Free Spam Filtering Tool With ANY.RUN to Analyse Email Threats

In a significant advancement for email security, ANY.RUN, a leader in malware analysis sandboxing, has unveiled a new module integrating RSPAMD into its Static Discovering feature. This RSPAMD integration marks a pivotal step in enhancing the detection and analysis of suspicious emails, providing users with an unparalleled toolset for identifying potential threats.

ANY.RUN is a cloud-based environment for analyzing Windows malware and Linux-based samples. Malware analysts, SOC, DFIR teams can safely examine threats, simulate different scenarios, and gain insights into malware behavior to improve cybersecurity strategies.

ANY.RUN also allows researchers to understand malware behavior, collect IOCs, and easily map malicious actions to TTPs — all in our interactive sandbox.

 The Threat Intelligence Lookup platform helps security researchers find the relevant threat data from a sandbox tasks of ANY.RUN.

What is RSPAMD?

RSPAMD is a sophisticated, open-source email filtering system that combines regular expressions, statistical analysis, and machine learning algorithms to detect spam, phishing attempts, and other malicious email content. By analyzing an email’s content, headers, and the sender’s reputation, RSPAMD assigns a spam score to each message, aiding in the identification of potential threats[

Key Features of RSPAMD in ANY.RUN

The integration of RSPAMD into ANY.RUN’s Static Discovering feature introduces several innovative functionalities:

• Symbols: RSPAMD conducts various tests on each email, generating symbols representing specific checks, such as spam keywords, known malicious URLs, and suspicious email patterns. These symbols provide insights into the email’s classification.
• Bayesian Filtering: This probabilistic method compares the email’s content against a database of known good and bad emails to determine its classification, enhancing the accuracy of spam detection
• HTML Content Preview: ANY.RUN has incorporated an HTML content preview of the email in question, allowing users to quickly assess its content and make informed decisions.

Integration of RSPAMD in Static Discovery

The RSPAMD module is seamlessly integrated into ANY.RUN’s Static Discovering feature. When users open an email file in Static Discovering, the RSPAMD tab provides a detailed breakdown of the email’s information, including its spam score, headers, and RSPAMD symbols.

This interactive display enables a thorough investigation of the email content, a capability that significantly enhances ANY.RUN’s email analysis functionality.

Case Studies and Practical Applications

ANY.RUN offers case studies demonstrating the effectiveness of the RSPAMD module. For example, an email with a score above 20 can preliminarily be deemed undesirable.

Further analysis with RSPAMD can reveal if the email contains text parts encoded in base64, a short HTML part with a link to an image, and if the “From” header display name contains excess whitespace. Such detailed analysis aids users in determining the trustworthiness of an email

The introduction of the RSPAMD module into ANY.RUN’s Static Discovering feature represents a significant leap forward in the field of email analysis. By providing users with detailed, interactive information about suspicious emails, ANY.RUN enhances the ability of analysts and cybersecurity professionals to identify and mitigate potential threats.

This development underscores ANY.RUN’s commitment to leveraging cutting-edge technology to improve cybersecurity practices, reaffirming its position as an indispensable resource in the cybersecurity domain.

ANY.RUN continues to evolve, offering tools like RSPAMD to streamline the malware analysis process and improve detection rates. With each update and new feature, ANY.RUN reaffirms its role as a crucial tool for cybersecurity professionals worldwide.

If you’re from the SOC and DFIR teams to investigate incidents and streamline threat analysis. Try all features of ANY.RUN at zero cost for 14 days with a free trial.