Iranian state-sponsored hackers affiliated with the Imperial Kitten group have been identified conducting cyberattacks against Israeli logistics, transportation, and technology companies, aiming to steal data and credentials. Security company CrowdStrike, which observed the attacks occurring between 2022 and 2023, highlighted the group’s tactics, including luring victims to attacker-controlled domains, phishing, credential theft, and exploiting publicly announced vulnerabilities.
Imperial Kitten, linked to Iran’s Islamic Revolutionary Guard Corps, has a history of targeting defense, aviation, maritime, IT, and logistics sectors to gather intelligence. The cybercrime group deploys a sophisticated toolkit, leveraging methods such as phishing emails with macro-enabled Excel documents, open-source tools for lateral movement, and .NET-based malware for data exfiltration.
During a specific operation analyzed by CrowdStrike in October, Imperial Kitten utilized phishing emails to deliver macro-enabled Excel documents. Upon enabling macros, the document initiated a process extracting three batch files that executed a reverse shell connecting to a specified IP address on TCP port 6443. The group also employs publicly available tools like PAExec, NetScan, PsExec, and a command-line utility called ProcDump to facilitate lateral movement and credential harvesting.
CrowdStrike identified the use of IMAPLoader, a .NET-based malware, observed for the first time in September, as part of the group’s toolkit. The malware uses email as a command-and-control channel to communicate with operators and is distributed as a dynamic link library loaded via AppDomainManager injection.
Another .NET malware, StandardKeyboard, was deployed by Imperial Kitten, utilizing email for C2 communication and executing Base64-encoded commands. CrowdStrike’s attribution is based on Imperial Kitten’s consistent focus on Israeli targets, the use of job-themed phishing emails, and reliance on previously used web compromise infrastructure. The assessment was made with low confidence due to indicators relying on single-source reporting.