Tech News - Security

In less than ten months of Wireshark’s last release, the Wireshark community has now released Wireshark 2.6. Wireshark is one of the popular tools to analyze traffic over a network interface or a network stream. It is used for troubleshooting, analysis, development and education. Wireshark is based on the Gerald Combs-initiated "Ethereal" project, released under the terms of the GNU General Public License (GNU GPL). Wireshark 2.6 is released with numerous innovations, improvements and bug fixes. The highlight of Wireshark 2.6 is that, it is the last release that will support the legacy (GTK+) user interface. It will not be supported or available in Wireshark 3.0. Major improvements since 2.5, the last version, include: This version now supports HTTP Request sequences. Support for MaxMind DB files, GeoIP and GeoLite Legacy databases has been removed. Windows packages are now built using Microsoft Visual Studio 2017. The IP map feature (the “Map” button in the “Endpoints” dialog) has been removed. Some other improvements since the version 2.4 Display filter buttons can now be edited, disabled, and removed via a context menu directly from the toolbar Support for hardware-timestamping of packets has been added Application startup time has been reduced. Some keyboard shortcut mix-ups have been resolved by assigning new shortcuts to Edit → Copy methods New Protocol Support: Many protocols have been added including the following. ActiveMQ Artemis Core Protocol: This supports interceptors to intercept packets entering and exiting the server. Bluetooth Mesh Protocol : This allows (Bluetooth Low Energy) BLE devices to network together to carry data back to a gateway device, where it can be further routed to the internet. Steam In-Home Streaming discovery protocol: This allows one to use input and output on a single computer, and lets another computer actually handle the rendering, calculations, networking etc. Bug Fix: Dumpcap, a network traffic dump tool which lets one capture packet data from a live network and write the packets to a file, might not quit if Wireshark or TShark crashes. (Bug 1419) To know more about the updates in detail, read Wireshark 2.6.0 Release Notes What is Digital Forensics? Microsoft Cloud Services get GDPR Enhancements IoT Forensics: Security in an always connected world where things talk

git-bug is a distributed bug tracker that is embedded in git. Using git's internal storage ensures that no files are added in your project. You can push your bugs to the same git remote that you are already using to collaborate with other people. The main idea behind implementing a distributed bug tracker in Git was to stop relying on a web service somewhere to deal with bugs. Browsing and editing bug reports offline wouldn’t be much of a pain, thanks to this implementation. While git-bug addresses a pressing need, note that the project is not yet available for full fledged use and is currently a proof of concept released just 3 days ago at version 0.2.0. Reddit is abuzz with views on the release. A user quotes- Source: reddit.com Certain users also had counter thoughts on the cons of the release - Source: reddit.com   Now that you want to get your hands on git-bug, let’s look at how to get started. Installing git-bug, Linux packages needed and CLI usage for its implementation To install the git-bug, all you need to do is execute the following command- go get github.com/MichaelMure/git-bug If it's not done already, add golang binary directory in your PATH: export PATH=$PATH:$GOROOT/bin:$GOPATH/bin You can set pre-compiled binaries by following 3 simple steps: Head over to the release page and download the appropriate binary for your system. Copy the binary anywhere in your PATH Rename the binary to git-bug (or git-bug.exe on windows) The only linux packge needed for this release is the Archlinux (AUR) Further, you can use the CLI to implement the git-bug using the following commands- Create a new bug: git bug new Your favorite editor will open to write a title and a message. You can push your new entry to a remote: git bug push [<remote>] And pull for updates: git bug pull [<remote>] List existing bugs: git bug ls   Use commands like show, comment, open or close to display and modify bugs. For more details about each command, you can run git bug <command> --help or scan the command's documentation. Features of the git-bug #1 Interactive User Interface for the terminal Use the git bug termui  command to browse and edit bugs. This short video will demonstrate how easy and interactive it is to browse and edit bugs #2 Launch a rich Web UI Take a look at the awesome web UI that is obtained with git bug webui. Source: github.com     Source: github.com   This web UI is entirely packed inside the same go binary and serve static content through a localhost http server. It connects to  backend through a GraphQL API. Take a look at the schema for more clarity. The additional features that are planned include media embedding import/export of github issue extendable data model to support arbitrary bug tracker inflatable raptor Every new release is expected to come with exciting new features, it is also coupled with a few minor constraints. You can check out some of the minor inconveniences as listed out on the github page. We can’t wait for the release to be in a fully working condition. But before that, if you need any additional information on how the git-bug works, head over to the github page. Snapchat source code leaked and posted to GitHub GitHub open sources its GitHub Load Balancer (GLB) Director Homebrew’s Github repo got hacked in 30 mins. How can open source projects fight supply chain attacks?

On November 26, the Kali Linux team announced its fourth and final release of 2019, Kali Linux 2019.4, which is readily available for download. A few features of Kali Linux 2019.4 include a new default desktop environment, Xfce; a new GTK3 theme (for Gnome and Xfce); Kali Undercover” mode, the kernel has been upgraded to version 5.3.9, and much more. Talking about ARM the team highlighted, “2019.4 is the last release that will support 8GB sdcards on ARM. Starting in 2020.1, a 16GB sdcard will be the minimum we support.” What’s new in Kali Linux 2019.4? New desktop environment, Xfce and GTK3 theme The much-awaited desktop environment update is here. The older versions had certain performance issues resulting in fractured user experience. To address this, they developed a new theme running on Xfce. Its lightweight design can run on all levels of Kali installs. The new theme can handle various needs of the average user with no changes. It uses standard UI concepts and there is no learning curve to it. It looks great with modern UI elements that make efficient use of screen space. Kali Undercover mode For pentesters doing their work in a public environment, the team has made a little script that will change the user’s Kali theme to look like a default Windows installation. This way, users can work a bit more incognito. “After you are done and in a more private place, run the script again and you switch back to your Kali theme. Like magic!”, the official blog post reads. BTRFS during setup Another significant new addition to the documentation is the use of BTRFS as a root file system. This gives users the ability to do file system rollbacks after upgrades. In cases when users are in a VM and about to try something new, they will often take a snapshot in case things go wrong. However, running Kali bare metal is not easy. There is also a manual clean up included. With BTRFS, users can have a similar snapshot capability on a bare metal install! NetHunter Kex – Full Kali Desktop on Android phones With NetHunter Kex, users can attach their Android devices to an HDMI output along with Bluetooth keyboard and mouse and get a full, no compromise, Kali desktop from their phones. To get a full breakdown on how to use NetHunter Kex, check out its official documents on the Kali Linux website. Kali Linux users are excited about this release and look forward to trying the newly added features. https://twitter.com/firefart/status/1199372224026861568 https://twitter.com/azelhajjar/status/1199648846470615040 To know more about other features in detail, read the Kali Linux 2019.4  official release on Kali Linux website. Glen Singh on why Kali Linux is an arsenal for any cybersecurity professional [Interview] Kali Linux 2019.1 released with support for Metasploit 5.0 Kali Linux 2018 for testing and maintaining Windows security – Wolf Halton and Bo Weaver [Interview]

On 31st July 2018, Eric Holmes, a security researcher gained access to Homebrew's GitHub repo easily (He documents his experience in an in-depth Medium post). Homebrew is a free and open-source software package management system with well-known packages like node, git, and many more. It simplifies the installation of software on macOS. The Homebrew repository contains its recently elevated scopes. Eric gained access to git push on Homebrew/brew and Homebrew/homebrew-core. He was able to invade and make his first commit into Homebrew’s GitHub repo within 30 minutes. Attack = Higher chances of obtaining user credentials After getting an easy access to Homebrew’s GitHub repositories, Eric’s prime motive was to uncover user credentials of some of the members of Homebrew GitHub org. For this, he made use of an OSSINT tool by Michael Henriksen called gitrob, which easily automates the credential search. However, he could not find anything interesting. Next, he explored Homebrew’s previously disclosed issues on https://hackerone.com/Homebrew, which led him to the observation that Homebrew runs a Jenkins instance that’s (intentionally) publicly exposed at https://jenkins.brew.sh. With further invasion into the repo, Eric encountered that the builds in the “Homebrew Bottles” project were making authenticated pushes to the BrewTestBot/homebrew-core repo. This further led him to an exposed GitHub API token. The token opened commit access to these core Homebrew repos: Homebrew/brew Homebrew/homebrew-core Homebrew/formulae.brew.sh Eric stated in his post that, “If I were a malicious actor, I could have made a small, likely unnoticed change to the openssl formulae, placing a backdoor on any machine that installed it.” Via such a backdoor, intruders could have gained access to private company networks that use Homebrew. This could further lead to data breach on a large scale. Eric reported this issue to Homebrew developer, Mike McQuaid. Following which, he publicly disclosed the issue on the blog at https://brew.sh/2018/08/05/security-incident-disclosure/. Within a few hours the credentials had been revoked, replaced and sanitised within Jenkins so they would not be revealed in future. Homebrew/brew and Homebrew/homebrew-core were updated so non-administrators on those repositories cannot push directly to master. The Homebrew team worked with GitHub to audit and ensure that the given access token wasn’t used maliciously, and didn’t make any unexpected commits to the core Homebrew repos. As an ethical hacker, Eric reported the vulnerabilities he found to the Homebrew team and did no harm to the repo itself. But, not all projects may have such happy endings. How can one safeguard their systems from supply chain attacks? The precautions which Eric Holmes took were credible. He informed the Homebrew developer. However, not every hacker has good intentions and it is one’s responsibility to make sure to keep a check on all the supply chains associated to an organization. Keeping a check on all the libraries One should not allow random libraries into the supply chain. This is because it is difficult to partition libraries with organization’s custom code, thus both run with the same privilege risking the company’s security. One should make sure to levy certain policies around the code the company wishes to allow. Only projects with high popularity, active committers, and evidence of process should be allowed. Establishing guidelines Each company should create guidelines for secure use of the libraries selected. For this, a prior definition of what the libraries are expected to be used for should be made. The developers should also be detailed in safely installing, configuring, and using each library within their code. Identification of dangerous methods and how to use them safely should also be taken care of. A thorough vigilance within the inventory Every organization should keep a check within their inventories to know what open source libraries they are using. They should also ensure to set up a notification system which keeps them abreast of which new vulnerabilities the applications and servers are affected. Protection during runtime Organizations should also make use of runtime application security protection (RASP) to prevent both known and unknown library vulnerabilities from being exploited. If in case they notice new vulnerabilities, the RASP infrastructure enables one to respond in minutes. The software supply chain is the important part to create and deploy applications quickly. Hence, one should take complete care to avoid any misuse via this channel. Read the detailed story of Homebrew’s attack escape on its blog post and Eric’s firsthand account of how he went about planning the attack and the motivation behind it on his medium post. DCLeaks and Guccifer 2.0: Hackers used social engineering to manipulate the 2016 U.S. elections Twitter allegedly deleted 70 million fake accounts in an attempt to curb fake news YouTube has a $25 million plan to counter fake news and misinformation

After Google Launched its Certification Authority in August 2017, it has now put in a  request to Mozilla certification store for the inclusion of the Google Trust Services R1, R2, R3, and R4 roots as documented in the following bug. Google’s application states the following- "Google is a commercial CA that will provide certificates to customers from around the world.  We will offer certificates for server authentication, client authentication, email (both signing and encrypting), and code signing.  Customers of the Google PKI are the general public. We will not require that customers have a domain registration with Google, use domain suffixes where Google is the registrant, or have other services from Google." What are Google Trust Services Roots? To adopt an independent infrastructure and build the "foundation of a more secure web," Google Trust Services allows the company to issue its own TLS/SSL certificates for securing its web traffic via HTTPS, instead of relying on third-party certs. The main aim of launching the GTS was to bring security and authentication certificates up to par with Google’s rigorous security standards. This means invalidating the old, insecure HTTP standard in Chrome, and depreciate Adobe Flash, a web program known to be insecure, and a resource hog. GTS will provide HTTPS certificates public websites to API servers, and it will be inclusive to all Alphabet companies, not just Google. Developers who build products that connect to Google’s services will have to include the new Root Certificates. All GTS roots expire in 2036, while GS Root R2 expires in 2021 and GS Root R4 in 2038. Google will also be able to cross-sign its CAs, using GS Root R3 and GeoTrust, to ease potential timing issues while setting up the root CAs. To know more about these trust services, you can visit GlobalSign. Some noticeable points in this request are Google has supplied a key generation ceremony audit report Other than the disclosed intermediates and required test certificates, no issuance has been detected from these roots. Section 1.4.2 of the CPS expressly forbids the use of Google certificates for "man-in-the middle purposes". Appendix C of the current CPS indicates that Google limits the lifetime of server certificates to 365 days. The following concerns exist in the Roots- From the transfer on 11-August 2016 through 8-December 2016, at the time it would not have been clear if any policies applied to these new roots. The applicable CPS (Certification Practice Statement) during that period makes no reference to these roots. Google does state in their current CPS that these roots were operated according to that CPS. From the transfer on 11-August 2016 through the end of Google’s audit period on 30-September, 2016, these roots were not explicitly covered by either Google’s audit nor GlobalSign’s audit. The discussion was concluded with adding this policy to the main Mozilla Root Store Policy (section 8). With these changes and the filing of the bug, Mozilla plans to take no action against GTS based on what has been discovered and discussed. Here is what users had to say on this request- Source: Vue-hn To get a complete insight into this request, head over to Google groups. Let’s Encrypt SSL/TLS certificates gain the trust of all Major Root Programs Pay your respects to Inbox, Google’s email innovation is getting discontinued Google’s prototype Chinese search engine ‘Dragonfly’ reportedly links searches to phone numbers  

The U.S. Defense Advanced Research Projects Agency ( DARPA) has come out with AI-based forensic tools to catch deepfakes, first reported by MIT technology review yesterday. According to MIT Technology Review, the development of more tools is currently under progress to expose fake images and revenge porn videos on the web. DARPA’s deepfake mission project was announced earlier this year. Alec Baldwin on Saturday Night Live face swapped with Donald Trump As mentioned in the MediFor blog post, “While many manipulations are benign, performed for fun or for artistic value, others are for adversarial purposes, such as propaganda or misinformation campaigns”. This is one of the major reasons why DARPA Forensics experts are keen on finding methods to detect deepfakes videos and images How did deepfakes originate? Back in December 2017, a Reddit user named “DeepFakes” posted extremely real-looking explicit videos of celebrities. He used deep learning techniques to insert celebrities’ faces into adult movies. Using Deep learning, one can combine and superimpose existing images and videos onto original images or videos to create realistic-seeming fake videos. As per the MIT technology review,“Video forgeries are done using a machine-learning technique -- generative modeling -- lets a computer learn from real data before producing fake examples that are statistically similar”. Video tampering is done using two neural networks -- generative adversarial networks which work in conjunction “to produce ever more convincing fakes”. Why are deepfakes toxic? An app named FakeApp was released earlier this year which helped create deepfakes quite easily. FakeApp uses neural networking tools developed by Google's AI division. The app trains itself to perform image-recognition tasks using trial and error. Ever since its release, the app has been downloaded more than 120,000 times. In fact, there are tutorials online on how to create deepfakes. Apart from this, there are regular requests on deepfake forums, asking users for help in creating face-swap porn videos of ex-girlfriends, classmates, politicians, celebrities, and teachers. Deepfakes is even be used to create fake news such as world leaders declaring war on a country. The toxic potential of this technology has led to a growing concern as deepfakes have become a powerful tool for harassing people. Once deepfakes found their way on the world wide web, many websites such as Twitter and PornHub, banned them from being posted on their platforms. Reddit also announced a ban on deepfakes, earlier this year, killing The “deepfakes” subreddit which had more than 90,000 subscribers, entirely. MediFor: DARPA’s AI weapon to counter deepfakes DARPA’s Media Forensics group, also known as MediFor, works in a group along with other researchers is set on developing AI tools for deepfakes. It is currently focusing on four techniques to catch the audiovisual discrepancies present in a forged video. This includes analyzing lip sync, detecting speaker inconsistency, scene inconsistency and content insertions. One technique comes from a team led by Professor Siwei Lyu of SUNY Albany. Lyu mentioned that they “generated about 50 fake videos and tried a bunch of traditional forensics methods. They worked on and off, but not very well”. As the deepfakes are created using static images, Lyu noticed that that the faces in deepfakes videos rarely blink and that eye-movement, if present, is quite unnatural. An academic paper titled "In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking," by Yuezun Li, Ming-Ching Chang and Siwei Lyu explains a method to detect forged videos. It makes use of Long-term Recurrent Convolutional Networks (LRCN). According to the research paper, people, on an average, blink about 17 times a minute or 0.283 times per second. This rate increases with conversation and decreases while reading. There are a lot of other techniques which are used for eye blink detection such as detecting the eye state by computing the vertical distance between eyelids, measuring eye aspect ratio ( EAR ), and using the convolutional neural network (CNN) to detect open and closed eye states. But, Li, Chang, and Lyu use a different approach. They rely on  Long-term Recurrent Convolutional Networks (LRCN) model. They first perform pre-processing to identify facial features and normalize the video frame orientation. Then, they pass cropped eye images into the LRCN for evaluation. This technique is quite effective. It is also better as compared to other approaches, with a reported accuracy of 0.99 (LRCN) compared to 0.98 (CNN) and 0.79 (EAR). However, Lyu says that a skilled video editor can fix the non-blinking deepfakes by using images that shows blinking eyes. But, Lyu’s team has a secret effective technique in the works to fix even that, though he hasn’t divulged any details. Others in DARPA are on the look-out for similar cues such as strange head movements, odd eye color, etc as these little details are leading the team even closer to detection of deepfakes. As mentioned in the MIT Technology review post, “the arrival of these forensics tools may simply signal the beginning of an AI-powered arms race between video forgers and digital sleuths” and how”. Also, MediFor states that “If successful, the MediFor platform will automatically detect manipulations, provide detailed information about how these manipulations were performed, and reason about the overall integrity of visual media to facilitate decisions regarding the use of any questionable image or video”. Deepfakes need to stop and the U.S. Defense Advanced Research Projects Agency ( DARPA) seems all set to fight against them. Twitter allegedly deleted 70 million fake accounts in an attempt to curb fake news A new WPA/WPA2 security attack in town: Wi-fi routers watch out! YouTube has a $25 million plan to counter fake news and misinformation  

In today’s world, organizations and companies go to great lengths to protect themselves from network breaches. However, even a pinhole is enough for the attackers to intrude into any system. Last week, routers by Cisco and Huawei were hacked by two separate groups using different methods. Cisco’s routers were hacked using a backdoor attack while Huawei routers were exploited using a much older vulnerability programming code. An abnormal rise in the Cisco router backdoors Cisco in the year 2004 had written the IETF proposal for a “lawful intercept” backdoor for their routers. This proposal stated that the law enforcement teams could use the intercept to remotely log in to routers. These routers which are sold to ISPs and other large enterprises would allow the law enforcement agents to wiretap IP networks. These law enforcement agents are supposed to gain such an access only via a court order or other legal access request. [box type="shadow" align="" class="" width=""]A backdoor is a malware type which can surpass the normal authentication process for accessing any system or application. Some backdoors are legitimate and assist, for instance, manufacturers to regain lost passwords. However, these backdoors can be used by attackers to remotely access the systems without anyone on the system knowing it.[/box] However, later in the year 2010, an IBM security researcher stated that such a protocol would give an easy access to malicious attackers and would take over Cisco IOS routers. Also, the ISPs related to these routers would also end up being hacked. Some undocumented backdoors were discovered in the year 2013, 2014, 2015, and 2017. According to Tom’s Hardware, this year alone, Cisco recorded five different backdoors within their routers, which resulted in a security flaw for the company’s routers. Let’s have a look at the list of undocumented backdoors found and when. The month of March recorded two backdoors. Firstly, a hardcoded account with the username ‘cisco’, which would have provided an intrusion within more than 8.5 million Cisco routers and switches in a remote mode. Another hardcoded password was found for Cisco's Prime Collaboration Provisioning (PCP) software. This software is used for the remote installation of Cisco voice and video products. May revealed another backdoor in Cisco’s Digital Network Architecture (DNA) Center. This center is used by enterprises to provision devices across a network. Further, in the month of June, Cisco’s Wide Area Application Services (WAAS) found a backdoor account. Note that this is a software tool for traffic optimizations in the Wide Area Network (WAN). The most recent backdoor, found this month, was in the Cisco Policy Suite, which is a software suite for ISPs and large companies that can manage a network’s bandwidth policies. Using this backdoor, the attacker gets a root access to the network with no mitigations against it. However, this backdoor has been patched with Cisco’s software update. The question that arises from these incidents is whether these backdoors were created accidentally or actually by intruders? The recurrence of such incidents does not paint a good picture of Cisco as a responsible, reliable and trustworthy network for end users. Botnet built in a day brings down Huawei routers Researchers from the NewSky security spotted a new botnet last week, which nearly enslaved 18,000 Huawei’s IoT devices within a day. [box type="shadow" align="" class="" width=""]Botnets are huge networks of enslaved devices and can be used to perform distributed denial-of-service attack (DDoS attack), send malicious packets of data to a device, and remotely execute code.[/box] The most striking feature of this huge botnet is that it was built within a day and with a vulnerability which was previously known, as CVE-2017-17215. Anubhav said, “It's painfully hilarious how attackers can construct big bot armies with known vulns"This botnet was created by a hacker, nicknamed Anarchy, says Ankit Anubhav, security researcher at NewSky security. Other security firms including Rapid7 and Qihoo 360 Netlab also confirmed the existence of this new botnet. They first noticed a huge increase in Huawei’s device scanning. Anubhav states that the hacker revealed to him an IP list of victims. This list has not been made public yet. He further adds that the same code was released as public in January this year. The same code was used in the Satori and Brickerbot botnets, and also within other botnets based on Mirai botnets (Mirai botnets were used in 2016 to disrupt Internet services across the US on a huge scale). The NetSky security researcher suspects that Anarchy may be the same hacker known as Wicked, who was linked with the creation of the Owari/Sora botnets. Moreover, Anarchy/Wicked told the researcher that they also plan to start a scan for Realtek router vulnerability CVE-2014-8361, in order to enslave more devices. After receiving such a warning from the hacker himself, what new security measures will be taken henceforth? Read more about this Huawei botnet attack on ZDNet. Is Facebook planning to spy on you through your mobile’s microphones? Social engineering attacks – things to watch out for while online DCLeaks and Guccifer 2.0: How hackers used social engineering to manipulate the 2016 U.S. elections

Last week, a group of security researchers reported that they have found a new malware that takes its instructions from code hidden in memes posted to Twitter. This method is popularly known as Steganography, a method popularly used by cybercriminals to abstract a malicious file within an image to escape from security solutions. According to Trend Micro, some malware authors posted two tweets including malicious memes on 25th and 26th October. These images were tweeted via a Twitter account created in 2017.  “The memes contain an embedded command that is parsed by the malware after it’s downloaded from the malicious Twitter account onto the victim’s machine, acting as a C&C service for the already- placed malware”, reported Trend Micro. According to the blog post, this new threat is detected as TROJAN.MSIL.BERBOMTHUM.AA. Also, this malware gets its command from a legitimate source, which they state is a popular networking platform. The memes cannot be taken down until the malicious Twitter account is disabled. Twitter, on the other hand, has already taken the account offline as of December 13, 2018. Malicious memes are no laughing matter The memes posted via the malicious Twitter accounts have a “/print” command hidden, which enables the malware to take screenshots of the infected machine. These screenshots are then sent to a C&C server whose address is obtained through a hard-coded URL on pastebin.com. Next, the malware will send out the collected information or the command output to the attacker by uploading it to a specific URL address. According to Trend Micro, “During analysis, we saw that the Pastebin URL points to an internal or private IP address, which is possibly a temporary placeholder used by the attackers. The malware then parses the content of the malicious Twitter account and begins looking for an image file using the pattern:  “<img src=\”(.*?):thumb\” width=\”.*?\” height=\”.*?\”/>” on the account.” Source: TrendMicro Researchers have also mentioned some other commands supported by this malware, which includes /processos to retrieve the list of running processes. /clip, to capture clipboard content, /username to retrieve username from the infected machine, and /docs to retrieve filenames from a predefined path such as (desktop, %AppData% etc.) According to TechCrunch, “The malware appears to have first appeared in mid-October, according to a hash analysis by VirusTotal, around the time that the Pastebin post was first created.” After Trend Micro reported the account, Twitter pulled the account offline, suspending it permanently. How the biggest ad fraud rented Datacenter servers and used Botnet malware to infect 1.7m systems How to build a convolution neural network based malware detector using malware visualization [Tutorial] Privilege escalation: Entry point for malware via program errors

Last week, the Metasploit team announced the release of its fifth version, Metasploit 5.0. This latest update introduces multiple new features including Metasploit’s new database and automation APIs, evasion modules and libraries, expanded language support, improved performance, and more. Metasploit 5.0 includes support for three different module languages; Go, Python, and Ruby. What’s New in Metasploit 5.0? Database as a RESTful service The latest Metasploit 5.0 now adds the ability to run the database by itself as a RESTful service on top of the existing PostgreSQL database backend from the 4.x versions. With this, multiple Metasploit consoles can easily interact. This change also offloads some bulk operations to the database service, which improves performance by allowing parallel processing of the database and regular msfconsole operations. New JSON-RPC API This new API will be beneficial for users who want to integrate Metasploit with new tools and languages. Till now, Metasploit supported automation via its own unique network protocol, which made it difficult to test or debug using standard tools like ‘curl’. A new common web service framework Metasploit 5.0 also adds a common web service framework to expose both the database and the automation APIs; this framework supports advanced authentication and concurrent operations and paves the way for future services. New evasion modules and libraries The Metasploit team announced a new evasion module type in Metasploit along with a couple of example modules in 2008. Using these module types, users can easily develop their own evasions and also add a set of convenient libraries that developers can use to add new on-the-fly mutations to payloads. A recent module uses these evasion libraries to generate unique persistent services. With Metasploit 5.0’s generation libraries, users can now write shellcode in C. Execution of an exploit module The ability to execute an exploit module against more than one target at a given point of time was a long-requested feature. Usage of the exploit module was limited to only one host at a time, which means any attempt at mass exploitation required writing a script or manual interaction. With Metasploit 5.0, any module can now target multiple hosts in the same way by setting RHOSTS to a range of IPs or referencing a hosts file with the file:// option. Improved search mechanism With a new improved search mechanism, Metasploit’s slow search has been upgraded and it now starts much faster out of the box. This means that searching for modules is always fast, regardless of how you use Metasploit. In addition, modules have gained a lot of new metadata capabilities. New metashell feature The new metashell feature allows users to background sessions with the background command, upload/download files, or even run resource scripts, all without needing to upgrade to a Meterpreter session first. As backward compatibility, Metasploit 5.0 still supports running with just a local database, or with no database at all. It also supports the original MessagePack-based RPC protocol. To know more about this news in detail, read its release notes on GitHub. Weaponizing PowerShell with Metasploit and how to defend against PowerShell attacks [Tutorial] Pentest tool in focus: Metasploit Getting Started with Metasploitable2 and Kali Linux

Researchers from the North China Electric Power University have recently published a paper titled, ‘A Review on The Use of Deep Learning in Android Malware Detection’. Researchers highlight the fact that Android applications can not only be used by application developers, but also by malware developers with criminal intention to design and spread malicious applications that can affect the normal work of Android phones and tablets, steal personal information and credential data, or even worse lock the phone and ask for ransom. In this paper, they have explained how deep learning methods can be used as a countermeasure in Android malware detection to fight back malware. Android Malware Detection Techniques Researchers have said that one critical point of mobile phones is that they are a sensor-based event system, which permits malware to respond to approaching SMS, position changes and so forth, increasing the sophistication of automated malware-analysis techniques. Moreover, the apps can use services and activities and integrate varied programming languages (e.g. Java and C++) in one application. Each application is analyzed in the following stages: Static Analysis The static analysis screens parts of the application without really executing them. This analysis incorporates Signature-based, Permission-based and Component-based analysis. The Signature-based strategy draws features and makes distinctive signs to identify specific malware. Hence, it falls short to recognize the variation or unidentified malware. The Permission-based strategy recognizes permission requests to distinguish malware. The Component-based techniques decompile the APP to draw and inspect the definition and byte code connections of significant components (i.e. activities, services, etc.), to identify the exposures. The principal drawbacks of static analysis are the lack of real execution paths and suitable execution conditions. Dynamic Analysis This technique includes the execution of the application on either a virtual machine or a physical device. This analysis results in a less abstract perspective of application than static analysis. The code paths executed during runtime are a subset of every single accessible path. The principal objective of the analysis is to achieve high code inclusion since every feasible event ought to be activated to watch any possible malicious behavior Hybrid Analysis The hybrid analysis technique includes consolidating static and dynamic features gathered from examining the application and drawing data while the application is running, separately. Nevertheless, it would boost the accuracy of the identification. The principal drawback of hybrid analysis is that it consumes the Android system resources and takes a long time to perform the analysis. Use of deep learning in Android malware detection Currently available machine learning has several weaknesses and some open issues related to the use of DL in Android malware detection include: Deep learning lacks transparency to provide an interpretation of the decision created by its methods. Malware analysts need to understand how the decision was made. There is no assurance that classification models built based on deep learning will perform in different conditions with new data that would not match previous training data. Deep learning studies complex correlations within input and output feature with no innate depiction of causality. Deep learning models are not autonomous and need continual retraining and rigorous parameters adjustments. The DL models in the training phase were subjected to data poisoning attacks, which are merely implemented by manipulating the training and instilling data that make a deep learning model to commit errors. In the testing phase, the models were exposed to several attack types including: Adversarial Attacks are where the DL model inputs are the ones that an adversary has invented deliberately to cause the model to make mistakes Evasion attack: Here, the intruder exploits malevolent instances at test time to have them incorrectly classified as benign by a trained classifier, without having an impact over the training data. This can breach system integrity, either with a targeted or with an indiscriminate attack. Impersonate attack: This attack mimics data instances from targets. The attacker plans to create particular adversarial instances to such an extent that current deep learning-based models mistakenly characterize original instances with different tags from the imitated ones. Inversion attack: This attack uses the APIs allowed by machine learning systems to assemble some fundamental data with respect to the target system models. This kind of attack is divided into two types; Whitebox attack and Blackbox attack. The white-box attack implies that an aggressor can loosely get to and download learning models and other supporting data, while the black-box one points to the way that the aggressor just knows the APIs opened by learning models and some observation after providing input. According to the researchers, hardening deep learning models against different adversarial attacks and detecting, describing and measuring concept drift are vital in future work in Android malware detection. They also mentioned that the limitation of deep learning methods such as lack of transparency and being nonautonomous, is to build more efficient models. To know more about this research in detail, read the research paper. Researchers introduce a deep learning method that converts mono audio recordings into 3D sounds using video scenes IEEE Computer Society predicts top ten tech trends for 2019: assisted transportation, chatbots, and deep learning accelerators among others Stanford researchers introduce DeepSolar, a deep learning framework that mapped every solar panel in the US

Brave, the open source privacy- focussed browser, has allegedly introduced a ‘backdoor’ to remotely inject headers in HTTP requests that may track users, say users on HackerNews. Users on Twitter and HackerNews have expressed their concerns over the new update on custom HTTP headers added by the Brave team: https://twitter.com/WithinRafael/status/1094712882867011585 Source: HackerNews A user on Reddit has explained this move as “not tracking anything, they just send the word "Brave" to the website whenever you visit certain partners of theirs. So for instance visiting coinbase.com sends an "X-Brave-Partner" custom header to coinbase.com.” Brendan Eich, from the Brave team, has replied back to this allegation saying that the ‘Update is not a "backdoor" in any event and is a custom header instead.’  He says the update is about custom HTTP headers that Brave sends to its partners, with fixed header values. There is no tracking hazard in the new update. He further stresses on the fact that Brave blocks 3rd party cookies and storage and 3rd party fingerprinting along with HSTS supercookies; thus assuring users on preserving their privacy. “I find it silly to assume we will "heel turn" so obviously and track our users. C'mon! We defined our model so we can't cheat without losing lead users who would see through it. That requires seeing clearly things like the difference between tracking and script blocking or custom header sending, though.” Users have also posted on Hacker News that the Brave browser Tracking Protection feature does not block tracking scripts from hostnames associated with Facebook and Twitter. The tracking_protection_service.h file contains a comment informing that a tracking protection white_list variable was created as a "Temporary hack which matches both browser-laptop and Android code". Bleepingcomputer also reports that this whitelist variable is associated with code in the tracking_protection_service.cc file that adds various Facebook and Twitter hostnames to the whitelist variable so that they are not blocked by Brave's Tracking Protection feature. In response to this comment, Brave says that the issue that was opened on September 8th, 2018 and developers decided to whitelist tracking scripts from Facebook and Twitter because blocking them would “affect the functionality of many sites” including Facebook logins. You can head over to Brendan’s Reddit thread for more insights on this update. Brave introduces Brave Ads that share 70% revenue with users for viewing ads Chromium-based Brave browser shows 22% faster page load time than its Muon-based counterpart Otter Browser’s first stable release, v1.0.01 is out

In the new found age of Artificial Intelligence, where everything and everyone uses Machine Learning concepts to make life easier, the dark side of the same is can be left unexplored. Cybersecurity is gaining a lot of attention these days.The most influential organizations have experienced a downfall because of undetected malware that have managed to evade even the most secure cyber defense mechanisms. The job just got easier for cyber criminals that exploit AI to empower them and launch attacks. Imagine combining AI with cyber attacks! At last week’s Black Hat USA 2018 conference, IBM researchers presented their newly developed malware “DeepLocker” that is backed up by AI. Weaponized AI seems here to stay. Read Also: Black Hat USA 2018 conference Highlights for cybersecurity professionals All you need to know about DeepLocker Simply put, DeepLocker is a new generation malware which can stealth under the radar and go undetected till its target is reached. It uses an Artificial Intelligence model to identify its target using indicators like facial recognition, geolocation and voice recognition. All of which is easily available on the web these days! What’s interesting is that the malware can hide its malicious payload in carrier applications- like a video conferencing software, and go undetected by most antivirus and malware scanners until it reaches specific victims. Imagine sitting on your computer performing daily tasks. Considering that your profile pictures are available on the internet, your video camera can be manipulated to find a match to your online picture. Once the target (your face) is identified, the malicious payload can be unleashed thanks to your face which serves as a key to unlock the virus. This simple  “trigger condition” to unlock the attack is almost impossible to reverse engineer. The malicious payload will only be unlocked if the intended target is reached. It achieves this by using a deep neural network (DNN) AI model. The simple logic of  “if this, then that” trigger condition used by DeepLocker is transformed into a deep convolutional network of the AI model.   DeepLocker – AI-Powered Concealment   Source: SecurityIntelligence   The DeepLocker makes it really difficult for malware analysts to answer the 3 main questions- What target is the malware after-  Is it after people’s faces or some other visual clues? What specific instance of the target class is the valid trigger condition? And what is the ultimate goal of the attack payload? Now that’s some commendable work done by the IBM researchers. IBM has always strived to make a mark in the field of innovation. DeepLocker comes as no surprise as IBM has the highest number of facial recognition patents granted in 2018. BlackHat USA 2018 sneak preview The main aim of the IBM Researchers- Marc Ph. Stoecklin, Jiyong Jang and Dhilung Kirat-  briefing the crowd in the BlackHat USA 2018 conference was, To raise awareness that AI-powered threats like DeepLocker can be expected very soon To demonstrate how attackers have the capability to build stealthy malware that can circumvent defenses commonly deployed today and To provide insights into how to reduce risks and deploy adequate countermeasures. To demonstrate the efficiency of DeepLocker’s capabilities, they designed and demonstrated a proof of concept. The WannaCry virus was camouflaged in a benign video conferencing application so that it remains undetected by antivirus engines and malware sandboxes. As a triggering condition, an individual was selected, and the AI was trained to launch the malware when certain conditions- including the facial recognition of the target- were met. The experiment was, undoubtedly, a success. The DeepLocker is just an experiment by IBM to show how open-source AI tools can be combined with straightforward evasion techniques to build a targeted, evasive and highly effective malware. As the world of cybersecurity is constantly evolving, security professionals will now have to up their game to combat hybrid malware attacks. Found this article Interesting? Read the Security Intelligence blog to discover more. 7 Black Hat USA 2018 conference cybersecurity training highlights 12 common malware types you should know Social engineering attacks – things to watch out for while online  

Signal, the encrypted communication App for iOs and Android, recently announced optional link previews for the four most popular sites- Imgur, Reddit, Instagram, and YouTube. This will enable Signal users to see what’s behind a particular URL, while sharing content with their friends. According to Joshua Lund, the creator of Signal, the feature has been created in such a way that users can generate link previews while hiding the URL from the Signal service itself, thereby shielding their IP address from the previewed site, and obfuscating the true size of the preview image. Link previews will expose relevant pieces of the URL to the recipient. There are some sites like YouTube where the URL is a random string of letters, numbers, and symbols. A recipient will never know where the link goes until they click on the same. With link previews in place, users will get an idea of what they can expect when they click the link, just by looking at the preview. Users can disable this feature through settings or  by tapping the 'X' in the corner of the preview before hitting send. The process of sending a link preview follows 3 simple steps: The Signal app will establish a TCP connection using a privacy-enhancing proxy that will obscure a users IP address from the site that is being previewed. A TLS session will be negotiated directly between the app and the previewed site through the proxy. This will ensure that the Signal service never has access to the URL. The Signal app uses overlapping range requests to retrieve preview images. This will help the proxy service to see repeated requests for a fixed block size when media is transferred. Link previews may also alert users to avoid clicking on links that may contain malicious content. Users have taken this news well, commending the team on this new feature: https://twitter.com/Roderik_de_Pree/status/1093329997882949632 https://twitter.com/bcomenl/status/1093270187208523776 You can head over to Signal’s official blog to know more about this news. Signal to roll out a new privacy feature in beta, that conceals sender’s identity! Messaging app Telegram’s updated Privacy Policy is an open challenge SafeMessage: An AI-based biometric authentication solution for messaging platforms

Matheus Eduardo Garbelini a member of the ASSET (Automated Systems SEcuriTy) Research Group at the Singapore University of Technology and Design released a proof of concept for three WiFi vulnerabilities in the Espressif IoT devices, ESP32/ESP8266. 3 WiFi vulnerabilities on the ESP32/8266 IoT device Zero PMK Installation (CVE-2019-12587) This WiFi vulnerability hijacks clients on version ESP32 and ESP8266 connected to enterprise networks. It allows an attacker to take control of the WiFi device EAP session by sending an EAP-Fail message in the final step during the connection between the device and the access point. The researcher discovered that both the IoT devices update their Pairwise Master Key (PMK) only when they receive an EAP-Success message. If the EAP-Fail message is received before the EAP-Success, the device skips to update the PMK received during a normal EAP exchange (EAP-PEAP, EAP-TTLS or EAP-TLS). During this time, the device normally accepts the EAPoL 4-Way handshake. Each time ESP32/ESP8266 starts, the PMK is initialized as zero, thus, if an EAP-Fail message is sent before the EAP-Success, the device uses a zero PMK. Thus allowing the attacker to hijack the connection between the AP and the device. ESP32/ESP8266 EAP client crash (CVE-2019-12586) This WiFi vulnerability is found in SDKs of ESP32 and ESP8266 and allows an attacker to precisely cause a crash in any ESP32/ESP8266 connected to an enterprise network. In combination with the zero PMK Installation vulnerability, it could increase the damages to any unpatched device. This vulnerability allows attackers in radio range to trigger a crash to any ESP device connected to an enterprise network. Espressif has fixed such a problem and committed patches for ESP32 SDK, however, the SDK and Arduino board support for ESP8266 is still unpatched. ESP8266 Beacon Frame Crash (CVE-2019-12588) In this WiFi vulnerability, CVE-2019-12588 the client 802.11 MAC implementation in Espressif ESP8266 NONOS SDK 3.0 and earlier does not correctly validate the RSN AuthKey suite list count in beacon frames, probe responses, and association responses. This allows attackers in radio range to cause a denial of service (crash) via a crafted message. Two situations in a malformed beacon frame can trigger two problems: When sending crafted 802.11 frames with the field Auth Key Management Suite Count (AKM) in RSN tag with size too large or incorrect, ESP8266 in station mode crashes. When sending crafted 802.11 frames with the field Pairwise Cipher Suite Count in RSN tag with size too large or incorrect, ESP8266 in station mode crashes. “The attacker sends a malformed beacon or probe response to an ESP8266 which is already connected to an access point. However, it was found that ESP8266 can crash even when there’s no connection to an AP, that is even when ESP8266 is just scanning for the AP,” the researcher says. A user on Hacker News writes, “Due to cheap price ($2—$5 depending on the model) and very low barrier to entry technically, these devices are both very popular as well as very widespread in those two categories. These chips are the first hits for searches such as "Arduino wifi module", "breadboard wifi", "IoT wifi module", and many, many more as they're the downright easiest way to add wifi to something that doesn't have it out of the box. I'm not sure how applicable these attack vectors are in the real world, but they affect a very large number of devices for sure.” To know more about this news in detail, read the Proof of Concept on GitHub. Other interesting news in IoT security Cisco Talos researchers disclose eight vulnerabilities in Google’s Nest Cam IQ indoor camera Microsoft reveals Russian hackers “Fancy Bear” are the culprit for IoT network breach in the U.S. Researchers reveal vulnerability that can bypass payment limits in contactless Visa card

With cybercrime on the rise, companies have started adopting the hard ways of preventing system breaches. Cybersecurity has become the need of the hour. This article will explore how cyberattacks bring companies down to their knees giving rise to cybersecurity. The article also looks at some of the cybersecurity strategies that an organization can adopt to safeguard itself from the prevalent attacks. Malware, Phishing, Ransomware, DDoS - these terms have become widespread today due to the increasing number of cyberattacks. The cyber threats that organizations face have grown steadily during the last few years and can disrupt even the most resilient organizations. 3 cyber attacks that shook the digital world 2011: Sony Who can forget the notorious Sony hack of April 2011? Sony’s PlayStation Network was hacked by a hacking group called “OurMine,” compromising the personal data of 77 million users. This cyberattack made Sony pay more than 15 million dollars in compensation to the people whose accounts were hacked. A hack made possible through a simple SQL inject could have been prevented using data encryption. Not long after this hack, in 2014, Sony Pictures was attacked through a malware by a hacker group called “Guardians of Peace” stealing more than 100 terabytes of confidential data. Sony had once again not paid heed to its security audit, which showed flaws in the firewall and several routers and servers resulting in the failure of infrastructure management and a monetary loss of 8 million dollars in compensation. 2013: 3 billion Yahoo accounts hacked Yahoo has been the target of the attackers thrice. During its takeover by Verizon, Yahoo disclosed that every one of Yahoo's 3 billion accounts had been hacked in 2013. However, one of the worst things about this attack was that it was discovered only in 2016, a whopping two years after the breach. 2017: WannaCry One of the most infamous ransomware of 2017, WannaCry spanned more than 150 countries targeting businesses running outdated Windows machines by leveraging some of the leaked NSA tools. The cyber attack that has been linked to North Korea hit thousands of targets, including public services and large corporations. The effects of WannaCry were so rampant that Microsoft, in an unusual move to curb the ransomware, released Windows patches for the systems it had stopped updating. On a somewhat unsurprising note, WannaCry owed its success to the use of outdated technologies (such as SMBv1) and improper maintaining their systems update for months, failing to protect themselves from the lurking attack. How cyber attacks damage businesses Cyberattacks are clearly bad for business. They lead to: Monetary loss Data loss Breach of confidential information Breach of trust Infrastructure damages Impending litigations and compensations Remediations Bad reputation Marketability This is why cybersecurity is so important - investing in it is smart from a business perspective as it could save you a lot of money in the long run. Emerging cybersecurity trends Tech journalist and analyst Art Wittmann once said "the idea that security starts and ends with the purchase of a prepackaged firewall is simply misguided". It's a valuable thing to remember when thinking about cybersecurity today. It's about more than just buying software; it's also about infrastructure design, culture and organizational practices. Cybersecurity is really a range of techniques and strategies designed to tackle different threats from a variety of sources. Gartner predicts that worldwide cybersecurity spending will climb to $96 billion in 2018. This rapid market growth is being driven by numerous emerging trends, including: Cloud computing Internet of things Machine learning Artificial Intelligence Biometrics and multi-factor authentication Remote access and BYOD--Bring your own device Effective cybersecurity strategies The most effective strategy to mitigate and minimize the effects of a cyberattack is to build a solid cybersecurity. Here are some of the ways in which an organization can strengthen their cybersecurity efforts: Understand the importance of security In the cyberage, you have to take the role of security seriously. You need to protect the organization with the help of a security team. When building a security team, you should take into accountthe types of risks that could affect the organization, how these risks will impact the business, and remedial measures in case of a breach Top notch security systems You cannot compromise on the quality of systems installed to secure your systems. Always remember what is at stake. Shoulda situation of attack arise, you need the best quality of security for your business. Implement a Red and Blue Team The organization must use the Red Team and Blue Team tactics, where the Red Team tactics can be used in penetration for accessing sensitive data, and the Blue Team tactics will defend your system from complex attacks. This team can be appointed internally or this job could be outsourced to the experts. Security audits Security audits are conducted with the aim of protect, detect, and respond. The security team must actively investigate their own security systems to make sure that everything is at par to defend against the lurking attack if it should occur. The security team must also be proactive with countermeasures to defend the organization walls against these malicious lurkers. Employees must also be properly educated to take proper precautions and act wisely in case of occurrence of a breach. Continuous monitoring Securing your organization against cyberattacks is a continuous process. It is not a one-time-only activity. The security team must be appointed to do regular audits of the security systems of the organizations. There should be a systematic and regular process, penetration testing must be conducted at regular intervals. The results of these tests must be looked at seriously to take mitigation steps to correct any weak or problematic systems. Enhance your security posture In an event of a breach, once the security team has confirmed the breach, they need to react quickly. However, don't start investigating without a plan. The compromised device should be located, its behavior should be analyzed and remedial actions should be underway. Vigilance In the words of the world’s most famous hacker, Kevin Mitnick, “Companies spend millions of dollars on firewalls, encryption,and secure access devices, and its money wasted; none of these measures address the weakest link in the security chain.” It cannot be stressed enough how important it is to be ever vigilant. The security team must stay current with the latest threat intelligence and always be on the lookout for the latest malicious programs that disrupt the organizations. Think ahead The question is never “if”, the real question is “when.”The attackers come sneaking when you are not looking. It is absolutely critical that organizations take a proactive stance to protect themselves by dropping the “if” attitude and adopting the “when” attitude. If you liked this post explore the book from which it was taken: Cybersecurity - Attack and Defense Strategies. Written by Yuri Diogenes and Erdal Ozkaya, Cybersecurity - Attack and Defense Strategiesuses a practical approach to the cybersecurity kill chain to explain the different phases of the attack, which includes the rationale behind each phase, followed by scenarios and examples that bring the theory into practice. Yuri Diogenes is a Senior Program Manager @ Microsoft C+E Security CxP Team and a professor at EC-Council University for their master's degree in cybersecurity program. Erdal Ozkaya is a doctor of philosophy in cybersecurity, works for Microsoft as a cybersecurity architect and security advisorand is also a part-time lecturer at Australian Charles Sturt University.