Here’s a concise breakdown of challenging samples for testing
@danb LLM, designed to highlight key areas of detection strength and weakness:
Tricky Malware Samples:
•Evasive Code: Malware using polymorphic/metamorphic code, heavy packing/encryption, or anti-analysis techniques (anti-VM, anti-debugging). The core malicious logic is hidden or constantly changing.
•"Living Off The Land" (LotL): Malicious use of legitimate system tools like PowerShell, WMIC, or Certutil. The tools themselves are benign; the danger lies in their contextual misuse.
•Complex Obfuscation: Code with convoluted control flow, junk instructions, hidden strings, or dynamic API calls. This makes raw code analysis difficult.
Tricky False Positive Samples:
•Benign Tools Mimicking Malware: Legitimate admin software (e.g., remote access tools, network scanners, pen-testing utilities) that perform actions similar to malicious activity (e.g., network connections, registry changes, process injection).
•Legitimate Installers/Updaters: Software that legitimately modifies system files, creates services, or downloads components, resembling malware installation.
•Obfuscated Benign Code: Lawful applications or scripts that use packing, compression, or intentional obfuscation (for IP protection) which might trigger generic suspicious patterns.
•User Scripts: Personal automation scripts that perform unusual system interactions (e.g., mass file operations, non-standard downloads) but are entirely benign in intent.
Focusing on these areas will provide a robust benchmark for SiriusLLM's ability to discern true malicious intent from complex or ambiguous code.
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