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Introduction
Attackers are increasingly leveraging custom virtual machines (VMs) to evade traditional endpoint detection and response (EDR) systems. Praetorian’s Centurion pushes this boundary further—a virtualized loader built around a bespoke x86-64-inspired instruction set architecture (ISA) and a freestanding C runtime, delivering a fully functional TLS bind shell that executes entirely within an interpreter layer, all generated in one week with LLM assistance.
Learning Objectives
- Understand how a custom ISA and virtualized loader can bypass static and behavioral detection mechanisms.
- Analyze the components of a TLS bind shell deployed inside a lightweight VM, including PE loader, TLS stack, and HTTP client.
- Learn practical detection, reverse engineering, and mitigation techniques for such “Bring Your Own Execution Environment” (BYOEE) threats.
You Should Know
- Inside the Custom VM: ISA, Freestanding C Runtime, and the Interpretation Layer
Centurion implements a virtualized loader that does not rely on the host OS’s native execution environment. Instead, it defines its own x86-64-inspired ISA—meaning every instruction (mov, add, syscall emulation) is interpreted by a lightweight software runtime. The freestanding C runtime (no libc, no OS dependencies) handles memory management, TLS negotiation, and HTTP client logic behind the interpreter.
What this does: The payload (e.g., a bind shell) is compiled to this custom bytecode, not native x86. The loader only exposes a minimal interpreter. Signature-based AV sees no known PE headers or API calls—only opaque bytecode.
Step‑by‑step guide to emulate a simple custom VM for analysis:
Python-based custom VM interpreter (for educational analysis)
import struct
class CustomVM:
def <strong>init</strong>(self, bytecode):
self.regs = [bash]8 8 general purpose registers
self.memory = bytearray(4096)
self.pc = 0
self.bytecode = bytecode
def fetch(self):
op = self.bytecode[self.pc]
self.pc += 1
return op
def run(self):
while self.pc < len(self.bytecode):
op = self.fetch()
if op == 0x01: MOV reg, imm
reg = self.fetch()
val = struct.unpack('<Q', self.bytecode[self.pc:self.pc+8])[bash]
self.pc += 8
self.regs[bash] = val
elif op == 0x02: SYSCALL (emulate write)
Emulate TLS send
print(f"[bash] Syscall: write reg1={self.regs[bash]}")
... add more opcodes
Detection: Monitor for high‑entropy bytecode blobs that invoke no common Windows/Linux syscalls, combined with memory allocation with `PAGE_EXECUTE_READWRITE` and a tight interpreter loop (e.g., while(pc < end) { switch(pc++) }).
- Building the TLS Bind Shell: How the PE Loader and TLS Stack Operate Behind Interpreter
A bind shell listens on a port and gives the attacker a remote shell. Centurion’s version uses TLS encryption (certificate validation, session keys) and runs inside the VM. The PE loader (normally used to load DLLs/exes) is repurposed to load the shellcode into the VM’s memory space, while the TLS stack handles network I/O—all inside the interpreter.
Linux command to inspect a suspicious process’s open ports and TLS libraries:
Find process listening on a high port (e.g., 4443)
sudo netstat -tulpn | grep -E "LISTEN.[0-9]{4}"
sudo ss -tulpn | grep 4443
Check which process handles TLS (look for libssl or custom binaries)
lsof -p <PID> | grep -E "libssl|libcrypto"
If no standard libs loaded but a TLS socket exists → suspect custom VM
Windows equivalent (PowerShell):
Get-1etTCPConnection -State Listen | Where-Object {$<em>.LocalPort -gt 1024}
Get-Process -Id (Get-1etTCPConnection -LocalPort 4443).OwningProcess | Select-Object ProcessName, Path
Check loaded modules:
Get-Process -Id <PID> | Select-Object -ExpandProperty Modules | Where-Object {$</em>.ModuleName -like "ssl"}
Mitigation: Deploy network-layer TLS inspection (decryption proxy) for egress traffic. For bind shells, restrict inbound connections to only trusted IPs via host-based firewall (iptables/netsh advfirewall).
- LLM-Assisted Development: Rapid Offensive Tooling and Its Defensive Countermeasures
The post states Centurion was built in “roughly a week of LLM-assisted development.” LLMs excel at generating boilerplate for custom interpreters, protocol parsers (TLS, HTTP), and shellcode loaders. This lowers the barrier for attackers to create bespoke, signature‑free malware.
What defenders can do: Use LLMs to generate detection rules, fuzzers, and deobfuscation scripts. For example, prompt an LLM to “write a YARA rule to detect a custom VM loop with high entropy bytecode and unusual syscall emulation.”
Sample YARA rule (generated by LLM concept):
rule Custom_VM_Interpreter_Loop {
meta:
description = "Detects typical VM interpreter switch-case loop"
strings:
$vm_loop = { 48 8B ?? ?? 48 83 ?? ?? 74 ?? 0F B6 ?? 48 83 ?? ?? 48 FF ?? EB ?? } // example x86 pattern
$high_entropy_blob = /[0-9a-f]{256,}/ fullword ascii
condition:
uint16(0) == 0x5A4D and // MZ header? not required for custom VM
($vm_loop and filesize < 200KB) or ($high_entropy_blob)
}
Step‑by‑step guide to use YARA:
1. Install YARA: `sudo apt install yara` (Linux) or download from GitHub for Windows.
2. Save the rule as centurion_detect.yar.
3. Scan a suspicious file: yara centurion_detect.yar /path/to/binary.
- Reverse Engineering the Custom ISA: Dynamic Analysis with QEMU and Custom Disassemblers
Since Centurion uses a non‑standard ISA, traditional disassemblers (IDA, Ghidra) fail. You must build a custom disassembler or emulate the bytecode. One approach: modify QEMU’s TCG (Tiny Code Generator) to support the new ISA, or use Unicorn Engine (a lightweight CPU emulator) to run the bytecode in a sandbox.
Linux commands to set up Unicorn for analysis:
pip install unicorn Sample Python script to load custom bytecode and hook syscalls
from unicorn import
from unicorn.x86_const import
def hook_syscall(uc, intno, user_data):
Capture emulated syscalls (e.g., socket, bind, listen)
eax = uc.reg_read(UC_X86_REG_EAX)
print(f"Intercepted syscall: {eax}")
Force return to avoid actual network
uc.reg_write(UC_X86_REG_EAX, -1)
mu = Uc(UC_ARCH_X86, UC_MODE_64)
Load custom bytecode at address 0x1000000
mu.mem_map(0x1000000, 0x10000)
mu.mem_write(0x1000000, custom_bytecode)
mu.hook_add(UC_HOOK_INTR, hook_syscall)
mu.emu_start(0x1000000, 0x1000000 + len(custom_bytecode))
Detection of emulation: Attackers can add anti‑emulation checks (e.g., timing differences, CPUID). Defenders can use Intel PT (Processor Trace) on Linux with `perf` to record actual executed branches even inside a VM interpreter.
- Cloud Hardening Against BYOEE Payloads: Network Segmentation and eBPF Monitoring
Cloud workloads (AWS, Azure, GCP) often allow arbitrary user code in containers or VMs. A TLS bind shell inside a custom VM can call out to C2 or accept inbound connections if security groups are misconfigured.
Best practices:
– Default deny inbound rules for all ports >1024 in security groups.
– Use eBPF (extended Berkeley Packet Filter) on Linux hosts to monitor execve and memory protection changes.
Example eBPF program (bpftrace) to detect `mmap` with `PROT_EXEC` and MAP_ANONYMOUS:
sudo bpftrace -e 'tracepoint:syscalls:sys_enter_mmap /args->prot & 0x04/ { printf("PROT_EXEC mmap by %d (%s) size %ld\n", pid, comm, args->len); }'
Windows counterpart: Use Sysmon (Event ID 10 for ProcessAccess, Event ID 12/13/14 for registry changes) combined with custom detection rules for unusual memory allocation patterns.
- Mitigation: Deploying Application Control and Constrained Language Runtimes
Because Centurion delivers a custom VM that does not invoke PowerShell, cmd, or bash directly, traditional application whitelisting (AppLocker, Software Restriction Policies) may miss it. However, you can enforce that only signed binaries from trusted publishers can execute, and use Microsoft Defender for Endpoint’s “Block Win32 API calls from Office macros” or similar rules.
Linux solution: Use SELinux in enforcing mode with custom policies that prevent any process from creating executable memory unless it’s a verified runtime (e.g., only `/usr/bin/python3` allowed to `mmap` with PROT_EXEC). Example command to check SELinux denials:
sudo ausearch -m avc -ts recent | grep "mmap"
Step‑by‑step to enable strict AppLocker on Windows:
- Open `secpol.msc` → Application Control Policies → AppLocker.
- Create a default rule to allow “All users” to run files in `Program Files` and
Windows. - Create a deny rule for `%USERPROFILE%\AppData\Local\Temp\.exe` and
.bin.
4. Update Group Policy with `gpupdate /force`.
What Undercode Say
- Key Takeaway 1: Centurion demonstrates how LLMs enable rapid creation of highly evasive, custom‑ISA malware in days—bypassing static detection and many sandboxes.
- Key Takeaway 2: Defenders must shift to behavioral monitoring (eBPF, syscall hooks, memory protection anomalies) and network TLS inspection, as signature‑based tools are blind to custom VM interpreters.
Analysis: The “Bring Your Own Execution Environment” model is a natural evolution from fileless malware and process injection. By moving the execution context into an interpreter that emulates a completely different architecture, attackers reset the playing field. Traditional EDRs rely on known syscall sequences, PE structure, and API call stacks—none of which are present. However, this approach is not invisible: the interpreter loop itself leaves a detectable CPU and memory access pattern (tight loop, high entropy, no standard library loading). Blue teams can leverage hardware tracing (Intel PT, Arm ETM) and AI‑driven anomaly detection on low‑level microarchitectural events. The LLM‑assisted development of such tools also means defenders can use LLMs to generate counter‑measures at the same speed—e.g., auto‑generating decoy VM bytecode to poison attacker threat feeds or creating specialized binary emulators to sandbox and extract C2 configurations. The race is now between offensive LLM‑generated custom ISAs and defensive LLM‑generated dynamic analyzers.
Prediction
- -1 Rapid proliferation of bespoke VMs in commodity malware: As LLM tooling improves, even low‑skill attackers will deliver custom‑ISA loaders, forcing every EDR to incorporate dynamic binary translation and high‑cost emulation, increasing detection latency and false positives.
- +1 AI‑driven defensive emulation as a service: Cloud providers and security vendors will offer “plug‑and‑play” custom‑ISA sandboxes that automatically infer unknown instruction sets and extract IOCs in real time, rebalancing the cost equation.
- -1 Increased abuse of legitimate TLS and HTTP stacks inside custom VMs: Traditional network monitoring (DPI without decryption) will fail to detect bind shells that encrypt traffic within the VM’s own TLS stack, leading to wider adoption of mandatory mTLS and egress TLS inspection proxies, increasing operational overhead.
- +1 Standardization of anti‑VM‑escape hardware features: CPU vendors (Intel, AMD, ARM) will introduce new instructions to allow the OS to detect or limit nested interpretation loops, giving defenders a low‑level primitive to flag possible BYOEE payloads without full emulation.
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IT/Security Reporter URL:
Reported By: Abelousova Centurion – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
