persistence▌

Detect T1547.001 startup folder persistence by monitoring Windows startup directories for suspicious file creation, analyzing autoruns entries, and using Python watchdog for real-time filesystem monitoring.

Detect suspicious Windows service installations (MITRE ATT&CK T1543.003) by parsing System event logs for Event ID 7045, analyzing service binary paths, and identifying indicators of persistence mechanisms.

Systematically remove malware, backdoors, and attacker persistence mechanisms from infected systems while ensuring complete eradication and preventing re-infection.

Hunt for DNS-based persistence mechanisms including DNS hijacking, dangling CNAME records, wildcard DNS abuse, and unauthorized zone modifications using passive DNS databases, SecurityTrails API, and DNS audit log analysis.

Hunt for registry-based persistence mechanisms including Run keys, Winlogon modifications, IFEO injection, and COM hijacking in Windows environments.

Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.

Detect malicious email forwarding rules created by adversaries to maintain persistent access to email communications for intelligence collection and BEC attacks.

Detect MITRE ATT&CK T1547.001 registry Run key persistence by analyzing Sysmon Event ID 13 logs and registry queries to identify malicious auto-start entries.

ln-650-persistence-performance-auditor

Thread-safe data persistence in Swift using actors with in-memory cache and file-backed storage. \n \n Implements an actor-based repository pattern that eliminates data races at compile time, replacing manual synchronization with Swift's actor model \n Combines fast O(1) in-memory lookups with atomic file persistence, supporting any Codable & Identifiable model type \n Provides synchronous initialization to avoid async complexity, with automatic await enforcement on all public API calls \n