EXECUTIVE SUMMARY:
An observed campaign leverage advanced generative-AI techniques to accelerate the reverse-engineering of the loader family commonly known as XLoader. The malware authors continue to deploy obfuscation and encryption tactics multiple packing layers, runtime decryption, sandbox and debugger evasions, and a large set of decoy domains and fake endpoints. Conventional sandboxing and purely manual static analysis workflows are increasingly insufficient to keep pace.
The malware examined utilized several defensive techniques, including multiple RC4-based encryption layers, runtime decryption of embedded code, obfuscated API calls using hashed or XOR-modified import tables, and decoy functions to mislead analysts. To address these barriers, the research employed a generative AI model trained to interpret and process exported disassembly data such as functions, strings, and data segments. This model generated functional IDAPython scripts capable of reconstructing decryption routines, identifying cryptographic keys, and restoring the original program structure. The workflow combined automated reasoning with manual validation to accurately trace decryption patterns and handle dynamic components. Two analysis modes were explored, a live, integrated pipeline using the Model Context Protocol (MCP) and an offline approach leveraging structured data exports for cloud-based analysis.
It indicates that generative AI can substantially accelerate reverse engineering by automating repetitive analytical steps, improving accuracy in decryption workflows, and enhancing collaborative malware analysis. Despite these advancements, human expertise remains vital for interpreting novel obfuscation methods, validating AI-generated scripts, and addressing dynamic elements beyond the models current capabilities. This hybrid approach underscores AIs growing role as a powerful tool that complements, rather than replaces, traditional reverse-engineering skills in modern operations.
THREAT PROFILE:
| Tactic | Technique Id | Technique | Sub-technique |
| Initial Access | T1566.002 | Phishing | Spearphishing Link |
| T1189 | Drive-by Compromise | — | |
| Execution | T1204.002 | User Execution | Malicious File |
| T1059.005 | Command and Scripting Interpreter | Visual Basic | |
| Persistence | T1547.001 | Boot or Logon Autostart Execution | Registry Run Keys / Startup Folder |
| T1543.003 | Create or Modify System Process | Windows Service | |
| Defense Evasion | T1027.002 | Obfuscated Files or Information | Software Packing |
| T1562.001 | Impair Defenses | Disable or Modify Tools | |
| Credential Access | T1555.004 | Credentials from Password Stores | Windows Credential Manager |
| Discovery | T1083 | File and Directory Discovery | — |
| Collection | T1113 | Screen Capture | — |
| Command and Control | T1071.001 | Application Layer Protocol | Web Protocols |
| Exfiltration | T1041 | Exfiltration Over C2 Channel | — |
MBC MAPPING:
| Objective | Behavior ID | Behavior |
| Anti-Behavioral Analysis | B0001 | Debugger Detection |
| Anti-Static Analysis | B0012 | Disassembler Evasion |
| E1027 | Obfuscated Files or Information | |
| Collection | E1056 | Input Capture |
| Command and Control | B0030 | C2 Communication |
| Discovery | B0013 | Analysis Tool Discovery |
| Execution | B0011 | Remote Commands |
| Persistence | F0012 | Registry Run Keys / Startup Folder |
| Privilege Escalation | E1055 | Process Injection |
REFERENCES:
The following reports contain further technical details: