DEKENEAS NEXT-GEN TECHNOLOGIES is a cybersecurity company whose aim is to provide the means and methods needed to address the newest and most complex cyber attacks facing organizations and individuals in today's ever changing threat landscape. Our products encompass more than 30 years of experience in both offensive and defensive fields of operations and they were born from the actual needs security professionals encounter while facing real life attackers. Our flag ship product, the Browser Attack Detector, is an artificial intelligence powered web malware scanner able to discover known and unknwon attacks against browsers, such as exploits, watering holes, crypto jacking or data skimming, for laptops, desktops, mobile, or IoT devices. The concept behind the Browser Attack Detector was presented at multiple esteemed cyber security conferences around the world and among the early adopters of this technology are companies such as ORANGE ROMANIA COMMUNICATIONS SA or public institutions such as Romanian National Cybersecurity Directorate. Along the Browser Attack Detector we also provide our customers with a cybersecurity threat intelligence platform that collects data about attacks against traditional technologies, but also about attacks against ICS/SCADA, medical or IoT technologies, and a decoy system ("Am I Owned") that transforms your networks and devices into honey traps that lure attackers, making them unveil the presence on the premises before they are able to perform any actual damaging actions. For more information about our products consult the detailed presentations for Browser Attack Detector, Cyber Threat Intelligence and Am I Owned or contact us.
9.11.2023"DATA SKIMMING ATTACKS: HOW YOUR CREDIT CARD DATA GETS STOLEN FROM E-COMMERCE SITES" https://www.dekeneas.com/blog/data-skimming.html
5.10.2023"UNMASKING HIDDEN THREATS IN TRADITIONAL TECHNOLOGIES" https://www.dekeneas.com/blog/unmasking-hidden-threats.html
19.09.2023"THE ROLE OF ARTIFICIAL INTELLIGENCE IN DETECTING WEB MALWARE" https://www.dekeneas.com/blog/role-of-ai-in-detecting-web-malware.html
12.09.2023"THE EVOLUTION OF CYBER ATTACKS: FROM BASIC HACKS TO SOPHISTICATED EXPLOITS" https://www.dekeneas.com/blog/evolution-of-cyber-attacks.html
07.09.2023"ALL YOU NEED TO KNOW ABOUT WATERING HOLE ATTACKS" https://www.dekeneas.com/blog/what-are-watering-hole-attacks.html
08.03.2023 -- TODAY WE SAVED OUR CUSTOMER FROM BLACKBYTENT RANSOMWAREOne of the customers of AIO (AM I OWNED) product was alerted late last night by some of the decoys deployed inside their infrastructure. Specifically, the first alert was triggered by an Active Directory decoy, soon followed by triggering of various Microsoft Office and PDF decoys placed on a certain workstation inside their network. The incident response team was able to determine with precision the compromised workstation, isolating it from the network and recovering binaries used by the threat actors. After carefully investigating the binaries we were able to assert with certainty that they were part of BlackByteNT ransomware campaign. Also, the incident response team was able to determine that initial access was obtained through a malicious Microsoft Office document sent by e-mail (CVE-2023-21716).
06.12.2022 -- ROMANIAN PUBLIC INSTITUTION WEBSITE USED IN WATERING HOLE ATTACKRomanian public institution in Cluj area used in watering hole attack The exploit was a type confusion in V8 bug affecting Windows, Linux and MacOS Chrome and Microsoft Edge and it was patched in the latest Chrome, version 108.0.5359.94 for Mac and Linux, and to 108.0.5359.94 or 108.0.5359.95 for Windows. We were able to obtain the full exploitation chain and also, the second stage malware thanks to #Dekeneas next-gen dynamic analysis. We haven't been able to perform accurate attribution during this attack. Some other websites may be hosting the same attack code as we discovered this particular attack while one of our users was visiting the watering hole website.
14.11.2022 -- NEW PRODUCTS ADDEDDEKENEAS products: Browser Attack Detector Can detect cryptojacking attacks (unauthorized use of browser to mine cryptocurrencies), data skimming attacks (credit card stealing implants, usually in web shops) or known and unknown exploit attacks against Chrome, Firefox, Edge, Safari, for desktops/laptops/servers but also for mobile (Android and iOS) or IoT devices. Cyber Threat Intelligence NEW Custom tailored CTI feed collected from a network of hundreds of devices (honeypots with low, medium or high interaction) for more than 60 different technologies from generic technologies, such as HTTP or SSH, to ICS/SCADA or IoT technologies. Am I Owned NEW We can transform virtually any asset in your network or device into a decoy appealing to hackers. When attackers compromise such an asset you will get an alert, knowing something unauthorized is happening, long before the attacker can impact your organization. Phishing Attack Detection NEW Actively detecting phishing campaigns aimed at your organization, also providing analysis and takedown services.
22.02.2022 -- DEKENEAS 2.0 RELEASEDWe are thrilled to announce the release of DEKENEAS 2.0, three years after DEKENEAS 1.0 was first introducing the concept of using machine learning to detect browser attacks and malicious web implants. The experience we gathered allowed us to better understand the tactics, techniques and procedures used by skilled actors to exploit and attack browser technologies, and while we constantly improve the technologies used to detect, identify and analyze web based threats, the new release brings a total rewrite from scratch of the whole project, new approaches and technologies. As a result, we added new instructions and code constructs used in malicious implants to our detection algorithm, we developed a new technology called "Code Logic Emulator (CLE)", we improved the "Requirements Extractor (RX)" technology, we replaced the old Javscript sandbox with "Smart Dynamic Analysis (SDA)" for both mobile and desktop environments, supporting various browsers for Windows, Linux, MacOS, Android or iOS, and last, but not least, we added "Network Attack Detector (NAD)" which is also a novel technology aiming to identify exploitation attempts in network traffic. Code Logic Emulator "Code Logic Emulator" (CLE) is a technology we developed in order to maximize the detection probability of malicious web implants by emulating the logic behind the code without the need to emulate the code itself and before deciding to analyze it inside a sandbox environment. Understanding the logic behind the suspicious code adds a great number of new features to the malicious features dataset, which is used to describe the behaviour of a malicious implant, therefore giving a more accurate picture on the functionalities of the code. Requirements Extractor "Requirements Extractor" (RX) is a technology used to identify if the code under scrutiny is requiring specific conditions to run, such as certain user agents, browser settings, language settings, IP address space, etc. This information is used both as features in the malicious features dataset, but also to know a priori what kind of sandbox environment to be started for this specific piece of code. This technology greatly reduces the probability of missing certain malicious activities due to analysis performed in the wrong environment. Smart Dynamic Analysis One of the most important improvements we made to DEKENEAS platform is the implementation of native sandboxes. We designed and created sandboxes for Linux, Windows and MacOS operating systems which are used in classical desktop devices, but also we designed and created sandboxes for mobile devices running on iOS and Android. The sandboxes support various browser technologies, specific to each platform and deploy methods and techniques to deter the identification of the analysis environment by making it appear legitimate. This includes, but is not limited to user interactions, screen sizes, apps and programs installed, etc. Network Attack Detector The "Network Attack Detector" (NAD) is a novel technology able to identify attacks in network traffic. The "Network Attack Detector" decrypts network traffic between client browser and the web server and scans for various indicators of exploitation such as nop sleds, heap spraying, shellcode and other specific indicators of attacks or compromises. All these technologies work together to give a better insight and understanding on how the attacks are performed, providing a hollistic approach on identification and analysis of browser attacks, both on traditional devices such as personal computers, or laptops, but also on mobile devices such as smartphones or tablets. Happy hunting!
CONTACT USoffice@dekeneas.com @dekeneas @dekeneas
FREQUENTLY ASKED QUESTIONS
Q: Who is at risk of getting attacked through browser exploits?
A: Considering that browsers are part of our day to day activities, being for work or pleasure, anyone can be targeted with a browser exploit. However, if you work in a sensitive environment, and your job requires you to have access to sensitive organizational resources, the risk of being attacked with a browser exploit increases significantly. But browser exploits are not the only browser attacks..
Q: How could a browser exploit affect my work place?
A: Organizational network defenses have become increasingly performant in the past years, with organizations investing allocating increased budgets to cybersecurity, therefore making it harder for attackers to directly attack organization's network perimeter. But at the same time, organizations tend to not address the insider threat with the same type of resilience. Therefore if you use your smartphone, laptop or tablet to access organizational resources attackers gain a foothold inside the network.
Q: What other browser attacks are outhere, except device compromises through exploits?
A: While browser exploits are the most dangerous type of browser attack, there are also cryptojacking attacks and data skimming attacks. Cryptojacking attacks use your device to mine for cryptocurrencies consuming your CPU cycles for the benefit of the attackers. Data skimming attacks are usually placed in online shops or other type of websites which require the user to enter banking or credit card informations. They are totally invisible to the end user and any security product he may use and they collect these informations to be sent to the attackers. Cyber criminal groups such as Magecart are getting the spotlight in the past years but these types of attacks have been going for at least a decade and they continue to affect hundreds of thousands of websites around the world.
Q: My antivirus is updated to the latest. Am I still vulnerable?
A: Unfortunately yes. Antivirus products use signatures to detect attacks. If a signatures has not been previously generated, the attack goes unnoticed to the antivirus product.
Q: I have the latest next-generation detection and response endpoint protection. Am I still vulnerable?
A: Unfortunately yes. Even the most performant XDR endpoint protection uses some type of signature scanning corroborated with behavioral analysis and even artificial intelligence (AI). However, they cannot be installed on smart phones, tablets or IoT devices. And even for traditional systems, such as desktops or laptops they fail to accurately identify attacks, mostly because browsers are very difficult to inspect and instrument and because these attacks are specifically crafted to look like normal user activities.
Q: I only browse behind my corporate network. Am I still vulnerable?
Q: I use a different web malware scanner. Isn't that enough?
A: Unfortunately no. All the commercially available web malware scanners use signature scanning to detect attacks against browsers. While this approach is sufficient to detect known attacks, they have no way of detecting unknown attacks. Most web malware today is crafted in such way that it looks different for every infection, even inside the same website. Also, most of the commercially available web malware scanners only scan the first page of the website, while in reality the attack can be hidden deeper inside the website.
Q: Ok, and how does DEKENEAS does it then?
A: We have an artificial intelligence (AI) algorithm trained to recognize features that might serve a malicious purpose. And we do not consider these features separately, our AI tries to understand how these features could be used in conjunction to serve a malicious purpose. This approach allows us to select only those HTML elements, such as scripts or iframes, that have a high risk of being used for malicious purposes. After this filtering, we launch each suspicious element inside a dynamic analysis environment which mimicks in the slightiest detail the behaviour of a legitimate user, in order to bypass any anti analysis or instrumentation environment detection techniques the malware might use. We record these interactions and also we record all the traffic exchanged between our dynamic analysis environment and the suspicious HTML element. The recorded traffic is analyzed by another AI algorithm in order to determine wether there are any signs of attacks inside the traffic. If there were no interactions during the dynamic analysis and there were no signs of attack inside the network traffic recorded, we still consider the element suspicious, needing manual analysis by one of our specialists.
Q: So every suspicious script is possibly an attack?
A: Sometimes, yes. Some other times, no. There could be an attack that evaded our dynamic analysis environment, and it needs further inspection, but also, sometimes, not very often, legitimate HTML elements use the same techniques as malware and we detect that. But it's better to be safe than sorry.
Q: I started my scan a few hours ago and it still did not finish. Is there something wrong?
A: Normal websites have thousands of pages, each of these pages containing tenths or hundreds of HTML elements that need to be analyzed. Even though our AI is doing a fantastic job at eliminating benign looking elements, there are still tenths or hundreds of these elements that need to be passed to our dynamic analysis environment. This is the most consuming part of the process, as we try to mimick in the slightiest detail the behavior of a normal user. So, especially at the first iteration, a scan could last for a few hours, depending on the number of suspicious HTML elements found.
DEKENEASDEKENEAS is a unique product, being the only publicly available tool able to identify with great accuracy both known and unknown browser exploits ("0day") and attacks by the means of artificial intelligence algorithms, instead of traditional signature scanning. Our approach is mainly focused on detection of unknown attack vectors for the vast majority of existing desktop browsers, such as Chrome, Edge, Firefox or Safari, but also mobile devices browsers for Android and iPhone. Our artificial intelligence algorithms understand the code of the website before actually executing it, and tries to understand if the code constructs encountered are malware specific or they are benign. Also it tries to figure out if there are special conditions for certain code to run, such as specific User-Agent strings, language settings or IP addresses. All this information is later used during the instrumentation performed by Dekeneas Sandbox, which comes as a double check, actually executing the suspicious code in a real environment according to the special conditions requested by the analyzed code, launching a specific browser with specific language or country settings in a specific environment (desktop or mobile), and analyzing how the code interacts with the browser. In addition to code instrumentation Dekeneas Sandbox also analyzes the traffic generated looking for exploitation gadgets, therefore maximizing the chances of identifying unknown attacks.
- Signature less scanning - browser malware looks different from infection to infection so signature scanning is mostly useless
- In-depth scanning of websites - most attacks are not placed in the first page
- Code interpretation without actually executing the code - greatly optimizing analysis time
- Detection of attacks in the early stage - as opposed to traditional methods who detect post-exploitation stage of infection
- Anti anti analysis capabilities - most browser attacks are highly obfuscated and have anti analysis capabilities
- Anti evasion capabilities - most browser attacks are able to evade detection by targetting specific browsers, technologies or settings
Dekeneas On-Premise WSGThe Dekeneas WSG range is a family of secure web gateway appliances, integrating the advanced artificial intelligence malware scanning capabilities of the DEKENEAS into your network, protecting your users from some of the most elusive attacks used by hackers.