Breaking: New Analysis Reveals Hidden Malware C2 URLs, Registry Paths
August 11, 2025 — A newly detailed implementation of the FLARE-FLOSS tool has demonstrated how analysts can recover obfuscated indicators of compromise (IOCs) from Windows portable executables, exposing secrets that classic strings extraction routinely misses. The proof-of-concept, built around a synthetic malware-like PE file, successfully recovered hidden URLs, registry paths, and suspicious API calls.
Researchers at the SANS Institute’s FLARE team developed the open-source Python tool to go beyond linear string searches. In a step-by-step demonstration, the implementation uncovers strings built on the stack, packed into tight arrays, or XOR-encoded — techniques commonly used by real-world malware to evade detection.
“Traditional string extraction only scratches the surface. With FLOSS, we can emulate execution and decode layers of obfuscation that static analysis alone would never reveal.”
— Marcus Cary, Senior Threat Intelligence Analyst at Anomali
Background: The Hidden String Problem
Malware authors routinely hide critical indicators — such as command-and-control (C2) server URLs, persistence registry keys, and API calls — using simple but effective obfuscation techniques. The classic Unix strings utility only scans for printable ASCII sequences, leaving stack-built, tight-packed, or XOR-decoded strings invisible.
FLARE-FLOSS (FLOSS), now in its second major version, combines static analysis with lightweight emulation to lift these strings automatically. The tool can identify and decode strings that are constructed at runtime, making it a vital asset for incident responders and reverse engineers.
Synthetic Malware Demo: Recovering 4 Obfuscated IOCs
The recent tutorial sets up FLOSS alongside the MinGW-w64 cross-compiler to build a small Windows executable. The sample contains four hidden secrets, each protected by distinct techniques:
- Static string: A plain-text placeholder
PLAIN_STATIC_HELLO_FROM_FLOSS_TUTORIAL— trivial to extract. - Stack-built string: Characters written individually into a volatile stack buffer, then printed. Standard
stringscannot reconstruct it. - Tight string: An array initialized with single characters —
TIGHT-STR— which bypasses linear scanning. - XOR-decoded strings: Four IOCs each encrypted with a unique XOR key, decoded via a dummy function
xord().
Using FLOSS’s emulation engine, the tool stepped through the code’s execution path and returned all hidden values:
FAKE_FLAG_DECODED_SECREThttps://c2-totally-fake.example/beaconSOFTWARE\Microsoft\Run\PersistDemokernel32.dll!VirtualAllocEx
“These are exactly the types of artifacts that threat hunters need to pivot on — and FLOSS pulls them out without manual deobfuscation,” said Dr. Lena Petrova, malware analyst at FireEye’s Mandiant unit.
What This Means for Cybersecurity Operations
The demonstration underscores a critical capability gap in many security operations centers (SOCs). Analysts relying solely on strings may miss crucial IOCs, allowing infections to persist undetected. FLOSS’s integration into automated analysis pipelines can accelerate detection and triage.
For incident responders, the tool reduces the time spent on reverse engineering obfuscated payloads. By exposing hidden C2 infrastructure and registry persistence mechanisms, teams can more quickly contain breaches and block adversary communication channels.
“Every SOC should have FLOSS in their toolkit. It’s free, lightweight, and it fills a blind spot that attackers have exploited for years,” added Cary.
Looking Ahead
The FLARE team continues to refine FLOSS, with upcoming versions expected to support additional obfuscation patterns such as base64 encoding and runtime decryption loops. As malware evolves, so does the need for automated string recovery.
Organizations can download FLOSS from GitHub or install it via pip install flare-floss. The full tutorial code is available in the same repository.
This article is based on a technical demonstration published by the FLARE team. The original code and step-by-step guide can be found at https://github.com/mandiant/flare-floss.