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2 posts from January 2017

Jan 30, 2017

Anti-analysis technique for PE Analysis Tools –INT Spoofing–

When analysing Windows executable file type (PE file) malware, a tool to parse and display the PE file’s structure (hereafter “PE analysis tool”) is often used. This tool enables referring to a list of APIs that the malware imports (Import API) and functions that it exports. By analysing the data, it is possible to presume the malware’s function as in communicating with external servers or creating registry entries, etc. In this way, PE analysis tools are often used for malware analysis, however, a type of malware which has techniques to disturb operations of PE analysis tools has already been observed [1].

This entry introduces techniques to deceive analysts by displaying incorrect information in the Import API, and measures to implement in PE analysis tools against the issue.

INT (Import Name Table) and IAT (Import Address Table)

PE files contain 2 address tables related to Import API – INT and IAT. INT describes the address of the area which stores API names imported by the PE file. IAT is used when actually calling an API, and writes an entry address of the functions corresponding to the API when the module which exports the function is loaded. For more information about PE file formats, please refer to Microsoft’s website [2].

NT header in a PE file describes various kinds of information required for executing the file. NT header is structured as “IMAGE_NT_HEADERS”, and INT and IAT can be identified by tracing the address in “IMAGE_DATA_DIRECTORY” of Optional Header within the structure (Figure 1) [3].

Figure 1: INT and IAT related section within NT header in a PE file

The Name field of “IMAGE_IMPORT_BY_NAME” structure, which is referred to by INT, describes importing API names as a string. Generally, IMAGE_IMPORT_BY_NAME lists API names in a sequence as in Figure 2.

Figure 2: Example of IMAGE_IMPORT_BY_NAME

INT Spoofing

IMAGE_IMPORT_BY_NAME contains strings specifying API names. Even if someone tries to alter the API name in IMAGE_IMPORT_BY_NAME to disguise it as another PE file, it would not be executed properly since it would import unintended API when executing the PE file. As the red part in Figure 3 indicates, however, if the PE file is modified by adding new API names at the end of the INT to existing API names within the INT, it will not attempt to load a module since the IAT does not have a field that stores the entry address of the functions corresponding to the added API name. If PE analysis tools display such deliberately added API names, analysts would believe that the PE file has new APIs that is imported, which would confuse the analysis.

Figure 3: Example of INT spoofing

Check for INT-spoofed PE files using PE analysis tools

Many of the existing PE analysis tools refer to only INT when listing Import API, and recognise and display strings in IMAGE_IMPORT_BY_NAME as API names. When handling normal PE files, there is no issues with the behaviour since importing API addresses corresponding to the strings in IMAGE_IMPORT_BY_NAME, are written in the IAT.

However, if INT is spoofed by the above mentioned method, extra APIs are also listed. As an experiment, JPCERT/CC generated some INT-spoofed PE files, and tested how their Import API would be displayed in several PE analysis tools. As a result, many of them displayed extra APIs that are not actually imported.

Figure 4: Analysis examples of INT-spoofed executable files on PE analysis tools (Indicates the number of Import API increased due to INT spoofing)

Countermeasures against INT spoofing

One countermeasure against such spoofing would be to compare INT and IAT on a PE analysis tool and only display APIs that are actually imported (and not display added API names marked in red in the Figure 3). pyimpfuzzy, which was introduced in a past blog entry, is also a tool which performs analysis based on Import API. In its first version, there was an issue where INT-spoofed samples could not be analysed correctly. As such, the tool was updated with a new feature to compare INT and IAT, and only analyse the APIs that are actually imported.

Many PE analysis tools display strings in IMAGE_IMPORT_BY_NAME as they are. However, many debuggers and IDA refer to IATs when displaying Import API, and thus most of them do not seem to be affected by INT spoofing. When referring to the information on Import API in malware analysis, it is recommended to check APIs that are actually loaded in IAT by using a debugger, as well as INT strings.


JPCERT/CC has not yet observed any INT-spoofed samples, however, this disguising technique could possibly be abused in the near future. Automated analysis tools based on Import API may be affected by INT spoofing. As introduced above, pyimpfuzzy has been updated to a new version – please make sure that you are using the latest version (version 0.02).

Thanks for reading.

- Shusei Tomonaga
(Translated by Yukako Uchida)


[1] Palo Alto Networks - The Dukes R&D Finds a New Anti-Analysis Technique

[2] Microsoft - PE Format

[3] Microsoft - IMAGE_NT_HEADERS structure

Jan 25, 2017

2016 in Review: Top Cyber Security Trends in Japan

Hi, this is Misaki Kimura from Watch and Warning Group.

Another new year has come and gone, and as I look back over about the significant security trends that took place in 2016, it is needless to mention that security threat landscape is ever evolving and increasingly complex. As a basis for what we can prepare for 2017, I’d like to review security headlines in 2016 by referring to the activities carried out in Japan, to look into the expectations to come.

Increase in DDoS built by botnets such as Mirai

Large-scale botnets leveraging Internet of Things (IoT) devices to launch massive DDoS attacks, became a prominent topic worldwide. The Mirai botnet, which was responsible for the series of attacks in recent months, including the DDoS attacks against American journalist’s website “Krebs on Security”, and DNS provider “Dyn”, had brought a huge impact. The word “Mirai” is a Japanese word for “future”, and just as it is interpreted, since the release of Mirai source code last September, it has called a lot of concerns of what poorly secured IoT devices may bring in the future.

In response to this, a technical alert (in Japanese) was released on Japan Vulnerability Notes (JVN) to promote IoT device owners/users in Japan to secure their devices, and organizations were encouraged to place countermeasures towards DDoS attacks. In addition, JPCERT/CC has announced a security alert for awareness raising, and the Information-technology Promotion Agency, Japan (IPA) has also announced an alert (in Japanese) respectively.

Security guidelines concerning IoT were also published from multiple organizations during last year. “IoT Security Guide for Consumers (ver1.0)” (in Japanese) that is intended for readers such as IoT device developers and consumers to take precautions towards IoT devices was published from the Japan Network Security Association (JNSA). Furthermore, “IoT Security Guideline ver1.0” (in Japanese) was announced from the IoT Acceleration Consortium’s IoT Security Working Group, organized by the Ministry of Economy, Trade and Industry (METI) and the Ministry of Internal Affairs and Communications (MIC).

Advanced Persistent Threat (APT) becomes increasingly sophisticated

Since the Japan Pension Service hack in 2015 that led to 1.25 million cases of personal data leak, the Japanese public has been paying attention to targeted attacks than ever before. These types of attacks continued to evolve constantly by developing new tactics, techniques and procedures. Particularly in 2016, we have been observing attacks concerning to malware known as Daserf [1], Asurex [2], Sysget (aka HelloBridge, ZACOM) [3] and Elirks (aka KLURP) [4]. Though the attribution for each malware may differ, a common attack vector is observed - malware infections are attempted by convincing the user to open attachments of spear phishing emails or watering hole attacks.

Amongst all, what specifically grabbed our attention was Daserf. Not only different C2 servers were used for each targeted organization, but the C2 server for each infected device within the organization was also individual. Due to this multiplicity, blacklisting the URLs and IP addresses of C2 servers were no more an effective measure, allowing the threat actors to remain undetected for a long duration of time.

On the other hand, Elirks was also unique in terms of retrieving its C2 server’s IP address – it obtains the IP address by accessing to pre-determined microblog service or SNS. This behavior is deemed to avoid the detection of security products and to flexibly switch the C2 server specified in the content of articles posted on those legitimate services by rewriting the code in it.

In accordance to this situation, at JPCERT/CC, we released a document on “Initial Procedures and Response Guideline for Countering Advanced Persistent Threat” (in Japanese) and also “Report on the Research into Evidence of Attack Tool Execution for Incident Investigation” (released in Japanese, English version will be coming out by the end of first half of 2017 (Title is tentative)). The former aims to enhance effective incident response procedures to deal with APT by providing knowledge on how to detect, analyze and contain the attacks, while the latter aims to promote efficient investigation upon an incident by providing information on actual attack tools used by threat actors and evidence left in log files when executing those tools.

Attack cases on financial theft continues to take place

According to the report (in Japanese) released by the National Police Agency (NPA), financial loss caused by illegal money transfer using Internet banking services that occurred in the first half of 2016 has been greatly reduced both in number of victims and the amount of financial loss of credit unions and corporate accounts. To be more specific, the damage amount in the first half of 2016 was 898 million Japanese yen, which decreased from the second half of 2015 (1.53 billion Japanese yen). However, in terms of personal accounts, the number of victims and amount of financial loss were witnessed at the same level as 2015 on average.

In 2016, Online Banking Trojans that steal IDs and passwords were attached to Japanese written spam emails and sent to Japanese users. Notorious Banking Trojans that were causing damages overseas such as Ursnif (aka: Gozi, Snifula) [5], Shiotob (aka: URLZONE, Bebloh) [6] and KRBANKER [7] (in Japanese), were also beginning to target online users in Japan.

In addition, ransomware continued to keep prevalent this year as well. Based on the report (in Japanese) from TrendMicro, Japanese organizations infected with ransomware in the first half of the year reached to 1,740, which was 7 times higher compared with the same time of 2015. Regarding the amount of financial loss itself, it has become the most significant security threat amongst all to Internet users.

Lastly, one more to note - 2016 was the year for JPCERT/CC to celebrate its 20th anniversary. As long as JPCERT/CC represents as the coordination center for cyber security incidents in Japan, we will continue to endeavor to create cyber space a safer place for all through cooperation and coordination with various partners around the globe. We would like to convey our gratitude for your support and cooperation, and would like to continuously devote the utmost effort in our activities.

Thank you for reading.

- Misaki Kimura


[1] http://www.lac.co.jp/security/report/pdf/cgview_vol2_en.pdf

[2] http://blog.jpcert.or.jp/2016/06/asruex-malware-infecting-through-shortcut-files.html

[3] https://www.fireeye.com/content/dam/fireeye-www/global/en/current-threats/pdfs/wp-operation-quantum-entanglement.pdf

[4] http://researchcenter.paloaltonetworks.com/2016/06/unit42-tracking-elirks-variants-in-japan-similarities-to-previous-attacks/

[5] http://blog.trendmicro.com/trendlabs-security-intelligence/ursnif-the-multifaceted-malware/

[6] http://blog.trendmicro.com/trendlabs-security-intelligence/bebloh-expands-japan-latest-spam-attack/

[7] http://blog.trendmicro.co.jp/archives/13683