{"id":59808,"date":"2025-12-08T00:00:00","date_gmt":"2025-12-08T00:00:00","guid":{"rendered":"urn:uuid:5886d7f9-4d21-6eef-6093-8c0699ec2eb3"},"modified":"2025-12-08T00:00:00","modified_gmt":"2025-12-08T00:00:00","slug":"ai-automated-threat-hunting-brings-ghostpenguin-out-of-the-shadows","status":"publish","type":"post","link":"https:\/\/www.threatshub.org\/blog\/ai-automated-threat-hunting-brings-ghostpenguin-out-of-the-shadows\/","title":{"rendered":"AI-Automated Threat Hunting Brings GhostPenguin Out of the Shadows"},"content":{"rendered":"<p><img decoding=\"async\" src=\"https:\/\/trendmicro.scene7.com\/is\/image\/trendmicro\/GhostPenguin_thumbnail:Large?qlt=80\"><\/p>\n<div><img decoding=\"async\" src=\"https:\/\/www.trendmicro.com\/content\/dam\/trendmicro\/global\/en\/research\/thumbnails\/GhostPenguin_thumbnail.jpg\" class=\"ff-og-image-inserted\"><\/div>\n<h2><span class=\"body-subhead-title\">Threat hunting approach<\/span><\/h2>\n<p>Our approach focused on collecting, processing, and analyzing a large number of malware samples from known and reported attacks. The goal was to extract useful artifacts that help hunt for new, undetected threats.<\/p>\n<p><b>Hunting workflow<\/b><\/p>\n<p><b>1. Collect and extract artifacts<\/b><br \/>We gather many malware samples from known and reported attacks and extract key information from them such as strings, API calls, behaviors, function names, variable names, and constants. All collected data is stored in a structured database. Afterwards, we tag and categorize the samples so they are easier to search and compare.<\/p>\n<p><b>2. Build VirusTotal hunting queries<\/b><br \/>Using the extracted artifacts, we create VirusTotal hunting rules and run them against samples with zero detections. When we find potential candidates, pass the samples to the profiling stage.<\/p>\n<p><b>3. Profiling and analysis<\/b><br \/>Binary files are sent to IDA Pro (Hex-Rays) for decompilation and further artifact extraction. CAPA also utilized to identify specific capabilities (A custom rule has been generated based on the artifacts collected during Stage 1). Non-binary files like scripts or code are passed directly to the profiler for feature extraction. The profiler subsequently generates a unified profile in JSON format for each file, which is then forwarded to the next stage of analysis.<\/p>\n<p>The AI agent Quick Inspect reviews the JSON profile created during the profiling stage. It analyzes the artifact, scores it, and determines if the file is malicious or not. Files below the threshold go into a monitoring list for later review, while files above the threshold tagged as malicious and move to the next stage.<\/p>\n<p>The Deep Inspector agent performs a deeper analysis on files that pass the threshold and are tagged as malicious. It generates a detailed analysis report for the file based on the decompiled code and the metadata created during the profiling stage. The agent reviews the file profile and produces a code-analysis report that includes:<\/p>\n<ul>\n<li><span class=\"rte-red-bullet\">A short summary<\/span><\/li>\n<li><span class=\"rte-red-bullet\">Identified capabilities<\/span><\/li>\n<li><span class=\"rte-red-bullet\">Code execution flow<\/span><\/li>\n<li><span class=\"rte-red-bullet\">Technical analysis<\/span><\/li>\n<li><span class=\"rte-red-bullet\">MITRE ATT&amp;CK framework mapping<\/span><\/li>\n<\/ul>\n<p>We used this pipeline to hunt for a VirusTotal zero-detection sample that we named GhostPenguin. The sample was submitted on July 7, 2025, and remained undetected in VirusTotal for more than four months.<\/p>\n<p>If a file is packed or obfuscated, the YARA scanner and AI model usually detect this and tags it. If you have automated scripts for unpacking, you can set up an MCP server that can route these files to your unpacking pipeline for dynamic, static, or manual unpacking. Simple obfuscation and unpacking process can often be handled directly by AI (by a AI resolver or AI generating script for deobfuscation\/unpacking), but heavy or complex obfuscation should be processed by external automation, custom scripts or manual efforts.<i><\/i><\/p>\n<p> Read More <a href=\"https:\/\/www.trendmicro.com\/en_us\/research\/25\/l\/ghostpenguin.html\">HERE<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this blog entry, Trend\u2122 Research provides a comprehensive breakdown of GhostPenguin, a previously undocumented Linux backdoor with low detection rates that was discovered through AI-powered threat hunting and in-depth malware analysis. Read More HERE&#8230;<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_layout":"default_layout","footnotes":""},"categories":[61],"tags":[9510,9534,9509],"class_list":["post-59808","post","type-post","status-publish","format-standard","hentry","category-trendmicro","tag-trend-micro-research-articles-news-reports","tag-trend-micro-research-latest-news","tag-trend-micro-research-research"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI-Automated Threat Hunting Brings GhostPenguin Out of the Shadows 2026 | ThreatsHub Cybersecurity News<\/title>\n<meta name=\"description\" content=\"ThreatsHub Cybersecurity News | ThreatsHub.org | Cloud Security &amp; Cyber Threats Analysis Hub. 100% Free OSINT Threat Intelligent and Cybersecurity News.\" \/>\n<meta name=\"robots\" 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