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Malware with strong evasion techniques do exist within the Linux platform. There is a high ratio of publicly available open-source malware that utilize strong evasion techniques and can be easily adapted by adversaries.

In part four of our ELF 101 blog series, we explain the dynamic linking process, including its purpose, how it works and the different linking modes.

Intezer Analyze community detections in May include malware from Chinese threat actor groups APT3, ChinaZ and APT10, and an endpoint infected with Nanocore.

The Pacha Group is disabling previously installed cryptominers from other threat groups on the cloud, most notably the Rocke Group, in order to obtain the largest foothold of computing power on the cloud for conducting malicious crypto-mining activities.

Get to know Intezer Analyze community manager Shaul Holtzman. Shaul is a former cybersecurity analyst helping organizations detect and classify advanced cyber threats.

Memory forensics are crucial for detecting fileless malware. The new Intezer endpoint analysis solution analyzes code in memory to detect advanced threats.

Announcing the release of an API for the Intezer Analyze community edition. Members of the free community can now create automation scripts to analyze files without manual intervention. Highlighted in this blog are some of the ways in which community users can utilize the API.

Software is evolutionary. Intezer has introduced a new innovative approach to automate malware analysis and provide clear insights into any suspicious file. The company's Genetic Malware Analysis technology empowers security teams to improve and accelerate all stages of their incident response, from the initial alert to the final step of remediation.

We would like to proudly announce that Intezer Analyze™ now supports genetic malware analysis for ELF binaries! You may now upload ELF files to our system and find code reuse. We have already indexed the genes of millions of different files into our ELF genome database, classified into both malicious, trusted, and...

Our technology is based on genetic analysis of files. So far, we’ve focused mainly on detection of code reuse, as part of the genetic malware analysis process.

The popular banking trojan Emotet is constantly evolving to evade detection. Stripped down to its genetic core, malware analysis reveals Emotet's code remains largely the same from generation to generation.

We’ve recently added to our product, support for Dynamic Execution and Static Extraction and we wanted our user interface to reflect these additions.

As stated in a previous blog entry, it is common for malware authors to sign malicious files with “legitimate” digital certificates in order to bypass security products.

This post is part of Intezers blog series about executable and linkable formats. In this post, we will introduce the concept of ELF relocations and their relationship with symbols. Later we will explain more advanced concepts, such as dynamic linking.

After launching Intezer community edition in November 2017, we noticed that many of our users uploaded packed samples. Yet packed files don’t reveal the true ‘DNA’ of the files.