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Introduction:
Attackers are constantly evolving their distribution methods, and the recent HijackLoader campaign via the Spanish website PiviGames is a prime example. By luring users with promises of free game downloads, the site delivers a sophisticated loader that employs multi-layer obfuscation, hash-based API resolution, and encrypted payloads. This article provides a hands‑on guide to dissecting HijackLoader, leveraging the specialized tools released by malware researchers, and understanding the step‑by‑step analysis required to uncover its hidden components.
Learning Objectives:
- Understand the infection chain and the role of HijackLoader in delivering secondary payloads.
- Learn to use hash‑resolving, decryption, and configuration‑extraction tools in a malware analysis workflow.
- Master manual and automated techniques for unpacking, debugging, and detecting this loader family.
You Should Know:
1. The Infection Chain: How PiviGames Distributes HijackLoader
The attack begins when a user visits PiviGames (pivigames[.]blog) and downloads what appears to be a free game installer. The downloaded executable is actually a dropper that extracts and executes HijackLoader. To observe this behavior safely, set up a Windows sandbox (e.g., FLARE VM) and use Sysinternals Process Monitor (ProcMon) to capture file system, registry, and process activity.
Step‑by‑step guide:
- Download and run ProcMon as Administrator.
- Apply a filter: `Process Name` – `is` – `the_dropper.exe` – then
Include. - Execute the suspicious installer in the sandbox.
- Look for writes to `%AppData%` or `%Temp%` that create new executables.
- Use Regshot to take a before‑and‑after snapshot of the registry; compare to identify persistence mechanisms (e.g., Run keys).
- Extracting the First Stage: Resolving API, Process, and Module Hashes
HijackLoader avoids storing plaintext API names; instead, it uses a hashing algorithm (often a variant of ROR13) to resolve addresses at runtime. The researchers’ tool can resolve these hashes automatically, but you can also perform manual analysis.
Step‑by‑step guide:
- Load the sample into a disassembler (IDA Pro or Ghidra) and locate the hash‑resolution loop.
- Identify the hashing algorithm by tracing the input (function name strings) and the output hash.
- Use the provided Python script (or write your own) to iterate over a list of common Windows API names and compute their hashes.
- Example command to extract strings from the binary:
`strings -n 8 malicious.exe > strings.txt` (Linux)
Then cross‑reference with the resolved hashes in the debugger.
– Once hashes are resolved, you can set breakpoints on the actual API calls (e.g., VirtualAlloc, CreateFile) to monitor behavior.
3. Decrypting Stage 2 Payload
The first stage typically contains an encrypted second stage embedded as a resource or appended to the file. The decryption key is often derived from the malware’s own code or from environmental data. The researchers’ tool automates this, but understanding the process is crucial.
Step‑by‑step guide:
- In a debugger (x64dbg), set a breakpoint after the decryption routine (look for loops with XOR or AES instructions).
- Dump the decrypted buffer to disk using a script:
`WriteDump(“stage2.bin”, decrypted_address, size)`.
- Alternatively, use the public decryptor:
`python decrypt_stage2.py -i packed.bin -o stage2.bin`
- Verify the output by running `file stage2.bin` on Linux or checking its entropy with
binwalk -E stage2.bin.
4. Extracting the Configuration and Module Table Entries
Stage 2 contains the loader’s configuration—C2 addresses, sleep times, and a module table listing additional payloads to fetch. The module table is often obfuscated with simple XOR or custom encoding.
Step‑by‑step guide:
- Run the decrypted stage2.bin in a sandbox with network monitoring (e.g., FakeNet-NG or Wireshark).
- Observe outbound connections; note any HTTP requests containing base64 or unique URIs.
- Use the config extractor tool:
`python extract_config.py -i stage2.bin -o config.json`
- Examine the JSON output; look for fields like
c2,campaign_id, andmodules. - Manually decode any embedded strings with a simple CyberChef recipe (XOR with key found via static analysis).
5. Extracting and Decrypting the Final Payload
The final payload (e.g., a backdoor, ransomware, or information stealer) is downloaded from the C2 or extracted from the module table. It may be further encrypted or packed. The researchers’ final tool performs this extraction.
Step‑by‑step guide:
- From the configuration, identify the URL or resource containing the final payload.
- Use a tool like `wget` or `curl` to download the encrypted blob:
`curl -o encrypted_payload.bin http://malicious.c2/payload.bin` - Determine the encryption algorithm (often AES or RC4) by analyzing the loader’s decryption routine.
- Use a Python script with `pycryptodome` to decrypt:
from Crypto.Cipher import AES key = bytes.fromhex("...") iv = bytes.fromhex("...") cipher = AES.new(key, AES.MODE_CBC, iv) payload = cipher.decrypt(encrypted_data) - Write the decrypted payload to disk and analyze it with standard tools (PE analysis, strings, etc.).
6. Detection and Mitigation Strategies
Defenders can create YARA rules based on unique strings, hashes, or patterns found during analysis. Network signatures can also block communication.
Step‑by‑step guide:
- Extract unique byte sequences from the loader:
`dd if=malware.exe bs=1 skip=0x1000 count=512 2>/dev/null | xxd -p`
– Write a YARA rule:rule HijackLoader { strings: $s1 = { 8B 45 08 33 C9 8B 55 0C } // example pattern $hash = "a1b2c3d4" // known hash constant condition: any of them } - Test the rule: `yara -w hijackloader.yar suspicious_file.exe`
– For cloud environments, implement egress filtering to block connections to known malicious IPs/domains extracted from the config. - Use Windows Defender Attack Surface Reduction (ASR) rules to block Office applications from creating child processes—a common loader behavior.
What Undercode Say:
- HijackLoader demonstrates the continued evolution of loader malware, combining hash‑based API resolution and multi‑stage encryption to evade static detection. The tools released by researchers are invaluable for automating the tedious parts of analysis, allowing analysts to focus on the payload’s behavior.
- The campaign’s use of a legitimate‑looking gaming site highlights the importance of user education and web filtering. Even seasoned users can be tricked by “free” offers, making layered defenses—endpoint detection, network monitoring, and application control—critical.
Prediction:
As loaders like HijackLoader become more modular, we can expect to see them integrated into larger crimeware‑as‑a‑service ecosystems. The use of legitimate hosting platforms (like PiviGames) may increase, forcing security vendors to rely more heavily on behavioral analysis and threat intelligence sharing. Future variants will likely adopt stronger encryption and anti‑analysis tricks, such as VM detection and environment fingerprinting, to prolong their dwell time.
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Karsten Hahn – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
