NVIDIA H100

Researchers Deploy Cowrie Honeypot Disguised as NVIDIA H100 Server to Study SSH Botnet Tactics

A cybersecurity team set up a realistic Cowrie honeypot on a fake server equipped with four NVIDIA H100 GPUs, 128 AMD EPYC cores, and terabytes of storage to observe what SSH brute-force bots actually do after gaining access. The trap used a custom StickyAuth module that allowed entry only after several failed attempts and locked in the successful credential pair per IP address. Over the first 12.5 hours the system recorded 1,846 connections from 126 unique IPs, 175 successful logins, and 1,524 commands executed, with the majority of activity traced to a single botnet linked to the Outlaw group. The attackers deployed SSH keys signed mdrfckr, changed the root password, killed competing processes, installed cron jobs, and downloaded a mining archive called dota3 containing an IRC backdoor and its own SSH scanner. The researchers also identified three realism issues in the base Cowrie setup—limited grep flags, outdated filesystem paths in Debian 12, and inconsistent hostname reporting—and patched them to keep sophisticated bots engaged longer. An auxiliary LLM service later summarized each session in Telegram for easier analysis.

Rubytech Tests Russian LLM Cotype 3 on Chinese GPUs Matching NVIDIA H100 Performance

Rubytech has successfully tested the Russian large language model Cotype 3 developed by MWS AI on Chinese graphics accelerators instead of NVIDIA hardware. The trials took place on the Skala^r AI machine software-hardware complex and demonstrated stable operation with inference performance comparable to configurations using NVIDIA H100 GPUs. Eight Chinese GPUs were used in the test system, delivering an average first-token generation time of about 8 seconds and inter-token latency between 111 ms when processing 27,000-token contexts. Engineers adapted drivers, software environments, and orchestration tools, achieving up to 2-2.2 times faster performance in certain scenarios compared to the standard Chinese GPU setup. The results indicate that corporate AI infrastructure can be built without mandatory reliance on NVIDIA accelerators, which is particularly relevant for government agencies, state-owned companies, and critical information infrastructure organizations requiring localized model deployment and controlled scaling. Rubytech also noted potential reductions in total cost of ownership with Chinese GPUs, although the company emphasized this is an additional option rather than a complete replacement for NVIDIA solutions.