Harnessing the Deep and Dark Web for Cyber Threat Intelligence

As cyber threats evolve, so must our strategies to combat them. The deepdarkCTI project serves as a crucial resource, offering access to a curated collection of intelligence from the Deep and Dark Web. This repository is a goldmine for those in cyber security, providing tools and data that are pivotal for both defensive measures and offensive strategies.

From detailed exploits and vulnerability patches found in obscure forums, to the tracking of ransomware groups' tactics and communication in encrypted channels—every piece of data can be leveraged. Moreover, our community-driven approach allows enthusiasts and professionals to contribute and stay ahead with the latest tactics and techniques discussed in our dedicated Telegram group.

For individuals looking to delve deeper or contribute, detailed methodologies for source analysis are available, ensuring that every user can effectively apply this intelligence. Whether you’re defending an organization or testing its defenses, the insights gained from these sources are invaluable.

Join and contribute to the deepdarkCTI project today to stay at the forefront of cybersecurity intelligence.

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LeakSearch - Search & Parse Password Leaks

LeakSearch is a simple tool to search and parse plain text passwords using ProxyNova COMB (Combination Of Many Breaches) over the Internet. You can define a custom proxy and you can also use your own password file, to search using different keywords: such as user, domain or password.

In addition, you can define how many results you want to display on the terminal and export them as JSON or TXT files. Due to the simplicity of the code, it is very easy to add new sources, so more providers will be added in the future.

Requirements

• Python 3
• Install requirements

Download

It is recommended to clone the complete repository or download the zip file. You can do this by running the following command:

git clone https://github.com/JoelGMSec/LeakSearch

Usage

  _               _     ____                      _     
 | |    ___  __ _| | __/ ___|  ___  __ _ _ __ ___| |__  
 | |   / _ \/ _` | |/ /\___ \ / _ \/ _` | '__/ __| '_ \ 
 | |__|  __/ (_| |   <  ___) |  __/ (_| | | | (__| | | |
 |_____\___|\__,_|_|\_\|____/ \___|\__,_|_|  \___|_| |_|

  ------------------- by @JoelGMSec -------------------

usage: LeakSearch.py [-h] [-d DATABASE] [-k KEYWORD] [-n NUMBER] [-o OUTPUT] [-p PROXY]

options:
  -h, --help            show this help message and exit
  -d DATABASE, --database DATABASE
                        Database used for the search (ProxyNova or LocalDataBase)
  -k KEYWORD, --keyword KEYWORD
                        Keyword (user/domain/pass) to search for leaks in the DB
  -n NUMBER, --number NUMBER
                        Number of results to show (default is 20)
  -o OUTPUT, --output OUTPUT
                        Save the results as json or txt into a file
  -p PROXY, --proxy PROXY
                        Set HTTP/S proxy (like http://localhost:8080)

The detailed guide of use can be found at the following link:

https://darkbyte.net/buscando-y-filtrando-contrasenas-con-leaksearch

License

This project is licensed under the GNU 3.0 license - see the LICENSE file for more details.

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RepoReaper - An Automated Tool Crafted To Meticulously Scan And Identify Exposed .Git Repositories Within Specified Domains And Their Subdomains

RepoReaper is a precision tool designed to automate the identification of exposed .git repositories across a list of domains and subdomains. By processing a user-provided text file with domain names, RepoReaper systematically checks each for publicly accessible .git files. This enables rapid assessment and protection against information leaks, making RepoReaper an essential resource for security teams and web developers.

Features

• Automated scanning of domains and subdomains for exposed .git repositories.
• Streamlines the detection of sensitive data exposures.
• User-friendly command-line interface.
• Ideal for security audits and Bug Bounty.

Installation

Clone the repository and install the required dependencies:

git clone https://github.com/YourUsername/RepoReaper.git
cd RepoReaper
pip install -r requirements.txt
chmod +x RepoReaper.py

Usage

RepoReaper is executed from the command line and will prompt for the path to a file containing a list of domains or subdomains to be scanned.

To start RepoReaper, simply run:

./RepoReaper.py
  or
python3 RepoReaper.py

Upon execution, RepoReaper will ask for the path to the file containing the domains or subdomains: Enter the path of the file containing domains

Provide the path to your text file when prompted. The file should contain one domain or subdomain per line, like so:

example.com
subdomain.example.com
anotherdomain.com

RepoReaper will then proceed to scan the provided domains or subdomains for exposed .git repositories and report its findings. 

Disclaimer

This tool is intended for educational purposes and security research only. The user assumes all responsibility for any damages or misuse resulting from its use.

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Navigating Telegram’s Underworld: A Cipher for the Elite Hackers

In the encrypted depths of Telegram, far beyond the scrutiny of average netizens, lies a network pulsating with the lifeblood of the hacking elite. This isn’t your run-of-the-mill tutorial or a hacker’s 101 guide. This post is a deep dive into the abyss, mapping the veins of active and dormant channels that are the backbone of cyber threat intelligence and underground hacking operations.

The channels we’re dissecting today are not just communication lines; they are the hidden layers of the onion, each peel revealing more about the dark arts of digital dominance. From active dens where real-time data breaches, exploit trades, and botnet controls unfold, to the ghostly silence of channels once alive with the chatter of codes and hacks now lying dormant or expired - every link, every channel, serves as a node in the vast neural network of the global hacking community.

Active Channels: The Frontlines

Here, in the buzzing hive of active channels, you're as likely to find a zero-day exploit as you are a discussion on the latest evasion techniques. This isn't just about sharing tools or data; it's a relentless innovation race. Techniques, scripts, and methodologies discussed here are not for the faint-hearted but for those who command the terminal like it’s an extension of their mind.

Dormant/Expired Channels: The Archives

The silent corridors of expired channels are not just digital tombs; they are treasure troves of past operations, a testament to the ephemeral nature of digital power. Each one holds lessons, failures, and victories. They are the archives for those willing to learn from history to master the future.

Access The Repository

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EmploLeaks - An OSINT Tool That Helps Detect Members Of A Company With Leaked Credentials

 

This is a tool designed for Open Source Intelligence (OSINT) purposes, which helps to gather information about employees of a company.

How it Works

The tool starts by searching through LinkedIn to obtain a list of employees of the company. Then, it looks for their social network profiles to find their personal email addresses. Finally, it uses those email addresses to search through a custom COMB database to retrieve leaked passwords. You an easily add yours and connect to through the tool.

Installation

To use this tool, you'll need to have Python 3.10 installed on your machine. Clone this repository to your local machine and install the required dependencies using pip in the cli folder:

cd cli
pip install -r requirements.txt

OSX

We know that there is a problem when installing the tool due to the psycopg2 binary. If you run into this problem, you can solve it running:

cd cli
python3 -m pip install psycopg2-binary`

Basic Usage

To use the tool, simply run the following command:

python3 cli/emploleaks.py

If everything went well during the installation, you will be able to start using EmploLeaks:

___________              .__         .__                 __
\_   _____/ _____ ______ |  |   ____ |  |   ____ _____  |  | __  ______
 |    __)_ /     \____  \|  |  /  _ \|  | _/ __ \__   \ |  |/ / /  ___/
 |        \  Y Y  \  |_> >  |_(  <_> )  |_\  ___/ / __ \|    <  \___ \
/_______  /__|_|  /   __/|____/\____/|____/\___  >____  /__|_ \/____  >
        \/      \/|__|                         \/     \/     \/     \/

OSINT tool 🕵  to chain multiple apis
emploleaks>

Right now, the tool supports two functionalities:

• Linkedin, for searching all employees from a company and get their personal emails.
  • A GitLab extension, which is capable of finding personal code repositories from the employees.
• If defined and connected, when the tool is gathering employees profiles, a search to a COMB database will be made in order to retrieve leaked passwords.

Retrieving Linkedin Profiles

First, you must set the plugin to use, which in this case is linkedin. After, you should set your authentication tokens and the run the impersonate process:

emploleaks> use --plugin linkedin
emploleaks(linkedin)> setopt JSESSIONID
JSESSIONID: 
[+] Updating value successfull
emploleaks(linkedin)> setopt li-at
li-at: 
[+] Updating value successfull
emploleaks(linkedin)> show options
Module options:

Name        Current Setting                      Required    Description
----------  -----------------------------------  ----------  -----------------------------------
hide        yes                                  no          hide the JSESSIONID field
JSESSIONID  **************************           no          active cookie session in browser #1
li-at       AQEDAQ74B0YEUS-_AAABilIFFBsAAAGKdhG  no          active cookie session in browser #1
            YG00AxGP34jz1bRrgAcxkXm9RPNeYIAXz3M
            cycrQm5FB6lJ-Tezn8GGAsnl_GRpEANRdPI
            lWTRJJGF9vbv5yZHKOeze_WCHoOpe4ylvET
            kyCyfN58SNNH
emploleaks(linkedin)> run i   mpersonate
[+] Using cookies from the browser
Setting for first time JSESSIONID
Setting for first time li_at

li_at and JSESSIONID are the authentication cookies of your LinkedIn session on the browser. You can use the Web Developer Tools to get it, just sign-in normally at LinkedIn and press right click and Inspect, those cookies will be in the Storage tab.

Now that the module is configured, you can run it and start gathering information from the company:

Get Linkedin accounts + Leaked Passwords

We created a custom workflow, where with the information retrieved by Linkedin, we try to match employees' personal emails to potential leaked passwords. In this case, you can connect to a database (in our case we have a custom indexed COMB database) using the connect command, as it is shown below:

emploleaks(linkedin)> connect --user myuser --passwd mypass123 --dbname mydbname --host 1.2.3.4
[+] Connecting to the Leak Database...
[*] version: PostgreSQL 12.15

Once it's connected, you can run the workflow. With all the users gathered, the tool will try to search in the database if a leaked credential is affecting someone:

As a conclusion, the tool will generate a console output with the following information:

• A list of employees of the company (obtained from LinkedIn)
• The social network profiles associated with each employee (obtained from email address)
• A list of leaked passwords associated with each email address.

How to build the indexed COMB database

An imortant aspect of this project is the use of the indexed COMB database, to build your version you need to download the torrent first. Be careful, because the files and the indexed version downloaded requires, at least, 400 GB of disk space available.

Once the torrent has been completelly downloaded you will get a file folder as following:

├── count_total.sh
├── data
│   ├── 0
│   ├── 1
│   │   ├── 0
│   │   ├── 1
│   │   ├── 2
│   │   ├── 3
│   │   ├── 4
│   │   ├─â&€ 5
│   │   ├── 6
│   │   ├── 7
│   │   ├── 8
│   │   ├── 9
│   │   ├── a
│   │   ├── b
│   │   ├── c
│   │   ├── d
│   │   ├── e
│   │   ├── f
│   │   ├── g
│   │   ├── h
│   │   ├── i
│   │   ├── j
│   │   ├── k
│   │   ├── l
│   │   ├── m
│   │   ├⠀─ n
│   │   ├── o
│   │   ├── p
│   │   ├── q
│   │   ├── r
│   │   ├── s
│   │   ├── symbols
│   │   ├── t

At this point, you could import all those files with the command create_db:

The importer takes a lot of time for that reason we recommend to run it with patience.

Next Steps

We are integrating other public sites and applications that may offer about a leaked credential. We may not be able to see the plaintext password, but it will give an insight if the user has any compromised credential:

• Integration with Have I Been Pwned?
• Integration with Firefox Monitor
• Integration with Leak Check
• Integration with BreachAlarm

Also, we will be focusing on gathering even more information from public sources of every employee. Do you have any idea in mind? Don't hesitate to reach us:

• Javi Aguinaga: jaguinaga@faradaysec.com
• Gabi Franco: gabrielf@faradaysec.com

Or you con DM at @pastacls or @gaaabifranco on Twitter.

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Msticpy - Microsoft Threat Intelligence Security Tools

Microsoft Threat Intelligence Python Security Tools.

msticpy is a library for InfoSec investigation and hunting in Jupyter Notebooks. It includes functionality to:

• query log data from multiple sources
• enrich the data with Threat Intelligence, geolocations and Azure resource data
• extract Indicators of Activity (IoA) from logs and unpack encoded data
• perform sophisticated analysis such as anomalous session detection and time series decomposition
• visualize data using interactive timelines, process trees and multi-dimensional Morph Charts

It also includes some time-saving notebook tools such as widgets to set query time boundaries, select and display items from lists, and configure the notebook environment.

The msticpy package was initially developed to support Jupyter Notebooks authoring for Azure Sentinel. While Azure Sentinel is still a big focus of our work, we are extending the data query/acquisition components to pull log data from other sources (currently Splunk, Microsoft Defender for Endpoint and Microsoft Graph are supported but we are actively working on support for data from other SIEM platforms). Most of the components can also be used with data from any source. Pandas DataFrames are used as the ubiquitous input and output format of almost all components. There is also a data provider to make it easy to and process data from local CSV files and pickled DataFrames.

The package addresses three central needs for security investigators and hunters:

• Acquiring and enriching data
• Analyzing data
• Visualizing data

We welcome feedback, bug reports, suggestions for new features and contributions.

Installing

For core install:

pip install msticpy

If you are using MSTICPy with Azure Sentinel you should install with the "azsentinel" extra package:

pip install msticpy[azsentinel]

or for the latest dev build

pip install git+https://github.com/microsoft/msticpy

Documentation

Full documentation is at ReadTheDocs

Sample notebooks for many of the modules are in the docs/notebooks folder and accompanying notebooks.

You can also browse through the sample notebooks referenced at the end of this document to see some of the functionality used in context. You can play with some of the package functions in this interactive demo on mybinder.org.

Log Data Acquisition

QueryProvider is an extensible query library targeting Azure Sentinel/Log Analytics, Splunk, OData and other log data sources. It also has special support for Mordor data sets and using local data.

Built-in parameterized queries allow complex queries to be run from a single function call. Add your own queries using a simple YAML schema.

Data Queries Notebook

Data Enrichment

Threat Intelligence providers

The TILookup class can lookup IoCs across multiple TI providers. built-in providers include AlienVault OTX, IBM XForce, VirusTotal and Azure Sentinel.

The input can be a single IoC observable or a pandas DataFrame containing multiple observables. Depending on the provider, you may require an account and an API key. Some providers also enforce throttling (especially for free tiers), which might affect performing bulk lookups.

TIProviders and TILookup Usage Notebook

GeoLocation Data

The GeoIP lookup classes allow you to match the geo-locations of IP addresses using either:

• GeoLiteLookup - Maxmind Geolite (see https://www.maxmind.com)
• IPStackLookup - IPStack (see https://ipstack.com)

GeoIP Lookup and GeoIP Notebook

Azure Resource Data, Storage and Azure Sentinel API

The AzureData module contains functionality for enriching data regarding Azure host details with additional host details exposed via the Azure API. The AzureSentinel module allows you to query incidents, retrieve detector and hunting queries. AzureBlogStorage lets you read and write data from blob storage.

Azure Resource APIs, Azure Sentinel APIs, Azure Storage

Security Analysis

This subpackage contains several modules helpful for working on security investigations and hunting:

Anomalous Sequence Detection

Detect unusual sequences of events in your Office, Active Directory or other log data. You can extract sessions (e.g. activity initiated by the same account) and identify and visualize unusual sequences of activity. For example, detecting an attacker setting a mail forwarding rule on someone's mailbox.

Anomalous Sessions and Anomalous Sequence Notebook

Time Series Analysis

Time series analysis allows you to identify unusual patterns in your log data taking into account normal seasonal variations (e.g. the regular ebb and flow of events over hours of the day, days of the week, etc.). Using both analysis and visualization highlights unusual traffic flows or event activity for any data set.

Time Series

Visualization

Event Timelines

Display any log events on an interactive timeline. Using the Bokeh Visualization Library the timeline control enables you to visualize one or more event streams, interactively zoom into specific time slots and view event details for plotted events.

Timeline and Timeline Notebook

Process Trees

The process tree functionality has two main components:

• Process Tree creation - taking a process creation log from a host and building the parent-child relationships between processes in the data set.
• Process Tree visualization - this takes the processed output displays an interactive process tree using Bokeh plots.

There are a set of utility functions to extract individual and partial trees from the processed data set.

Process Tree and Process Tree Notebook

Data Manipulation and Utility functions

Pivot Functions

Lets you use MSTICPy functionality in an "entity-centric" way. All functions, queries and lookups that relate to a particular entity type (e.g. Host, IpAddress, Url) are collected together as methods of that entity class. So, if you want to do things with an IP address, just load the IpAddress entity and browse its methods.

Pivot Functions and Pivot Functions Notebook

base64unpack

Base64 and archive (gz, zip, tar) extractor. It will try to identify any base64 encoded strings and try decode them. If the result looks like one of the supported archive types it will unpack the contents. The results of each decode/unpack are rechecked for further base64 content and up to a specified depth.

Base64 Decoding and Base64Unpack Notebook

iocextract

Uses regular expressions to look for Indicator of Compromise (IoC) patterns - IP Addresses, URLs, DNS domains, Hashes, file paths. Input can be a single string or a pandas dataframe.

IoC Extraction and IoCExtract Notebook

eventcluster (experimental)

This module is intended to be used to summarize large numbers of events into clusters of different patterns. High volume repeating events can often make it difficult to see unique and interesting items.

This is an unsupervised learning module implemented using SciKit Learn DBScan.

Event Clustering and Event Clustering Notebook

auditdextract

Module to load and decode Linux audit logs. It collapses messages sharing the same message ID into single events, decodes hex-encoded data fields and performs some event-specific formatting and normalization (e.g. for process start events it will re-assemble the process command line arguments into a single string).

syslog_utils

Module to support an investigation of a Linux host with only syslog logging enabled. This includes functions for collating host data, clustering logon events and detecting user sessions containing suspicious activity.

cmd_line

A module to support he detection of known malicious command line activity or suspicious patterns of command line activity.

domain_utils

A module to support investigation of domain names and URLs with functions to validate a domain name and screenshot a URL.

Notebook widgets

These are built from the Jupyter ipywidgets collection and group common functionality useful in InfoSec tasks such as list pickers, query time boundary settings and event display into an easy-to-use format.

 

More Notebooks on Azure Sentinel Notebooks GitHub

Azure Sentinel Notebooks

Example notebooks:

• Account Explorer
• Domain and URL Explorer
• IP Explorer
• Linux Host Explorer
• Windows Host Explorer

View directly on GitHub or copy and paste the link into nbviewer.org

Notebook examples with saved data

See the following notebooks for more examples of the use of this package in practice:

• Windows Alert Investigation in GitHub or NbViewer
• Office 365 Exploration in GitHub or NbViewer
• Cross-Network Hunting in GitHubor NbViewer

Supported Platforms and Packages

• msticpy is OS-independent
• Requires Python 3.6 or later
• See requirements.txt for more details and version requirements.

Contributing

For (brief) developer guidelines, see this wiki article Contributor Guidelines

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

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How SSPM Simplifies Your SOC2 SaaS Security Posture Audit

 

An accountant and a security expert walk into a bar… SOC2 is no joke.

Whether you're a publicly held or private company, you are probably considering going through a Service Organization Controls (SOC) audit. For publicly held companies, these reports are required by the Securities and Exchange Commission (SEC) and executed by a Certified Public Accountant (CPA). However, customers often ask for SOC2 reports as part of their vendor due diligence process.

Out of the three types of SOC reports, SOC2 is the standard to successfully pass regulatory requirements and signals high security and resilience within the organization — and is based on the American Institute of Certified Public Accountants (AICPA) attestation requirements. The purpose of this report is to evaluate an organization's information systems relevant to security, availability, processing integrity, confidentiality, and privacy — over a period of time (roughly six to twelve months).

As part of a SOC2 audit, it is necessary to conduct security checks across the company's SaaS stack that will look for misconfigured settings such as detection and monitoring to ensure continued effectiveness of information security controls and prevent unauthorized/ inappropriate access to physical and digital assets and locations.

If you're beginning or on a SOC2 audit journey, then an SSPM (SaaS Security Posture Management) solution can streamline the process and shorten the time it takes to pass a SOC2 audit successfully, fully covering your SaaS Security posture.

Learn how to streamline your organization's SOC2 compliance

What are the AICPA Trust Services Criteria (TSC)?

When external auditors engage in a SOC 2 audit, they need to compare what you're doing to a long list of established requirements from AICPA TSC. The "Common Controls" fall into five groups:

• Security - Includes sub controls of the Logical and Physical Access (CC6)
• Availability - Includes sub controls of the System Operations (CC7)
• Processing integrity: Includes sub controls of the System Operations (CC7)
• Confidentiality: Includes sub controls of the Logical and Physical Access (CC6)
• Privacy - Includes sub controls of the Monitoring Activities (CC4)

Within each common control are a set of sub controls that turn the overarching standard into actionable tasks.

Passing a SOC 2 audit takes a lot of time, effort, and documentation. During a SOC2 audit, you not only need to show that your controls work during the audit period, but you also need to show that you have the ability to continuously monitor your security.

Going through the entire TSC framework is too long for a blog post. However, a quick look into a couple of controls of Logical and Physical Access (CC6) and System Operations (CC7) gives you an idea of what some of the controls look like and how you can utilize an SSPM to ease the SOC2 audit.

Get a 15-minute demo of how an SSPM can help your SOC 2 TSC audit

Logical and Physical Access Controls

This section sets out the types of controls needed to prevent unauthorized or inappropriate access to physical and digital assets and locations. Managing user access permissions, authentication, and authorization across the SaaS estate poses many challenges. In fact, as you look to secure your cloud apps, the distributed nature of users and managing the different access policies becomes increasingly challenging.

Under CC6.1 control, entities need to:

• Identify, classify, and manage information assets
• Restrict & manage user access
• Consider network segmentation
• Register, authorize, and document new infrastructure
• Supplement security by encrypting data-at-rest
• Protect encryption keys

Example

The department that utilizes a SaaS app is often the one that purchases and implements it. Marketing might implement a SaaS solution for monitoring leads while sales implements the CRM. Meanwhile, each application has its own set of access capabilities and configurations. However, these SaaS owners may not be trained in security or able to continuously monitor the app's security settings so the security team loses visibility. At the same time, the security team may not know the inner workings of the SaaS like the owner so they may not understand more complex cases which could lead to a security breach.

An SSPM solution, maps out all the user permissions, encryption, certificates and all security configurations available for each SaaS app. In addition to the visibility, the SSPM solution helps correct any misconfiguration in these areas, taking into consideration each SaaS app's unique features and usability.

In CC.6.2 control, entities need to:

• Create asset access credentiations based on authorization from the system's asset owner or authorized custodian
• Establish processes for removing credential access when the user no longer requires access
• Periodically review access for unnecessary and inappropriate individuals with credentials

Example

Permission drifts occur when a user has certain permissions as part of a group membership, but then gets assigned a specific permission that is more privileged than what the group has. Over time many users get extra permissions. This undermines the idea of provisioning using groups.

Classic deprovisioning issues, an SSPM solution can spot inactive users and help organizations to quickly remediate, or at the very least, alert the security team to the issue.

Under CC.6.3 control, entities need to:

• Establish processes for creating, modifying or removing access to protected information and assets
• Use role-based access controls (RBAC)
• Periodically review access roles and access rules

Example

You might be managing 50,000 users across five SaaS applications, meaning the security team needs to manage a total of 250,000 identities. Meanwhile, each SaaS has a different way to define identities, view them, and secure identities. Adding to the risk, SaaS applications don't always integrate with each other which means users can find themselves with different privileges across different systems. This then leads to unnecessary privileges that can create a potential security risk.

An SSPM solution allows visibility into user privileges and sensitive permission across all connected SaaS apps, highlighting the deviation from permission groups and profiles.

System Operations

This section focuses on detection and monitoring to ensure continued effectiveness of information security controls across systems and networks, including SaaS apps. The diversity of SaaS apps and potential for misconfigurations makes meeting these requirements challenging.

In CC7.1 control, entities need to:

• Define configuration standards
• Monitor infrastructure and software for noncompliance with standards
• Establish change-detection mechanisms to aler personnel to unauthorized modification for critical system, configuration, or content files
• Establish procedures for detecting the introduction of known or unknown components
• Conduct periodic vulnerability scans to detect potential vulnerabilities or misconfigurations

It is unrealistic to expect from the security team to define a "configuration standard" that complies with SOC2 without comparing against a built-in knowledge base of all relevant SaaS misconfigurations and to continuously comply with SOC2 without using an SSPM solution.

Get a 15-minute demo to see how an SSPM solution automates your SaaS security posture for SOC2 and other standards.

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New Variant of UpdateAgent Malware Infects Mac Computers with Adware

 Microsoft on Wednesday shed light on a previously undocumented Mac trojan that it said has undergone several iterations since its first appearance in September 2020, effectively granting it an "increasing progression of sophisticated capabilities."

The company's Microsoft 365 Defender Threat Intelligence Team dubbed the new malware family "UpdateAgent," charting its evolution from a barebones information stealer to a second-stage payload distributor as part of multiple attack waves observed in 2021.

"The latest campaign saw the malware installing the evasive and persistent Adload adware, but UpdateAgent's ability to gain access to a device can theoretically be further leveraged to fetch other, potentially more dangerous payloads," the researchers said.

The actively in-development malware is said to be propagated via drive-by downloads or advertisement pop-ups that masquerade as legitimate software like video applications and support agents, even as the authors have made steady improvements that have transformed UpdateAgent into a progressively persistent piece of malware.

Chief among the advancements include the capability to abuse existing user permissions to surreptitiously perform malicious activities and circumvent macOS Gatekeeper controls, a security feature that ensures only trusted applications from identified developers can be installed on a system.

In addition, UpdateAgent has been found to take advantage of public cloud infrastructure, namely Amazon S3 and CloudFront services, to host its second-stage payloads, including adware, in the form of .DMG or .ZIP files.

Once installed, the Adload malware makes use of ad injection software and man-in-the-middle (MitM) techniques to intercept and reroute users' internet traffic through the attacker's servers to insert rogue ads into web pages and search engine results to increase the chances of multiple infections on the devices.

"UpdateAgent is uniquely characterized by its gradual upgrading of persistence techniques, a key feature that indicates this trojan will likely continue to use more sophisticated techniques in future campaigns," the researchers cautioned.

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New Wave of Cyber Attacks Target Palestine with Political Bait and Malware

 

Cybersecurity researchers have turned the spotlight on a new wave of offensive cyberattacks targeting Palestinian activists and entities starting around October 2021 using politically-themed phishing emails and decoy documents.

The intrusions are part of what Cisco Talos calls a longstanding espionage and information theft campaign undertaken by the Arid Viper hacking group using a Delphi-based implant called Micropsia dating all the way back to June 2017.

The threat actor's activities, also tracked under the monikers Desert Falcon and the APT-C-23, were first documented in February 2015 by Kasperksy and subsequently in 2017, when Qihoo 360 disclosed details of cross-platform backdoors developed by the group to strike Palestinian institutions.

The Russian cybersecurity company-branded Arid Viper the "first exclusively Arabic APT group."

Then in April 2021, Meta (formerly Facebook), which pointed out the group's affiliations to the cyber arm of Hamas, said it took steps to boot the adversary off its platform for distributing mobile malware against individuals associated with pro-Fatah groups, the Palestinian government organizations, military and security personnel, and student groups within Palestine.

                                    Decoy document containing text on Palestinian reunification

The raft of new activity relies on the same tactics and document lures used by the group in 2017 and 2019, suggesting a "certain level of success" despite a lack of change in their tooling. More recent decoy files reference themes of Palestinian reunification and sustainable development in the territory that, when opened, lead to the installation of Micropsia on compromised machines.

The backdoor is designed to give the operators an unusual range of control over the infected devices, including the ability to harvest sensitive information and execute commands transmitted from a remote server, such as capturing screenshots, recording the current activity log, and downloading additional payloads.

"Arid Viper is a prime example of groups that aren't very advanced technologically, however, with specific motivations, are becoming more dangerous as they evolve over time and test their tools and procedures on their targets," researchers Asheer Malhotra and Vitor Ventura said.

"These [remote access trojans] can be used to establish long-term access into victim environments and additionally deploy more malware purposed for espionage and stealing information and credentials."

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