Analyzing Embedded ZIP Payloads in RTF Documents for Malware Analysis

The Persistence of RTF-Based Payload Delivery

Rich Text Format (RTF) remains a resilient vector for initial access within the MITRE ATT&CK framework. While many modern email security gateways aggressively block executable files and script attachments, RTF documents often bypass these filters due to their perceived legacy nature and complexity in parsing. A common TTP observed in Phishing campaigns involves embedding a compressed archive, such as a ZIP file, directly within the RTF structure. This method leverages the document as a delivery vehicle rather than a direct exploit, forcing the user to interact with an embedded object that then executes the final payload.

According to the SANS Internet Storm Center, the technical challenge of analyzing these files stems from how RTF handles binary data. Unlike MIME-encoded emails or modern XML-based Office formats, RTF is essentially a text file that encapsulates binary information through hex-encoding. This encoding obfuscates the underlying file structure from basic signature-based detection, requiring specialized tools for extraction and analysis.

Technical Analysis of Hex-Encoded Binary Data

In a standard RTF file, binary data such as images or OLE objects are contained within curly braces and identified by specific control words. The most significant control word for analysts is \objdata. When an attacker embeds a ZIP archive, the binary content of that archive is converted into a continuous string of hexadecimal characters.

To perform effective RTF malware analysis using rtfdump, an analyst must look for the characteristic magic bytes of the embedded format. For ZIP archives, this is the “PK” header, represented in hexadecimal as 50 4B. Because the RTF format stores this as text, searching for the literal string “504b” within an object’s data stream is the primary method of identification. This technique is essential when extracting malicious payloads from RTF files that might otherwise appear benign to standard antivirus engines.

Identifying Malicious Payloads: How to Detect ZIP Files in RTF Documents

Identification begins with identifying the correct data stream. RTF documents are organized into groups and objects. Using a tool like rtfdump.py, developed by Didier Stevens, analysts can partition the document into its constituent parts. Each part is assigned an index, allowing the analyst to inspect the hexadecimal content without manual carving.

The presence of an OLE object (indicated by the \oleobj control word) followed by a large block of hex data starting with 504B is a high-confidence indicator of an embedded ZIP archive. Once identified, the hex stream must be converted back into binary. This process involves stripping any RTF control characters or whitespace that may be interspersed within the hex string to ensure the resulting ZIP file is not corrupted and can be opened for further forensic inspection.

Forensic Deconstruction and Tooling

Automation is key for a modern SOC or incident response team. Manual extraction of hex strings from multi-megabyte RTF files is prone to error and inefficient. Tools like rtfdump.py provide a command-line interface to filter objects by size or content. For example, an analyst can use a command to select a specific object index and apply a transformation (like hex-decoding) to output the raw binary data directly to a file.

This deconstructed archive can then be analyzed for secondary indicators of compromise, such as obfuscated JavaScript, malicious LNK files, or executables designed to establish C2 communications. By isolating the ZIP file, analysts can pivot from document analysis to traditional file-based malware forensics.

Defensive Strategies and Detection Optimization

Defenders should prioritize the inspection of RTF files at the perimeter. While blocking all RTF files may be impractical for some organizations, implementing a SIEM rule to alert on RTF documents containing OLE objects with “PK” headers is a proactive step. Furthermore, security teams should ensure that their sandboxing solutions are configured to decompress and scan embedded objects within RTF containers.

Beyond technical controls, user education remains a vital component of defense. Since many RTF-embedded ZIP files require the user to double-click an icon within the document to trigger the payload, training users to recognize suspicious embedded objects can break the attack chain before execution occurs. By combining automated extraction techniques with robust perimeter monitoring, organizations can significantly reduce the risk posed by these deceptive document formats.