Accelerating EDR Evasion with LLM-Driven Analysis

#EDR #LLM

New Stealit Campaign Abuses Node.js Single Executable Application

#SEA #Nodejs #malware

tl;dr
really effective malware multi-staged, multiple programming languages, use as many dependencies as possible. AI making this easier to do. AVs struggling

Historically, in regards to malware development, the end goal was minimalism. It was in your best interest to strip as many dependencies, shred the file size down, and make it position independent.

I think, as of ... now ... we need to take a different approach.

I think instead of stripping binaries, we (Red Team, Threat Emulation, malware developers) should intentionally introduce dependencies.

I have witnesses two unique things in the malware landscape since the AI boom.

1. Increase in malware slop. I continue to see stagers which contain notes in them. This is not intentional and this does not "trick" the analyst. This is a colossal mistake on the malware developers part. However, despite it being slop, AI has made malware more diverse. I am seeing more and more malware in Lua, Node JS (including SEA and nexe), Java, and Python. I am seeing more and more malware doing inter-process communication across multiple programming languages. Of course all of these have existed prior to AI, but I am seeing an explosion in these languages. This also has resulted in malware researchers creating new tools to combat this malware diversity.

2. Anti-malware services struggling. When I encounter a binary that is a Node JS SEA blob (Electron JS .exe, self-contained using SEA), which extracts a .JS payload, which uses obfuscated Java or heavily obfuscated Lua, all of these languages require a VM (PVM, LVM, JVM, whatever) for interpretation. Thus, with heavy obfuscation and multistaging, static analysis fails and the heavy abstraction makes it difficult for traditional hooking or minifilters to be effective, in essence there is too much noise. Many of these payloads with heavy dependencies easily avoid static analysis and even some emulation systems because they fail to account for the necessary dependencies which are required to emulate it correctly.

pic maybe related idk

The Defensive Stack is Exposed: LLMs, Reverse Engineering, and the End of Opaque Defense

#LLM #EDR

Persistence via Fake AMSI Provider | Playbook & Detection Strategies

#persistence #amsi

Red Team Engineering 2026

Info : https://nostarch.com/red-team-engineering

#redteam

Archive gems, don't bookmark.

#EDR

🔓 Dumping NTLM Hashes from Windows Memory via forensics tools
What can an attacker recover from a Windows memory image after gaining access to an endpoint?

In my new blog, I explored:
WinPmem → Volatility 3 → SYSTEM/SAM → NTLM

#RedTeam #OffensiveSecurity