# Extracting Config From Agent Tesla Rat

> Perform extracting config from agent tesla rat assessment during authorized security testing. Use this skill when indicators of the vulnerability class are present in the target environment.

- Skill: `wufufu770/extracting-config-from-agent-tesla-rat` (Agent Skill)
- Install (CLI): `npx skillmds@latest add wufufu770/extracting-config-from-agent-tesla-rat`
- Raw SKILL.md: https://api.skillmd.com/api/skills/wufufu770/extracting-config-from-agent-tesla-rat/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: Apache-2.0
- Author: wufufu770 (https://skillmd.com/u/wufufu770)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/wufufu770/extracting-config-from-agent-tesla-rat

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## TL;DR

- **目的**：Extracts embedded configuration from Agent Tesla RAT samples, including SMTP/FTP/Telegram exfiltration credentials, keylogger settings, and…
- **适用**：恶意软件分析/逆向
- **输入**：RAT 样本文件路径（HASH/MD5/SHA256）
- **输出**：配置审计报告 + 修复建议
- **红线**：仅限授权范围内；扫描限速 `-c 10 -rl 10`；所有动作记 oplog
- **关联**：上游：003-src-session-start → 下游：075-performing-malware-triage-with-yara, 074-performing-malware-ioc-extraction, 137-analyzing-malicious-pdf-with-peepdf

# Extracting Config from Agent Tesla RAT

## Overview

Agent Tesla is a .NET-based Remote Access Trojan (RAT) and keylogger that ranked among the top 10 malware variants in 2024, impacting 6.3% of corporate networks globally. It exfiltrates stolen credentials via SMTP email, FTP upload, Telegram bot API, or Discord webhooks. The malware configuration is embedded in the .NET assembly, typically obfuscated using string encryption, resource encryption, or custom loaders that decrypt and execute Agent Tesla in memory via .NET Reflection (fileless). Configuration extraction involves decompiling the .NET assembly with dnSpy or ILSpy, identifying the decryption routine for configuration strings, and extracting SMTP server addresses, credentials, FTP endpoints, Telegram bot tokens, and targeted applications.


## When to Use

- When performing authorized security testing that involves extracting config from agent tesla rat
- When analyzing malware samples or attack artifacts in a controlled environment
- When conducting red team exercises or penetration testing engagements
- When building detection capabilities based on offensive technique understanding

## Prerequisites

- dnSpy or ILSpy for .NET decompilation
- Python 3.9+ with `dnlib` or `pythonnet` for automated extraction
- de4dot for .NET deobfuscation
- Understanding of .NET IL code and Reflection
- Sandbox for dynamic analysis (ANY.RUN, CAPE)

## Workflow

### Step 1: Deobfuscate and Extract Configuration

```python
#!/usr/bin/env python3
"""Extract Agent Tesla RAT configuration from .NET assemblies."""
import re
import sys
import json
import base64
import hashlib
from pathlib import Path


def extract_strings_from_dotnet(filepath):
    """Extract readable strings from .NET binary for config analysis."""
    with open(filepath, 'rb') as f:
        data = f.read()

    # Extract US (User Strings) heap from .NET metadata
    strings = []

    # Look for common Agent Tesla config patterns
    patterns = {
        "smtp_server": re.compile(rb'smtp[\.\-][\w\.\-]+\.\w{2,}', re.I),
        "email": re.compile(rb'[\w\.\-]+@[\w\.\-]+\.\w{2,}'),
        "ftp_url": re.compile(rb'ftp://[\w\.\-:/]+', re.I),
        "telegram_token": re.compile(rb'\d{8,10}:[A-Za-z0-9_-]{35}'),
        "telegram_chat": re.compile(rb'(?:chat_id=|chatid[=:])[\-]?\d{5,15}', re.I),
        "discord_webhook": re.compile(rb'https://discord\.com/api/webhooks/\d+/[\w-]+'),
        "password": re.compile(rb'(?:pass(?:word)?|pwd)[=:]\s*[\w!@#$%^&*]{4,}', re.I),
        "port": re.compile(rb'(?:port|smtp_port)[=:]\s*\d{2,5}', re.I),
    }

    results = {}
    for name, pattern in patterns.items():
        matches = pattern.findall(data)
        if matches:
            results[name] = [m.decode('utf-8', errors='replace') for m in matches]

    # Extract Base64-encoded strings (common obfuscation)
    b64_pattern = re.compile(rb'[A-Za-z0-9+/]{20,}={0,2}')
    b64_decoded = []
    for match in b64_pattern.finditer(data):
        try:
            decoded = base64.b64decode(match.group())
            text = decoded.decode('utf-8', errors='strict')
            if text.isprintable() and len(text) > 5:
                b64_decoded.append(text)
        except Exception:
            pass

    if b64_decoded:
        results["base64_decoded_strings"] = b64_decoded[:30]

    return results


def decrypt_agenttesla_strings(data, key_hex):
    """Decrypt Agent Tesla encrypted configuration strings."""
    key = bytes.fromhex(key_hex)
    # Agent Tesla V1: Simple XOR with key
    decrypted_strings = []

    # Find encrypted blobs (high-entropy byte sequences)
    blob_pattern = re.compile(rb'[\x80-\xff]{16,256}')
    for match in blob_pattern.finditer(data):
        blob = match.group()
        # Try XOR decryption
        decrypted = bytes(b ^ key[i % len(key)] for i, b in enumerate(blob))
        try:
            text = decrypted.decode('utf-8', errors='strict')
            if text.isprintable() and len(text.strip()) > 3:
                decrypted_strings.append(text.strip())
        except UnicodeDecodeError:
            pass

    # V2: SHA256-based key derivation then AES
    sha256_key = hashlib.sha256(key).digest()

    return decrypted_strings


def analyze_exfiltration_config(config):
    """Analyze extracted configuration for exfiltration methods."""
    methods = []

    if config.get("smtp_server"):
        methods.append({
            "type": "SMTP",
            "servers": config["smtp_server"],
            "emails": config.get("email", []),
        })

    if config.get("ftp_url"):
        methods.append({
            "type": "FTP",
            "urls": config["ftp_url"],
        })

    if config.get("telegram_token"):
        methods.append({
            "type": "Telegram",
            "tokens": config["telegram_token"],
            "chat_ids": config.get("telegram_chat", []),
        })

    if config.get("discord_webhook"):
        methods.append({
            "type": "Discord",
            "webhooks": config["discord_webhook"],
        })

    return methods


if __name__ == "__main__":
    if len(sys.argv) < 2:
        print(f"Usage: {sys.argv[0]} <agent_tesla_sample>")
        sys.exit(1)

    config = extract_strings_from_dotnet(sys.argv[1])
    methods = analyze_exfiltration_config(config)

    report = {"raw_config": config, "exfiltration_methods": methods}
    print(json.dumps(report, indent=2))
```

## Validation Criteria

- Exfiltration method identified (SMTP/FTP/Telegram/Discord)
- Server addresses and credentials extracted from config
- Targeted applications list recovered
- Keylogger and screenshot capture settings documented
- Persistence mechanism identified
- IOCs suitable for network blocking extracted

## References

- [Splunk - Agent Tesla Detection and Analysis](https://www.splunk.com/en_us/blog/security/inside-the-mind-of-a-rat-agent-tesla-detection-and-analysis.html)
- [Qualys - Catching the RAT Agent Tesla](https://blog.qualys.com/vulnerabilities-threat-research/2022/02/02/catching-the-rat-called-agent-tesla)
- [ANY.RUN Agent Tesla Analysis](https://any.run/malware-trends/agenttesla/)
- [Trustwave - Agent Tesla Novel Loader](https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/agent-teslas-new-ride-the-rise-of-a-novel-loader/)
- [Malpedia - Agent Tesla](https://malpedia.caad.fkie.fraunhofer.de/details/win.agent_tesla)

## Tools & Systems

- **Cuckoo Sandbox** — Automated dynamic analysis
- **CAPE Sandbox** — Config extraction + evasion detection
- **Any.run** — Cloud-based interactive sandbox
- **Ghidra** — NSA's reverse engineering framework
- **dnSpy** — .NET assembly decompiler
- **PE Studio** — Static PE analysis
- **Volatility** — Memory forensics
- **YARA** — Pattern-based malware identification

Run all tools in isolated sandbox environment. Never connect to production networks.