and immediately disconnect This also showed me that grouping activity only by IP isn't enough. Several apparently different sources can use the same SSH client fingerprint, command sequence, public key, or downloaded artifact and probably belong to the same automated campaign. At the moment this is primarily a live log viewer. Some directions I am considering are: - automatic classification of sessions as scanning, credential probing, reconnaissance, persistence, downloading, or tunneling - clustering activity into campaigns using HASSH fingerprints, command sequences, SSH keys, and artifact hashes - historical statistics and searchable sessions - support for multiple distributed honeypot sensors - publishing the collector and dashboard code The public stream currently includes source IPs, attempted credentials, and commands. I added a notice explaining that an IP may belong to a compromised machine, proxy, VPN, or scanner, but I am still thinking through the privacy and responsible-disclosure tradeoffs. Cowrie's "login.success" events only mean that the honeypot accepted the credentials; they don't mean those credentials would work on a real server. I'm trying to decide whether this should remain a simple live visualization or grow into a small analysis tool. Which direction would make this project most useful or interesting to you? Are there other patterns or types of analysis that would be worth adding?
- p1anecrazy 3mo agoHi, this is very interesting, thanks. While trying to educate myself about honeypots I came across this (https://securehoney.net/ https://securehoney.net/). The aggregations of popular logins and IP locations seem interesting.
- LorenDB 3mo agoFrom that site: Files uploaded 25,522 (46 unique) Malware uploaded 7,735 (43 unique) I wonder what 3 files were so common that they were uploaded 17,787 times instead of malware.
- CookieCrisp 3mo agoProbably the ssh key
- tusksm 2mo agoAdded https://honeypotlive.cc/campaigns/ https://honeypotlive.cc/campaigns/ to view combined campaigns. For now, only in strict high-confidence clusters.
- hideout_berlin 3mo agoyou could make the logs public too :)
- krunck 3mo agoThis is great. Thanks. Try fingerprinting the behaviour in the sessions. Over time you should be able to distinguish between various automated tools and live people.
- rkagerer 3mo agoSome kind of source IP masking would be prudent. As you pointed out, some of those machines are compromised, and you aren't making their owners' lives any easier. Bad actors might use the data you're publishing to fingerprint specific exploits to which the machines are vulnerable, multiplying the problem. If producing an IP blacklist is one of your aims, divorcing it from any specific traffic would be more responsible. You may also want to consider the risk traffic from compromised machines could leak PII (eg. say a script tried to use you as a relay to exfiltrate data) - and the ethical and legal consequences. A filter for SIN, credit cards, etc. would be a basic table-stakes mitigation step.
- arm32 3mo agoHi tusksm! It's honeypot season! Really cool project, I've been working on a honeypot project of my own right now called `honeyprompt` (https://github.com/alectrocute/honeyprompt https://github.com/alectrocute/honeyprompt) that utilizes LLMs to craft responses and supports multiple protocols. Having a public sink presentation layer like honeypotlive.cc was one of my next todos.
- tarpitt 3mo agoreminds me of https://xkcd.com/350/ https://xkcd.com/350/
- CzaxTanmay 3mo agoLooks cool!
- Diti 3mo ago[flagged]
- __MatrixMan__ 3mo agoMaybe it's not the styling they're commenting on.
- drcongo 3mo agoYou know what extra data would be cool? If you hit `curl https://ip.guide/{src_ip} https://ip.guide/{src_ip}` and got back the ASN and country etc and added a leaderboard. In my own experiments in this area I've been gobsmacked by how much malicious traffic comes from Azure.
- reaperducer 3mo agoIn my own experiments in this area I've been gobsmacked by how much malicious traffic comes from Azure. I'm currently fighting this battle. As of this morning: 80% of malicious traffic comes from Azure. 10% from Digital Ocean. 5% from AWS. 5% from GCP.
- ok123456 3mo agoCloser to 95% if you count Teams.
- razodactyl 2mo agoI appreciate you.
- drcongo 3mo agoMine is very similar, but with DO and AWS swapped around.
- exiguus 3mo agoI have a similar experience with a tendency to Digital Ocean. Actually, I semi-automatically collect IPs that are banned by (mostly SSH) fail2ban and eBPF bans from dnsdist. These IPs are then merged into CIDRs, which are used as ipsets in a firewall ban chain. The IPs are collected on around ~20 Machines with public, static IPv4 and IPv6 addresses. Most of the Machines are in Canada and Europe. However, I have statistics for the CIDRs based on their whois record that look like: CIDRs used: 1255 Already cached: 1252 Skipped uncached targets: 0 IPs scanned total: 985300 Estimated throttled wait: 0.10 minutes == Country codes == Metric: Top 10 of 90 unique country codes Total: 1183 country codes total and 90 unique country codes in 1255 targets US 287 CN 132 NL 88 VN 53 DE 51 HK 45 AU 38 ID 36 RU 33 CA 27 == Regions == Metric: Top 10 of 29 unique regions Total: 334 regions total and 29 unique regions in 1255 targets CO 48 FL 40 WA 37 QLD 32 GA 26 NY 25 CA 23 TX 17 QC 15 UT 14 == Origin ASNs == Metric: Top 10 of 382 unique origin ASNs Total: 805 origin ASNs total and 382 unique origin ASNs in 1255 targets AS16276 26 AS132203 24 AS24086 18 AS38731 18 AS7552 18 AS24940 17 AS9808 15 AS135377 14 AS137718 13 AS62390 11 == Netnames == Metric: Top 10 of 630 unique netnames Total: 1157 netnames total and 630 unique netnames in 1255 targets RIPE 38 MSFT 31 SINGLEHOP 25 ACEVILLEPTELTD-SG 21 VIETTEL-VN 18 CMNET 17 APNIC 16 CHINANET-GD 14 VOLCANO-ENGINE 13 UCLOUD-HK 11 == Org names == Metric: Top 10 of 222 unique org names Total: 703 org names total and 222 unique org names in 1255 targets RIPE Network Coordination Centre 55 DigitalOcean, LLC 40 Asia Pacific Network Information Centre 32 Microsoft Corporation 31 Internap Holding LLC 25 HostPapa 23 Korea Telecom 20 Hetzner Online GmbH 17 China Mobile 16 ReliableSite.Net LLC 16 == Organizations == Metric: Top 10 of 236 unique organizations Total: 691 organizations total and 236 unique organizations in 1255 targets RIPE Network Coordination Centre (RIPE) 55 DigitalOcean, LLC (DO-13) 40 Asia Pacific Network Information Centre (APNIC) 32 Microsoft Corporation (MSFT) 31 Internap Holding LLC (IC-1425) 25 HostPapa (HOSTP-7) 23 ORG-HOA1-RIPE 17 ORG-CM1-AP 16 ReliableSite.Net LLC (RL-323) 15 FranTech Solutions (SYNDI-5) 13 == Domains == Metric: Top 10 of 534 unique domains Total: 2581 domains total and 534 unique domains in 1255 targets rdap.arin.net 404 apps.db.ripe.net 83 chinatelecom.cn 63 vnnic.vn 58 ripe.net 55 www.ripe.net 53 apnic.net 46 digitalocean.com 44 ovh.net 38 www.as14061.net 35 I deleted the (abuse) mail section. Because. 99% of the IPs are IPv4. In the IPset are mostly /32 but also a lot of ~/24 and rarely ~/16 segments. RIPE, ARIN and APNIC comes into play because some CIDR blocks are somewhat generously sized and block multiple network segments belonging to different organizations at the same time. E.g. this hides BR from the stats (because the ipset mostly bans every provider from BR).
- belval 3mo agoSomeone instantly started spamming the bee movie's introduction. Solid pun.
- preetham_rangu 3mo agoWatching the first few minutes was more educational than I expected.
- b0rbb 3mo agolol @ the person spamming Never Gonna Give You Up
- fragmede 3mo agoSSH to funky.nondeterministic.computer
- paoliniluis 3mo agoThere's a guy trying to take down the server by sending as user/pass the lyrics of Rick Astley's "never gonna give you up"
- KomoD 3mo agoFrom his home IP... very smart. https://ipinfo.io/86.120.252.156 https://ipinfo.io/86.120.252.156
- reaperducer 3mo agoProbably a relay through a "free" app installed on someone's phone or "smart" TV.
- KomoD 3mo agoNah, Spur (a company tracking residential proxies) doesn't flag it at all. He's most likely just not very smart.
- gruez 3mo ago>Nah, Spur (a company tracking residential proxies) doesn't flag it at all. I looked into it and so far as I can tell it works off a blacklist system, rather than any sort of automatic analysis (eg. TCP or MTU fingerprinting). If you set up a "residential proxy" in the form of a home VPN, it won't be detected. It also means the detection is only as good as whatever their backlist source is. If it's a niche provider, it might not get picked up at all.
- KomoD 3mo ago[dead]
- GreenVulpine 3mo agoThey're not doing a very good job at it, tried a few disposable free residential proxies - not flagged. Tried my CGNAT home connection - flagged. My phone connection - also flagged.
- spikk 3mo agoFor the sake of interest you could try to expose periodically rotated keyed hashes of IPs and credentials instead of the raw values. It would still let people correlate events within a limited time window
- Farrynet 3mo agoIts always wild seeing the sheer volume of background noice on public IPs. Fun project.
- _def 3mo agofun to watch until the ssh user input exploits the web interface :P
- polycancel 3mo ago[dead]
- fragmede 3mo agoWhat do you mean my SSH Login username can't be <script>alert('lol');
- throwaway7783 3mo agoVery cool! Adding a client geo would be nice (even if its not very accurate)
- fragmede 3mo agoYeah I have an SSH daemon running on the default port at funky.nondeterministic.computer for people to hit, but it's mostly bots, which is no fun.
- Human-Cabbage 3mo agoIs this the GTA 4 trailer?! /s It’s too bad that ssh doesn’t carry sound. A MIDI-style rendition of the song would really tie it all together.
- inigyou 3mo agoDo you allow them entry, present a fake prompt, and record what they do? Some time ago I did a little experiment by running `nc -l -p 23` (telnet) which connects the next incoming telnet connection to your console. Type in a simulated prompt like Password: or # and it'll be buffered until the connection comes in. Then see what the scanner sends.
- Fabricio20 3mo agoOpened the website to be greeted with only spam of huge walls of random text, seems people are abusing the fun out of it! Would love to actually have seen some interesting bot patterns from the authors comments.
- tusksm 3mo agoYou're right. HN traffic quickly turned the live feed from bot activity into a wall of human-generated test payloads. I'm already working on truncating long values and grouping events by source. The next step will probably be rate limiting noisy sources and separating likely human test traffic from recurring automated behavior. The recurring bot patterns are the part I ultimately want the interface to surface, rather than forcing visitors to inspect every raw event.
- throawayonthe 3mo agocan't you just keep the honeypot secret and detached from the interface? i guess someone might start scanning ips until their message pops up but still
- charcircuit 3mo agoLooking at it, all they do is install ssh keys. I honestly expected them to do more like start some kind of service.
- tusksm 3mo agoThat was my first impression too, since the SSH-key installation attempts are much more frequent and tend to dominate the feed. I did find at least one campaign that went further: it tried to fetch `http://41.216.189.157/run.sh http://41.216.189.157/run.sh` with wget or curl, execute it, and remove the script afterward. The downloader referenced payloads for aarch64, i386, loongarch64, and m68k, so it appears to be targeting a fairly broad set of Linux systems. I haven't fully analyzed the artifacts yet, so I can't say exactly what service or payload it ultimately installs. But it was definitely doing more than adding a key. This also exposed a weakness in the current UI: repetitive persistence attempts are prominent, while rarer download and execution chains are easy to miss.
- micheloosterhof 3mo agoCowrie author here! Yes this is the usual background noise on the internet! Cowrie (which I suspect is used here as well as the data generator) recently had a lot of updates, including now easy install from pip (pip install cowrie), and a much improved shell parser that’s much more capable of parsing attacker commands! https://github.com/cowrie/cowrie https://github.com/cowrie/cowrie and get the full raw data in JSON or other formats to add geoip and ASN attribution! And of course malware samples.
- tusksm 3mo ago[dead]
- asd000hh 3mo agoCooll!!!
- 1g10k 3mo ago[flagged]
- lightthemad 3mo ago[dead]
- guender 3mo ago[dead]
- jsabess24 2mo agoCool
- FelixKunzJr 2mo ago[dead]