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While hackers don't differentiate between the size of their victims, certain attacks, like social engineering attacks, are most common in SMBs and SMEs. This blog specifically addresses the unique challenges and threats you may face as a small and medium-sized business or enterprise (SMB/SME) owner. Not for nothing, social engineering attacks are termed – unseen perils, silent threats to your small business and enterprise. Social Engineering Attacks: The Stats and The Reports Picture this: 📌 Per the report by Barracuda, small businesses witness 350% more social engineering attacks than larger enterprises. 📌 More than 30% of small businesses in the US have weak points that threat actors can exploit. 📌 Per the recent Verizon Data Breach Investigation Report, social engineering attacks, system intrusion, and privilege misuse incidents account for 92% of breaches in small businesses. It is essential to understand what a social engineering attack is and how it impacts your small business to understand how it affects you. What Is Social Engineering? As Cisco puts it, social engineering is not a cyberattack at its heart. It is the art of persuasion and human psychology. The modus operandi here is to target the minds of the victims like conmen and gain their trust. With the victims' trust gained, the attackers go in for the kill by encouraging them to 📍Divulge personal information 📍Click on malicious web links 📍Open malware-infected attachments So, what is Social Engineering? Let's look at the definition. Social Engineering: The Definition Any manipulation technique that exploits human errors to gain personal information, access, or valuables is a social engineering attack. In technical terms, social engineering is the psychological manipulation of people into divulging confidential information or performing unsafe actions. In layman's terms, social engineering is an assault on your emotions and feelings to extract sensitive and personal information for malicious purposes. In the world of cybercrime, scams related to human hacking are on the rise. These scams target unsuspecting users, playing tricks with their minds and luring them into revealing sensitive data and confidential information. Social engineering attacks can happen 👉 Online 👉 In-person 👉 Other interactions How Does Social Engineering Work? Social engineering works in four steps. But essentially, it works on your cognitive biases, where a threat actor impersonates either an authoritative person or a trustworthy individual and cons you into trusting them. They work in four steps. Preparation This is where a threat actor collects information about your business, and this may include your business emails, messaging apps, and other sensitive information related to your business. Infiltration This is where a bad actor will approach you or your employees. They usually imitate a reliable resource and use the previously gathered information to validate themselves. Exploitation Here, a threat actor will use persuasion tricks to obtain more sensitive information from your employees or even you. The threat actor plays on the human mind and tricks you into revealing some sensitive information. Disengagement Once an attacker has the information they sought, they will cut off all ties with you, deploy malware in your office network, and disappear in thin air. Why are SMBs and SMEs Prime Targets? Whether you have a small business or a small enterprise, you are at risk of social engineering attacks. Here are the prime reasons threat actors love your small business or your small enterprise. 📍Lack of resources is one of the primary reasons threat actors target your small business or small enterprise. 📍Trusting Culture of SMBs/SMEs is an important reason for threat actors to love small businesses and enterprises. 📍Your overworked and overburdened employees who juggle multiple responsibilities are the prime targets of threat actors. So, how do you counter these attacks on your business? Top Ways To Protect Your Small Business From Social Engineering Social Engineering attacks can be devastating for your small business, and your business may suffer: 📍Significant financial losses 📍Downtime 📍Reputational damage 📍Loss of Stakeholder and customers' trust You can counter social engineering attacks on your small business with these methods. 📌Train your employees to recognize 📍Phishing emails 📍Suspicious phone calls 📍Unsolicited requests for sensitive data 📌 Verify each email for sender addresses and the legitimacy of the data requests. 📌 Deploy two-factor authentication or multi-factor authentication on all your accounts for better security. 📌 Data encryption is your ally; embrace it with both hands. Encrypt your data at rest and in transition. When you follow these steps, you can ensure that your small business is protected from social engineering attacks. While you are at it, here are some common scams to watch out for. Common Scams to Watch Out For While practicing the four ways you can mitigate the threat of social engineering attacks, keeping an eye on some of the most common scams prevalent is essential. 📌 Phishing 📌 Tech Support Scams 📌 Pretexting 📌 Baiting 📌 Malware 📌 CEO Fraud Each of these scams is also an individual scam, but they can be deployed for sophisticated social engineering attacks. The best method to prevent social engineering attacks is to create awareness about the various tactics used by threat actors. Final Words Social engineering is becoming dangerous because attacks have become sophisticated with tech evolution. Threat actors indulging in social engineering are master con artists who know how to trick you into revealing sensitive information by invoking extreme emotions in you and your employees. So, the best way to protect your small business from social engineering is to educate your employees.

SINGAPORE, Singapore, May 7th, 2024/GamingWire/-- As the digital dawn of gaming rises, the visionary minds behind DECIMATED are ecstatic to unveil their groundbreaking foray into the desolate yet captivating future of online gaming. DECIMATED, a novel 3rd person PvP and PvE online game experience, invites players to an unprecedented journey through a vast dystopian landscape. Offering freedom for players to explore this post-apocalyptic playground, DECIMATED opens up a realm where players craft their own fate as human citizens struggling for survival or cyborg cops enforcing order in a world where nature and technology collide in chaos. https://youtu.be/18NLye2JA?si=5SBJktv0U4TV25MJ&embedable=true A New World Awaits: Immersive Gameplay and Unparalleled Adventure At the heart of DECIMATED lies a richly designed, immersive world that tests each player's survival instincts at every turn. Players engage in a relentless battle for existence against the apocalyptic aftermath, populated by mutated creatures, environmental hazards, and rival survivors. This rich narrative is further enhanced by offering players the opportunity to salvage advanced technology, uncover hidden treasures, and navigate the perils of a fractured society on the brink of rebirth. DECIMATED stands as a testament to survival, strategy, and resilience, offering a sandbox of endless possibilities. Whether patching up a battle-scarred vehicle, building impenetrable bases, to navigating the treacherous markets of this new world, players can embrace the lawless land, facing off against deranged robots, monstrous bio-entities, and other mutants, all while forging alliances or rivalries with other players to carve out a semblance of civilization amid chaos. Backed By 46 Investors And a Growing Community Decimated received an Epic Mega Grant and was backed by 46 investors in December 2021 after the studio was self-funded as an indie start-up for three years. Developers Fracture Labs were offered M from 180 investors and accepted .5M from VCs, including Mechanism Capital, Spartan Capital, Polygon Ventures, Good Games Guild, Israel Blockchain Association, Dutch Crypto Investors, and Metavest Capital, to name a few. Since then, the Decimated community has grown to 60k followers on Twitter and 23k members in Discord, many of whom are participating in the closed alpha testing. A Quest For Dominance In The Wasteland: The DIO Token Economic gameplay takes a revolutionary turn in DECIMATED with the DIO token, integrated into the game using the Solana chain and with interoperability between all of Fracture Labs' planned games. This creates a real-time digital economy within DECIMATED, incentivizing players for each and every decision made, as well as their efforts within the game itself. Every transaction, trade, and treasure found within this desolate world is valued in DIO, bridging the game to real-world economic principles and making the thrill of loot discovery and trading exponentially more engaging. The ways to earn in DECIMATED are as varied as the wasteland itself. Players can venture into the unknown, salvaging cargo and lost technology, engaging in both legal and illicit commerce to claim their fortune. Whether it's ambushing convoys for loot, undertaking dangerous missions, or trading valuable finds on the virtual market, success in the desolate landscape of DECIMATED demands wit, bravery, and a keen sense of strategy. Decimated features a leaderboard system that rewards the best-performing players, whether they play solo, in guilds, or in clans. In a recent announcement, DECIMATED confirmed its official sponsorship of Token2049 Dubai, underscoring its commitment to innovation, blockchain technology, and the burgeoning digital economy, demonstrating its potential for the future from the lens of immersive gaming. This sponsorship accentuates DECIMATED's commitment to forging a future where gaming transcends mere entertainment to become a cornerstone of digital economies in virtual worlds, allowing players to earn real rewards through tournaments. The community buzzed with excitement for DECIMATED listing on the Epic Games Store in May 2024. While the official launch date is yet to be announced, the open alpha is pegged for the end of 2024, and the eagerness around this launch grows daily as players and fans are encouraged to keep an eye out for what hopes to be a landmark announcement in online gaming history. About DECIMATED DECIMATED is the future of immersive online gaming, offering a dynamic 3rd person PvP and PvE experience within a richly detailed post-apocalyptic world. With its unique digital economy and endless opportunities for exploration, combat, and alliance, DECIMATED invites players to define their legacy in a world where every decision can mean the difference between survival and extinction. For media inquiries or further information, please visit https://www.decimated.net Contact Stephen Arnold Fracture Labs PTE Ltd contact@decimated.net +35699554901 :::tip This story was distributed as a release by Gamingwire under HackerNoon's Business Blogging Program. Learn more about the program here. :::

DECIMATED Game DECIMATED SINGAPORE Store SINGAPORE

A time is coming when your thoughts will be the only activity you need to get things done. Have you ever been so caught up with work, you don't want to move a muscle? You are not willing to use your voice because you feel the ideas will escape once you do. So, what do you do when you suddenly wish your favorite songs were playing at that moment, but you feel too lazy to pick up your phone or call Siri's attention to turn on your playlist? If only your thoughts could make the orders, right? Here, you are thinking, "Siri, play me 'Easy on Me' by Adele" and seconds later the sound fills your workspace. Then you think, "Nope, too low. Siri, increase the volume to 10", and the volume gets adjusted to suit what's on your mind perfectly. Your brain alone processes commands without any effort from your mouth. I guess that can be seen as a grand breakthrough in the history of neuroscience—or probably not! Let's find out what this means for the world collectively. What Exactly is Neurocomputing? Neurocomputing is a branch of neuroscience that deals with the examination of brain patterns and activities. It is a subfield of cognitive neuroscience that scientifically studies the biological mechanisms and reactions of the brain to different experiences. The term applies to the process of reading, analyzing, and interpreting brain activities by utilizing brain sensors and an imaging framework to examine how our brain reacts in response to different emotions. This is usually through the use of a Brain-Computer Interface Device. The framework, in this case, is called the "triad,” a 3-step process of emotion-valuation, sensory-motor, and meaning-knowledge evaluation. With the introduction of Al, neuroscientists hit a new milestone with brain activity studies. n The Rise of Neurocomputing Would you have ever imagined that one day, the content of your thoughts could be read by devices? Science fiction? Sure! Why not? We see a lot of that. But reality? That's almost impossible (or so we thought). Lie detectors were the most mind readers, but they can never detect what your thoughts are word by word. However, technology always seems to awe us as time progresses because the technology we once thought only existed in movies is right here! The use of brainwave-controlled devices to read minds began with the invention of Electro Encephalogram (EEG) in the 1900s. History has it that the German psychiatrist, Hans Berger, created the first EEG brain recording in neurosurgery. These devices, fitted with sensors, were used mostly to monitor and record a patient's brain activity. When placed on your scalp, the sensors pick up electrical signals produced by the brain, which can be interpreted. Around 2008, consumer-focused EEG became commercialized for public use. NeuroSky and Emotive—both tech companies—were among the early players in this scene as they released EEG headsets with the promise to create mind-controlled video games. Furthermore, it began being tested in other areas besides video games, like how it could be used to control your phone or other activities by companies like iBrain and Muse. Relief from Brain-Computer Interfaces Technology Innovations and advanced companies like Meta and Neuralink notched it up with their research into Brain-Computer Interfaces (BCIs) - a technology that can pick thoughts directly from brain neurons and translate them into words. This technology uses AI algorithms to read brain activity and decode emotions into words. Between 2017 and 2019, Meta began funding research into this technology. As of March 2022, the funded Nature Neuroscience, UCSF researchers achieved brain-to-text decoding with an average error rate as low as 3% when it was tested with vocabularies of up to 300 words—a huge advancement from previous studies. At the same time, Elon Musk's Neuralink is already making a good deal of progress with its flexible ultra-thin threads that can be implanted directly into the brain, enabling the carrier to control their gadgets/devices with their thoughts. This is already being tested on paraplegics. The technology has been very much welcomed by paralytic patients who need to gain a good level of control over their lives again. Neuralink has already begun testing the brain threads on paraplegics. n Case Study of Neurocomputing Although this technological concept sounds somewhat new, neurocomputing has been in the research and development stage for years, and test-flight gadgets are already being produced. The possibilities of mind reading and brainwave-controlled gadgets are endless. Scientists continue to look into ways to integrate them into our lives, experimenting across various sectors with the possible use of non-invasive EEG devices and BCIs. Many of these experiments are often procedures aimed at helping the physically and mentally disabled to communicate their needs and gain some control over their lives. Breakthrough at the GrapheneX-UTS Human-centric Artificial Intelligence Centre: The world is not new to cases of patients who can not speak due to sicknesses, paralysis, stroke, or just being born that way. So when, for the first time in history, researchers at the GrapheneX-UTS Human-centric Artificial Intelligence Centre, University of Technology Sydney, invented a portable non-invasive device that could translate thoughts into words, it was seen as a breakthrough in neurocomputing. At the time, though, the accuracy was questionable, but with the initial goal achieved, it would only take more years of developing it to increase its accuracy rating. We already find Meta and Neuralink taking up this task with BCIs and electron threads. Evolving neurocomputing also makes smooth communication possible between humans and machines, be it our gadgets, robots, or prosthetic arms. The FIFA 2014 World Cup Kick-Off Event: The history of neurocomputing and brain-controlled devices left a remarkable mark in the FIFA 2014 World Cup when, for the first time, the symbolic kick-off event for the tournament was led and completed by a paraplegic man using an advanced assisted mobility technology—a brain-controlled exoskeleton. This technology, by The Walk Again Project, a collaborative invention of over 100 scientists from around the world, made use of a set of non-invasive electrodes to read the brain signals from the paraplegic and transmit them to the lightweight exoskeleton triggering movements that helped the man complete the kick-off successfully. Paralyzed Ian Burkhart Regained Mobility: In the same year of the FIFA World Cup kick-off event, the director of the Center for Neuromodulation, Ohio State University, Dr. Ali Rezai, performed a life-changing surgery on 26-year-old quadriplegic Ian Burkhart. The surgery involved implanting a tiny 4 x 4 mm microchip into Burkhart's motor cortex, used alongside an electrical sleeve and purpose-made algorithms. This allowed the sensors to trigger his thoughts to control his hands and fingers while bypassing his damaged spinal cord. It was a success. This is not the only successful brain implant in the history of neurocomputing; a man paralyzed from the shoulders down has also been able to regain control of his paralyzed muscles by bypassing the injured spinal cord with the implantation of two aspirin-sized 96-channel electrode arrays into his motor cortex. Other Notable Strides: EEG devices and BCIs are greatly contributing to improved quality of life for disabled people. But we can't say that brain-controlled and mind-reading devices are only for the sick and disabled. These devices could also be used to carry out other tasks/activities for the good of everyone: BBC and This Place teamed up to create a mind-reading headset to enable its user to control the BBC iPlayer with their thoughts—goodbye to remote controls. A team led by an Associate Professor at the KU-KIST Graduate School of Converging Science and Technology, Korea University, Suk-Won Hwang, developed E-Glasses. This prototype eyeglass is made up of flexible electrode sensors located between the ears and eyes of the wearer. First, the electrodes consist of an EEG to monitor the brain's electrical activity and an ElectroOculogram (EOG) to track eye movements and transmit both from the glasses to a device for processing and interpretation. This glass can be used to monitor the mental health of the wearer, help them control games with their eyes, and turn on and off the sunglasses mode when the wearer needs it. Nissan and NASA are working together to build a self-driving robot car technology called Mind Sense that can read, monitor, and measure a driver's brain activity to know if he/she is alert to drive or not. In an exciting twist of things, in 2013, NASA came up with the crazy idea of using BCIs to control planetary rovers. Together with scientists from the University of Essex, they launched a project to control a virtual spaceship with the mind. A Brain Drone Race competition was held in 2016 by neuroscientists at the University of Florida, a competition that had pilot flying their drones to the finish line by using their minds. And the list goes on and on. But like every other technology and thing that exists, there will always be pros and cons to consider. The Ethical Considerations of Neurocomputing Neurocomputing is a technology that is already transforming lives, especially for paraplegics, who, in many cases, have been able to get robotic body parts that can be controlled with their minds or bypass spinal cord injuries to stimulate their bodies into motion through brain neuron implants. People who couldn't talk can now communicate their feelings and what they want/need and interact through mind-reading gadgets. For everyone else abled people, organizations, and companies that wish to apply these gadgets in their daily lives or their various sectors, it is very much achievable. It can bring "ease" into certain activities and, perhaps, create a more quiet world. However, the implantation of invasive BCIs into the brain involves a surgical procedure that is almost too risky to be considered. The brain is a fragile organ; damage to it can lead to mental abnormalities or even brain death. As such, the risk of brain implants makes this technology far-fetched for fully functional humans. Paraplegics, on the other hand, can wager these procedures because of the quest to have a better quality of life. A delicate situation, but if that is what it takes for them not to be stuck in a static world at the mercy of others, it is worth the risky shot. This is why BCIs by companies like Neuralink and Meta, although envisioned to cater to all and sundry, are more appealing to the paralytic section of the world at the moment. Because of these concerns, scientists are looking back into non-invasive methods of mind reading. Last year, researchers at the GrapheneX-UTS Human-centric Artificial Intelligence Centre, University of Technology Sydney, invented a portable, non-invasive cap-like device that could translate thoughts into words when placed on the head. Additionally, scientists from the University of Texas, Austin, developed a non-invasive technique to translate the thoughts in one's brain into actual speech by monitoring the brain's activity involving the use of fMRI and Al language models. The accuracy of these techniques was average. However, with the intended goal achieved, it would only take more years of development to increase its accuracy. Still, no one wants to walk around carrying a headpiece with cords sticking out, and neither can they carry fMRI machines all day. Hence, there is a need for less obvious, non-intrusive devices or less risky invasive BCIs. While the world can be swamped by Brainwave-controlled devices that read our minds, it poses serious concerns. One day, like every other day, we'll be carrying out activities with silent thoughts all in our heads, but this is the sad part: organizations would be able to read, monitor, store, access, and use these thoughts when needed. As tragic as this sounds, it is already in progress. Data Privacy: The thoughts in our brain are currently our only inaccessible assets, our privacy safe, our most intimate thoughts, and our personal identity—no one should be able to access our minds. But with the recent discoveries and technologies in neuroscience, this intrinsic privacy may be breached sooner than we know, leaving us truly vulnerable to Big Tech companies and organizations. If we lose control of our minds, if any company can spy into our thoughts, what else do we have left of ourselves? Just like we have on the internet, companies would be able to buy and access our brain data for targeted marketing. The first appeal for every product starts with the brain. You may not be able to say it, but you can think it accurately. Imagine advertisers having that exact information just as we feel it; then, they will be able to market their products in a practically irresistible way. Neurocomputing and mind-reading devices would make brain data available on a massive scale, and this is also very detrimental to us. Think about it; aside from compelling advertising, how safe are you? The brain is where all your secrets lie: your passwords, location, investments, amount of money you own, where you saved your assets, etc. A brain data hack would mean a loss too great to bear. The argument of some neuroscientists that the potential for misuse of neurocomputing and mind reading is so great that there needs to be a revamp of the human rights laws to protect us all is valid. Because this technology has what it takes to interfere with our most basic rights, the current laws are not fully equipped to salvage the situation; we need a new "jurisprudence of the mind" for our protection. So, in all, our biggest challenge is privacy and safety! n What's the future? A quiet world. Maybe what we need? Or maybe not. Elon Musk and his company, Neuralink, have been at the forefront, pushing the concept of neurocomputing beyond the idea of it being the help for paraplegics only. For Musk, it would take conceptual interactions to a whole new level where words and conversations don't have to be verbalized, just thought. He calls it "consensual telepathy,” a realm where your speech becomes completely unnecessary. You can walk into a room with people conversing but not conversing because their thoughts are flying invisibly between them. Reading that now, it does sound uncanny. What becomes of our speech? Oh! I know what you are thinking, "there would never be a day when our speech isn't needed,” and of course, that's somewhat true. But come to think of it, before the advent of mobile phones, would there have been a day we thought we'd be so glued to these gadgets we'd rarely appreciate physical communication and rather be embedded in virtual conversations? I don't think so. When all you need is your thoughts to perform the most basic activities like ordering a coffee from a cafe, asking your friend to pass you the popcorn at a movie, communicating a proposal to your boss, conversing verbally on a date, etc., you may slowly lose touch of actual words. Almost the same way, we are slowly losing touch with writing on paper because we'd rather type into our computers, tablets, or phones. Well, there's no denying the fact that it sounds pretty interesting, too. You'd never have to say you don't know how to express yourself because your mind will do all the expressing for you where words would have escaped you. The concept of your feelings will flow just as you feel them, and no matter how disgruntled they are, your receiver will get the exact message with the fear, excitement, contempt, and all the fleeting emotions - conveyed just as it is. Also, the advancement of this technology would eliminate the language barrier. Whatever we think can be communicated directly to the recipient in whatever language desired. What neurocomputing proposes for the future is both unsettling and intriguing, but we really can't stop technology from evolving, and neither can we stop the future. We only hope that measures are instituted to mitigate the cons while we hope for the best. n

brain activity Neurocomputing

For instance, from this graph, we can conclude that given the same time to complete the test, older users typically perform slightly better than their younger counterparts. This can be attributed to differences in visual experience and color perception needs across various age groups. You're invited to participate in the study by using the Dehancer Color Test. The second part of this series will focus on the algorithm used to calculate the number of colors based on the data we have gathered.

Dehancer Color Human Eye typically perform users typically

Microsoft just released a preview of their new AI model called VASA-1, which animates any photo into a “talking face avatar.” It takes a few seconds for our eyes and brain to adjust to this reality, but then the immediate question arises: what are these new avatars supposed to say? Will this new AI milestone be wasted on lip dubs and creating even more fictional Manga-Anime? What if you could create an AI version of yourself by combining VASA-1 with your own AI to have an official AI that represents you online and is legitimate enough to speak for you? The future we all knew was coming. It was inevitable that large tech companies like Microsoft and Google would develop models to animate pictures and make them “talk.” They have been working on Image Processing, Facial Recognition, Image reconstruction and Classifiers for years. They have the talent and the research to master the processing of visual and audio data… So you can expect more announcements on these two fronts very soon. With their significant investment in AI research and in the Metaverse (let's not forget the hundreds of millions poured into it), animating images was destined to happen. It's no surprise that these tech giants are now leading the charge in transforming static visuals into dynamic, talking heads. Create the perfect AI version of you with your brain and your talking image! Microsoft will not make VASA-1 public because of the ethical risks of creating an infinite amount of deep fakes and misrepresenting people too easily. So, the “talking image” feature will not be available in the near future, but you can absolutely create your own AI version. Using Spheria to create the AI version of yourself, you can grow your own AI double that learns directly from you, giving you real answers and speaking in your name. The goal is to one day combine your own AI double with a realistic and animated 3D shell — powered by VASA-1 or another image model. This would really create the futuristic society we've seen many times in sci-fi movies. You would then have a real official AI version of yourself to represent you online and give your real answers based on your personal experience and opinions. The problem with Avatars and VASA-1 Many companies like NVIDIA, Unreal, and Microsoft focus on creating a 3D rendering of real people or 3D avatars using various technologies like Unreal Engine or VASA-1. But the result is always the same: an impressive empty shell. What's the real-life use of a Mona Lisa that can rap? Why would Napoleon suddenly say things that the real Napoleon would never say? 3D avatars and “talking images” are doomed to become empty shells. And these companies, including Microsoft, have no interest in creating convincing fictional characters — it's too much effort and extremely difficult. 3D avatars gain all their value when they have a distinct personality and when they can deliver meaningful information that is not generic — i.e., information not already available on chatGPT or Wikipedia. As humans, we immediately differentiate how we choose to interact with generic AI entities or with real people. The line is set by having a personality and an individuality. So, while VASA-1 evolves, and while 3D avatars become mainstream, you can learn how to easily create the AI version of yourself that captures your unique thoughts and individuality… to connect it in the future with the 3D avatar of your choice.

Photo by Headway on UnsplashMalicious Domain Detection Using Machine LearningFriend or Foe?Spam detection, a classic example of machine learning (ML) applied to cyber security, has been around for many years. The way it works can be understood intuitively based upon how we as humans distinguish spam from non-spam (‘ham') emails. Namely, if an email is littered with spelling mistakes, excessive exclamation points, is out-of-character for the alleged sender, is making an offer that's too good to be true, or is asking for personal information, it raises red flags. ML models work in a similar way, teasing out such features when presented with a training dataset made-up of spam and ham emails.However, something like a web address presents a very different challenge. Afterall, something like www.royal-mail-customer.com only contains a small amount of information, and yet the detection of a malicious domain (‘royal-mail-customer.com' in the above example) is equally as important as spam detection. Phishing emails, for example, are the source of the majority of cyber attacks around the world¹. If they make it past a phishing detector, the target will often be encouraged to click on a malicious web address, leading to data theft, malware distribution, etc.In the past, the approach taken for such a challenge was to build and maintain huge lists of untrustworthy domains and corresponding Internet Protocol (IP) addresses. As a side note, it's the Domain Name Service (DNS) that connects these two items. For example, the domain google.com is associated with the IP address of 142.251.46.174. This system is essential for bridging the gap between a human's preferred information (words) and that of a computer's (numbers).Returning to our compiled lists, if such a domain or IP address appears in an email, or a user tries to browse to such an address manually, the connection will be blocked using the appropriate software. However, this clearly offers no protection on new, malicious domains. Given the huge number of new registrations each year², a large chunk of which are malicious, this is clearly an issue.To go beyond lists, an ML approach is presented in a paper by Marques et al³, the logic and performance of which we'll explore below.Below the IcebergDomain names actually possess far more information that first meets the eye. For example, there is meta-data in the form of DNS usage logs that can shed light on the veracity of a domain. Such logs, however, take time to build.In terms of more immediate pieces of information, there are aspects such as the entropy or randomness of a domain name. This can provide some predictive power to an ML algorithm, where a higher level of randomness in a domain name can be indicative of a malicious address. Other attributes intrinsic to the name itself include the number of special characters, the number of vowels, consonants, and numeric characters, the number of consecutive numeric characters, and the overall length of the name.Going further, the use of Open-source intelligence (OSINT) sources can enrich such meta-data collections further, adding attributes such as,WHOIS information (domain owner, domain registrar, registration date, etc.)Whether a domain has a Sender Policy Framework (SPF) attribute (an email authentication method, as are the next two)Whether a domain has a Domain Keys Identified Email (DKIM) attributeWhether a domain has Domain-Based Message Authentication (DMARC)The domain's country codeetc.ML Training & PerformanceOnce such information was collected (automatically via a Python script) the authors cleaned, scaled and normalised the data. They then used methods such as the Extra Trees Classifier algorithm to assess the importance of each feature, allowing those with the lowest importance to be removed, in order to avoid overfitting.Next, a range of ML algorithms were used to fit the data, including Support Vector Machines (SVM), Logistic Regression (LR), Linear Discriminant Analysis (LDA), K-nearest neighbours (KNN), Classification And Regression Trees (CART) and Naïve Bayes (NB). Training and testing subsets of the data were used, along with 10-fold cross validation. Finally, metrics such as Precision and Recall for each algorithm were calculated, with the highest values from the different approaches being 0.96 and 0.94, respectively (using CART).In summary, they were able to successfully create an ML model based upon the associated features with an excellent classification performance.Building a Simple ModelThe authors have made the data⁴ and code⁵ available for general use. Below we'll create a simple Random Forest (RF) model in Python to follow the logic of the paper. The code I used is also available⁶Initially, I explored the data to get a feel for the various attributes. As an example, below is a plot of the distribution of record types (from a total of 90k), showing A, CNAME, and MX records,Next, I performed the basics of data preparation, such as creating dummy variables for categorical features and splitting the data into a train and test set (80%/20%). Then, I trained an RF model using scikit-learn and made predictions on the test set. The performance was good and the training time was short (less than 10s).From this model, I decided to check the top 20 features that the model had used. These are shown below,From this, you can see that there is a mix of intrinsic features, such as domain length, and external features, such as ‘Has SPF info'. I wondered if a classifier could be trained, with reasonable performance, from just a handful of intrinsic features. I therefore limited the training data to just 4 attributes (with their descriptions from the paper in brackets);StrangeCharacters (“The number of characters different from [a-zA-Z] and considering the existence maximum of two numeric integer values”)NumericSequence (“The maximum number of consecutive numbers in the domain”)NumericRatio (“The ratio of numeric characters in the domain (numeric_chars/len(domain)”)DomainLength (“The length of the domain”)Looking at the data, all four of these are on average higher with malicious domains compared to benign ones. For example, below is a boxplot for domain length, grouped by class (0 = benign, 1 = malicious). We can see that the median value is higher for the malicious cases, and that the malicious class has many more extreme domain lengths of >100 characters,I then retrained the model and checked the performance. The headline metrics were,Accuracy: 0.945Precision: 0.912Recall: 0.985F1: 0.947And the corresponding confusion matrix,Finally, below is the tree model itself,Predicting New CasesThe advantage of only using intrinsic attributes is we can easily calculate them and make predictions on new cases. Using code to work out the x4 attributes mentioned above, they can then be used with the model. Below are some examples and the corresponding output,The model predicted that google.com is benign (probability 0.998)The model predicted that g00gle!.com is malicious (probability 0.731)The model predicted that microsoft.com is benign (probability 0.998)The model predicted that micro_soft1#.com is malicious (probability 0.731)The model predicted that clickthislink!123456.com is malicious (probability 0.808)Looking at the attributes for these, we can easily follow the decision tree to see how it's classifying each case. For example, for google.com, we have the following;StrangeCharacters: 0NumericSequence: 0NumericRatio: 0.0DomainLength: 10The first node in the tree asks if ‘NumericSequence' is ≤0.5, which in this case it is, which classes it as benign. However, for clickthislink!123456.com, we have the following;StrangeCharacters: 5NumericSequence: 6NumericRatio: 0.25DomainLength: 24The first node in the tree asks if ‘NumericSequence' is ≤0.5, which in this case it isn't. Next it asks if ‘NumericRatio' is ≤ 0.25, which it is, then if ‘StrangeCharacters' ≤ 4.5, which it isn't, leading to a classification of malicious.ConclusionThe concept of using DNS information to create an alternative type of firewall is a useful tool in the ongoing battle against cyber attacks. Here, using the publicly available data from the ‘DNS firewall' paper, we've seen how a handful of those attributes can be used to classify example domains into benign and malicious categories. It's easy to imagine such a model with added data and sophistication, and then deployed for real-time use, as described by the authors of the paper.ReferencesCybersecurity & Infrastructure Security Agency Stop Ransomware campaignVast majority of newly registered domains are maliciousMarques, C., Malta, S. and Magalhães, J., 2021. DNS firewall based on machine learning. Future Internet, 13(12), p.309.Marques, Claudio (2021), “Benign and malicious domains based on DNS logs”, Mendeley Data, V5, doi: 10.17632/623sshkdrz.5Claudioti/Machine-Learning. Available online: https://github.com/claudioti/machine-learningCode for the blog post DNS Firewall Blog Code (github.com)Malicious Domain Detection using Machine Learning was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

Domain Detection

Giving feedback to your manager can be tricky. What if they don't like what you say? What if they take it the wrong way? What if they turn against you? People refuse to give candid feedback to their managers because they don't want to put their jobs at risk. This prevents most managers from getting an accurate picture of how others view them, often creating a huge gap between perception and reality. When you don't share what they need to hear, don't expect your manager to improve or blame them for repeating behaviors and actions that hurt their team and impact your productivity and performance. Just like your manager is expected to share constant feedback to help you learn and grow, you also need to contribute to your manager's growth. All managers have blind spots—unknowns that are in their circle of awareness (known unknowns) and things they don't even know (unknown unknowns). There are lurking gaps in how they see themselves (or their actions) and how others perceive them leading to inadvertent blind spots. This is further exacerbated by their past beliefs, experiences, upbringing and many other psychological factors. Without reconciling reality, these blind spots perpetuate disconnect and dissonance with people. It may be uncomfortable at first to tell your manager what they're doing wrong—you've to fight your fears and resist your instinct to avoid dealing with them. But with practice and experience, you'll get better at it. Your courage will inspire others to do it too, contributing to a healthy workplace with a feedback rich environment. When you give yourself permission to communicate what matters to you in every situation you will have peace despite rejection or disapproval. Putting a voice to your soul helps you to let go of the negative energy of fear and regret. — Shannon L. Alder Help your managers become better leaders by giving them the feedback they need. Follow these practices to ensure your feedback lands right: Check whether they're receptive to feedback Giving feedback to your manager is risky, no doubt. That's why you shouldn't do it without gauging whether they're receptive to it. Toxic managers will not react poorly to your feedback; they will hold it against you. These managers believe in power structures where feedback is expected to flow only in one direction—from top to bottom. They take feedback personally as it hurts their ego and question their place in the hierarchy. They are blind to their flaws and refuse to address them. Instead of treating feedback as a gift, they treat it as a slap in the face. To determine if your manager is open to feedback, start with a low-stakes situation and identify how they react to it. Share your feedback on a very small matter—do they show curiosity to learn more about the feedback, or do they shut you down? How do they behave afterward—show resentment or appreciate you? Starting small also makes it easier when you have some critical feedback to share. Once you've built trust and relationships with the manager by sharing small improvement areas, they will be more open-minded when you have something big or bold to say. Don't waste your time and energy on a manager who treats feedback as a one-way street. It's time to change teams or find another job if they aren't receptive to feedback and their behavior is getting in the way of your growth. State your intentions When you don't state your intentions explicitly, others are bound to create a story around it—that's just how the human mind works. Intentions are invisible. We assume them from other people's behavior. In other words, we make them up, we invent them. But our invented stories about other people's intentions are accurate much less often than we think. — Douglas Stone Intentions play a big role in how your feedback is received. When you are judgmental and opinionated, when you argue and attack their story, when you tell them how to do their job, your manager is more likely to get defensive than to explore your point of view. When you show up with the intent to ask questions, make suggestions, raise concerns, challenge ideas, and find better ways to work together, or help them improve, they are more likely to take your feedback positively and may even decide to act on it. Don't let your manager play a guessing game—clearly state your intention. For example, you may say: My intent is to find better ways to communicate so that we can avoid communication gaps. *My intent is to find the best possible solution. I want to discuss how we can encourage more disagreements in the team.* My intent is to get more visibility around my work. Can we discuss how you can enable this for me as a manager? Explicitly stating what you desire from the conversation and why you're approaching them prevents them from attaching their own meaning. They can focus on the solution when they know you have their best intentions at heart. Frame it right Your manager has hundreds of things to do, most of which are not visible to you. It's very important for you to realize that you may not have all the context to understand why your manager behaved a certain way in a particular situation unless you're actually doing your manager's job. So, instead of judgment, lead with observation. Leave room for understanding and curiosity. Don't draw conclusions from your limited interactions with your manager, and treat them as a source of truth. How you frame the feedback determines the reaction and response you get. Framing that involves blame, complaining, or a judgmental tone can never get you the outcomes you desire. If you want your feedback to be received well, frame it right—describe the situation followed by your observation (without judgment and opinion), then state the impact as you see it with an open-ended question to get their perspective. Talking about the impact their behavior has on others and how it prevents them from achieving their goals makes it much easier to understand. Ending with an open-ended question invites them to share how they view the situation or what they can do to help. Right framing = Situation + Observation + Impact + Open-Ended Question For example: Instead of: You don't care about our ideas. Say: In our meeting yesterday, you asked the team for their input (situation). However, I noticed that whenever someone shared their viewpoint that didn't align with the original idea, you dismissed their suggestion without exploring it completely (observation). Rejecting ideas this way makes the team feel that their opinions don't matter. They will be demotivated to speak up next time around (impact). How do you suggest we encourage healthy disagreements in the team while aligning on the goal of finding the best possible solution (open-ended question)? Instead of: You don't trust us with more responsibilities. Say: I wanted to discuss work allocation and responsibilities in the team (situation). I have noticed that you always have too many things to do in a day. At the same time, the team feels more than ready to take on additional responsibilities (observation). Not getting an opportunity to handle next-level responsibilities is preventing the team from growing while doing all that work by yourself, leaving you tired and exhausted (impact). What do you suggest we can do to gain your trust so that you can delegate more work to the team (open-ended question)? Here are a few do's and don'ts of framing it right: Don't tell them how to do their job. Don't generalize or attack their character. Focus on a specific behavior or action. Don't be opinionated or fixated on a single point of view. Show flexibility when changing your point of view. Don't presume you have complete visibility into their situation. Be respectful and polite. Seek their input or advice. It makes them invested in the problem. Embrace silence. Give them time to chew on the information. Framing your solution negatively, such as “Don't shout at me,” tends to focus the other's attention even more on the unwanted behavior and may unconsciously reinforce it, particularly if you are shouting back at them. It is more effective to say, quietly, “Please talk to me in a quiet tone.” Focus the other's mind clearly on the positive action you want them to take. — William Ury When giving feedback to your manager, take time to decide what you're going to say. Without thinking about it upfront, you may say things that you regret later. Do it in person When giving feedback, what you convey through your eyes, hand gestures, and body language matters as much as what you say in words. These non-verbal cues play a significant role in determining how your feedback is understood and received. While giving feedback to your manager, it may be easy to drop an email or message or do it over a phone call. But your chances of being misunderstood or not delivering feedback effectively go higher when you avoid meeting them in person. When giving feedback, it's very important for both the feedback giver and the receiver to observe the body language. Carrying yourself in a powerful way directs your feelings, thoughts, behaviors, and body to feel powerful and be present (and even perform better) in situations ranging from the mundane to the most challenging. — Amy Cuddy Your positive body language can speak a lot about your intention and can guide the conversation in a positive direction. Your manager's body language can serve as a hint on how they're processing the information and give you useful signals on whether to continue speaking or keep your mouth shut. When giving feedback to your manager, always do it face-to-face. Tune your body to send out positive vibes—open, honest and self-assured—and not exude a negative body language—closed or judgmental. With a casual and respectful tone, your manager will be more likely to take your feedback constructively instead of feeling misunderstood, offended or disrespected. Respect is like air. As long as it's present, nobody thinks about it. But if you take it away, it's all that people can think about. The instant people perceive disrespect in a conversation, the interaction is no longer about the original purpose—it is now about defending dignity. — Ron McMillan Summary Your manager is not perfect. They, too, have gaps, much like everyone else. Don't avoid giving them feedback just because it's uncomfortable and risky. Not all managers are receptive to feedback. Some might hold it against you. Start with a low stake situation, share feedback with your manager and gauge their reaction. Your intentions play a significant role in how your feedback is perceived. Don't leave your manager guessing or attach meaning to your words. Clearly state your intention. Right framing of the feedback can get your managers attention and invite them to problem solve instead of turning defensive. Always give feedback to your manager face-to-face. Don't ignore the power of your body language—what you convey through non-verbal cues matters as much as what you say in words. Also published here.

HTB Cyber Apocalypse CTF 2024 — ReversingWrite-ups for HTB Cyber Apocalypse 2024 CTF Reverse Engineering challengesReversing challenges🏠 HTB Cyber Apocalypse CTF 2024 Write-upsChallenges· LootStash· BoxCutter· PackedAway· ConclusionLootStashA giant stash of powerful weapons and gear have been dropped into the arena — but there's one item you have in mind. Can you filter through the stack to get to the one thing you really need?💡SolutionWe begin by extracting the ZIP archive provided by the challenge, which presents us with a file that looks like a binary. Let's verify that before we proceed.$ file stashstash: ELF 64-bit LSB pie executable, x86-64, version 1 (SYSV), dynamically linked, interpreter /lib64/ld-linux-x86-64.so.2, BuildID[sha1]=817b1311ae44bdc6ed8a9b563159616844e59c64, for GNU/Linux 3.2.0, not strippedELF stands for Executable and Linkable Format, a type of executable file format commonly found in Unix-like operating systems. It is a standard file format for executables, object code, shared libraries, and core dumps.When approaching reverse engineering challenges, it's common practice to start with simpler checks and analyses before diving into more advanced tools like debuggers, decompilers, and disassemblers.Simple checks may include examining file headers and running basic command-line tools like file, strings, or hexdump to gather initial information about the binary, identifying any strings or clues embedded in the binary, and running the binary to observe its behavior.Let's try strings on our executable binary to search for any text or strings that may contain a flag:$ strings stash| grep -i "htb"Draughtbane, Bond of HateLightbane, Crusader of Trembling HandsHTB{n33dl3_1n_a_l00t_stack}Draughtbane, Fan of PerditionI used the strings command on the binary file stash to extract printable strings. Then, I searched using grepfor the case-insensitive (-i)string “htb” to find any potential flag formats among the extracted strings.Bingo! Easy day in the office :)Flag: HTB{n33dl3_1n_a_l00t_stack}BoxCutterYou've received a supply of valuable food and medicine from a generous sponsor. There's just one problem — the box is made of solid steel! Luckily, there's a dumb automated defense robot which you may be able to trick into opening the box for you — it's programmed to only attack things with the correct label.💡SolutionAgain, we kick off by extracting the ZIP archive provided by the challenge, which contains a file that resembles a binary. Let's double-check its file type:$ file cutter cutter: ELF 64-bit LSB pie executable, x86-64, version 1 (SYSV), dynamically linked, interpreter /lib64/ld-linux-x86-64.so.2, BuildID[sha1]=f76eb244685ad0c3b817caa99093531754fc84c8, for GNU/Linux 3.2.0, not strippedWe have indeed a 64-bit Unix binary. We proceed with running the basic checks such as strings and hexdump.$ strings cutter | grep -i htb$ hexdump cutter| grep -i htbThis yielded nothing. Right, before we roll up our sleeves and run a debugger, let's re-read the challenge description for more clues.In the given challenge, words like “automated defense robot” and “correct label” may hint at the need to analyze the program's behavior, making stracea valuable tool for understanding its actions.“strace” is a debugging tool used to monitor system calls and signals. In CTF challenges, it can help uncover hidden functionality or reveal clues by tracing the execution of a program.$ strace ./cutter execve("./cutter", ["./cutter"], 0x7ffec8610920 /* 55 vars */) = 0brk(NULL) = 0x55dd45444000mmap(NULL, 8192, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7f3cf4a37000access("/etc/ld.so.preload", R_OK) = -1 ENOENT (No such file or directory)openat(AT_FDCWD, "/etc/ld.so.cache", O_RDONLY|O_CLOEXEC) = 3newfstatat(3, "", {st_mode=S_IFREG|0644, st_size=90375, ...}, AT_EMPTY_PATH) = 0mmap(NULL, 90375, PROT_READ, MAP_PRIVATE, 3, 0) = 0x7f3cf4a20000close(3) = 0openat(AT_FDCWD, "/lib/x86_64-linux-gnu/libc.so.6", O_RDONLY|O_CLOEXEC) = 3read(3, "177ELF21133>1220x2"..., 832) = 832pread64(3, "64@@@"..., 784, 64) = 784newfstatat(3, "", {st_mode=S_IFREG|0755, st_size=1926256, ...}, AT_EMPTY_PATH) = 0pread64(3, "64@@@"..., 784, 64) = 784mmap(NULL, 1974096, PROT_READ, MAP_PRIVATE|MAP_DENYWRITE, 3, 0) = 0x7f3cf483e000mmap(0x7f3cf4864000, 1396736, PROT_READ|PROT_EXEC, MAP_PRIVATE|MAP_FIXED|MAP_DENYWRITE, 3, 0x26000) = 0x7f3cf4864000mmap(0x7f3cf49b9000, 344064, PROT_READ, MAP_PRIVATE|MAP_FIXED|MAP_DENYWRITE, 3, 0x17b000) = 0x7f3cf49b9000mmap(0x7f3cf4a0d000, 24576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_FIXED|MAP_DENYWRITE, 3, 0x1cf000) = 0x7f3cf4a0d000mmap(0x7f3cf4a13000, 53072, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_FIXED|MAP_ANONYMOUS, -1, 0) = 0x7f3cf4a13000close(3) = 0mmap(NULL, 12288, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7f3cf483b000arch_prctl(ARCH_SET_FS, 0x7f3cf483b740) = 0set_tid_address(0x7f3cf483ba10) = 194052set_robust_list(0x7f3cf483ba20, 24) = 0rseq(0x7f3cf483c060, 0x20, 0, 0x53053053) = 0mprotect(0x7f3cf4a0d000, 16384, PROT_READ) = 0mprotect(0x55dd44aeb000, 4096, PROT_READ) = 0mprotect(0x7f3cf4a69000, 8192, PROT_READ) = 0prlimit64(0, RLIMIT_STACK, NULL, {rlim_cur=8192*1024, rlim_max=RLIM64_INFINITY}) = 0munmap(0x7f3cf4a20000, 90375) = 0openat(AT_FDCWD, "HTB{tr4c1ng_th3_c4ll5}", O_RDONLY) = -1 ENOENT (No such file or directory)newfstatat(1, "", {st_mode=S_IFCHR|0600, st_rdev=makedev(0x88, 0x3), ...}, AT_EMPTY_PATH) = 0getrandom("x80x44x83x84xa3x91xb5xc7", 8, GRND_NONBLOCK) = 8brk(NULL) = 0x55dd45444000brk(0x55dd45465000) = 0x55dd45465000write(1, "[X] Error: Box Not Foundn", 25[X] Error: Box Not Found) = 25exit_group(0) = ?+++ exited with 0 +++We have found the flag in the line starting with “openat(AT_FDCWD”.openat()is a system call used to open files, similar to open(). In this case, the file was the flag string, which does not exist, hence the error “No such file or directory”.We've tried the system call monitoring route, what about any dynamic library calls? Another way of checking for the flag is by using ltrace tool to execute the binary and monitor library calls.“ltrace” is a debugging tool used to intercept and record dynamic library calls made by a program during its execution. It helps in understanding how a program interacts with shared libraries, which can be useful in analyzing its behavior or identifying specific functions or system calls it makes.$ ltrace ./cutteropen("HTB{tr4c1ng_th3_c4ll5}", 0, 00) = -1puts("[X] Error: Box Not Found"[X] Error: Box Not Found) = 25+++ exited (status 0) +++Bingo! The ltrace tool successfully intercepted a dynamic library call to open()a file named “HTB{tr4c1ng_th3_c4ll5},” which, as expected, does not exist. However, this interception revealed the location where the flag value was hidden within the application.Flag: HTB{tr4c1ng_th3_c4ll5}PackedAwayTo escape the arena's latest trap, you'll need to get into a secure vault — and quick! There's a password prompt waiting for you in front of the door however — can you unpack the password quick and get to safety?💡SolutionLet us begin by doing some basic reverse engineering checks on the executable binary we have just extracted from the ZIP archive.$ file packedpacked: ELF 64-bit LSB pie executable, x86-64, version 1 (SYSV), statically linked, no section headerUsing stringsstrings packed | grep -i htbWe have to dig a little deeper nowJudging by the title of the challenge and the description, we suspect that the intended solution may have something to do with “packing”.Packing typically refers to the process of compressing or encrypting executable files to make analysis and reverse engineering more challenging. Packed binaries often use various techniques to obscure their code and data, making it harder for analysts to understand their functionality. It is a technique favoured by malware writers to obfuscate the malicious code in order to thwart human reverse analysis or evade anti-virus software.If a packer was used, we may find a reference to it in the application's printable “strings”. Let's check if we haven't missed something in the full output of the strings tool.$ strings packed.bak| grep -i pack$Info: This file is packed with the UPX executable packer http://upx.sf.net $Fantastic, we are getting somewhere. Let's view the full output of the strings command:strings packed | lessWe can scroll down using the spacebar until we see this section below:Strings command reveals UPX packer was usedIf you are curious (or impatient) and have launched your favorite disassembler or debugger already, you may have also found the same information in the binary without much effort. Below is a screenshot of IDA Free revealing the application's strings:IDA Free also can reveal the use of packersLet's head to the UPX website given in the text and install the Packer.Note that most packers can pack as well as unpack a binary.I have opted to use the Linux version of the application and unpacked or decompressed the binary using the following command:upx -d packed Ultimate Packer for eXecutables Copyright (C) 1996 - 2024UPX 4.2.2 Markus Oberhumer, Laszlo Molnar & John Reiser Jan 3rd 2024 File size Ratio Format Name -------------------- ------ ----------- ----------- 22867 <- 8848 38.69% linux/amd64 packedUnpacked 1 file.The flag -d is for decompressing a file.Now we can perform the basic reverse engineering checks on the file. note the difference between the packed and unpacked binary.For demonstration purposes I have named the unpacked file “packed” and the original packed copy “packed.bak”.$ file packed* packed: ELF 64-bit LSB pie executable, x86-64, version 1 (SYSV), dynamically linked, interpreter /lib64/ld-linux-x86-64.so.2, BuildID[sha1]=d24a6e8eef367eb565e8bb90fe3ef9e9d0a71a43, for GNU/Linux 3.2.0, not strippedpacked.bak: ELF 64-bit LSB pie executable, x86-64, version 1 (SYSV), statically linked, no section headerStrings:$ strings packed | grep -i htbHTB{unp4ck3dr3t_HH0f_th3_pH0f_th3_pH0f_th3_pH0f_th3_pHHTB{HTB{unp4ck3d_th3_s3cr3t_0f_th3_p455w0rd}We can stop right here. We've successfully detected the packing of the binary, found the right packer, decompressed it and analyzed it for strings that contain the flag. Job done!Flag: HTB{unp4ck3d_th3_s3cr3t_0f_th3_p455w0rd}ConclusionLooking back, my experience with the Reverse Engineering category during this CTF was eye-opening. I'm pleased with my progress, but I'm eager for more chances to refine my skills in this area. The challenges in reverse engineering not only tested what I knew but also pushed me to learn new techniques and tools.Time was a constraint, and I couldn't explore this category as deeply as I'd have liked. Still, the challenges I tackled gave me valuable insights, especially into packers. Before this, I didn't know much about packers, but now I understand their importance better. I have also gained a better understanding of dynamic library calls and system calls in Linux.Looking ahead, I see the need to improve my skills with debuggers, decompilers, and disassemblers. Tools like Radare2, Ghidra, GDB, and IDA are great, but mastering both command-line and graphical interfaces is key.Thank you for visiting my blog and taking the time to engage with my content.As always, I urge you to explore as many solutions from my blog and others as possible. Exposing yourself to different methodologies and perspectives can broaden your understanding and deepen your skills.Once again, thank you for your support and enthusiasm. 🙏Now, Go and Play!CyberSecMaverickHTB Cyber Apocalypse CTF 2024 — Reversing was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

MAP PROT

Join the Be.Cyber community! On the program: news and tools monitoring, mutual aid and knowledge sharing, event organization (workshops, CTF resolution), ... And it's all in good fun!

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So far, most of my playing with Generative AI has been on the prompt side, with no real look at the various settings you can tweak in your calls. As I'm still very new to this, I'm trying my best to take things slowly. But every time I open Google AI Studio and see the settings on the right, I keep nagging myself to take a deeper look. You can also see the various settings options in the default code Studio spits out: const generationConfig = { temperature: 0.9, topK: 1, topP: 1, maxOutputTokens: 2048, }; const safetySettings = [ { category: HarmCategory.HARM_CATEGORY_HARASSMENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_HATE_SPEECH, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, ]; I thought today I'd take a look at temperature, as I had a very rough idea of what it implied. Temperature, at a high level, refers to how 'varied' a particular generated response can be. As an example, if I were to say, "I like ____", then you could make a list of what the next word would be, rated by how likely it is: Cats (VERY LIKELY) Star Wars (LIKELY) Books (LIKELY) Vegetables (UNLIKELY) At the highest temperature value, there will be a lot of variety. At the lowest level, no variety. Now, from what I know, that does not mean that every response will be the same. Just very similar. This post, "Creatively Deterministic: What are Temperature and Top_P in Generative AI?", does a great job explaining temperature (and other settings). While it's relatively easy in AI Studio to adjust the temperature setting you see above, what I really wanted was a tool to help me see multiple results at once. So, I built one. :) Temperature Testing Tool My tool begins with a simple prompt: This is pretty vanilla HTML, so I won't share the code here (I've got a link to everything down below). Upon hitting the button, that's where the magic begins. Here's the JavaScript: // Testing ranges for temperature const tempRanges = [0, 0.3, 0.6, 1]; // How many times to test per temp. const perTemp = 2; let $status, $results; document.addEventListener('DOMContentLoaded', init, false); async function init() { document.querySelector('#submitBtn').addEventListener('click', handleSubmit, false); $status = document.querySelector('#status i'); $results = document.querySelector('#results'); } I begin with some variable declarations and a listener for DOMContentLoaded. The first two variable sections are the crucial ones. Temperature values go from 0 (focus on only the highest probable response) to 1 (be more creative), and I decided to test four values in that range. For each range in the array of temperatures, I do two tests. My thinking was that two results would be enough to see the variance in one particular temperature value. Carrying on… async function handleSubmit(e) { e.preventDefault(); $results.innerHTML = ''; let prompt = document.querySelector('#prompt').value.trim(); if(prompt === '') return; /* We are going to loop perTemp times for each tempRange. In order to not get stopped by Gemini for too many requests, and to provide feedback to the user, I'll report after each tempRange */ for(temp of tempRanges) { $status.innerText = `Getting results for temperature ${temp}.`; let promises = []; for(let i=0; i<perTemp; i++) { promises.push(getResult(prompt, temp)); } let results = await Promise.all(promises); let html = `<h2>Temperature ${temp}</h2>`; for(let i=0; i < results.length; i++) { html += ` <p> Result #${i+1}:<br/> ${results[i]} </p>`; } $results.innerHTML += html; console.log(results); } $status.innerText = ``; } async function getResult(prompt, temperature) { console.log(`Calling getResult with prompt ${prompt} and ${temperature}`); let body = { prompt, temperature }; let req = await fetch('/api', { method: 'POST', body: JSON.stringify(body)}); return await req.json(); } In this code, I loop over the range of temperatures and then make my two sample calls. When done, I render it out to the screen. The last function simply passes my prompt and temperature to the backend API. I'll share a screenshot, but it's a long wall of text. This is only a small portion: The backend is a lightweight Node.js server that basically handles outputting my HTML and responding to the POST request by the client-side JavaScript. Let's take a look at that, specifically the portion handling the Google Gemini call: import { GoogleGenerativeAI, HarmCategory, HarmBlockThreshold } from '@google/generative-ai'; const MODEL_NAME = "gemini-pro"; const API_KEY = process.env.GOOGLE_AI_KEY; const genAI = new GoogleGenerativeAI(API_KEY); const model = genAI.getGenerativeModel({ model: MODEL_NAME }); async function callGemini(text, temperature) { const generationConfig = { temperature, topK: 1, topP: 1, maxOutputTokens: 2048, }; const safetySettings = [ { category: HarmCategory.HARM_CATEGORY_HARASSMENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_HATE_SPEECH, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, { category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, threshold: HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE, }, ]; const parts = [ {text}, ]; const result = await model.generateContent({ contents: [{ role: "user", parts }], generationConfig, safetySettings, }); const response = result.response.candidates[0].content.parts[0].text; return response; } This is pretty much the exact code spit out by Studio but wrapped into a function where the prompt and temperature can be passed in. This function has no error handling, and that absolutely bit me in the butt. I'm going to be taking a look at those errors, and how to handle them, in a future blog post. So what did I find? Results Here are the results of using the prompt: "Tell me a story about cats." First, temperature 0. Result 1 Once upon a time, in a quaint little town nestled amidst rolling hills, there lived a mischievous cat named Mittens. Mittens was known throughout the neighborhood for her playful antics and her insatiable curiosity. One sunny afternoon, as Mittens was basking in the warmth of the sunbeam that streamed through the window, she noticed a peculiar sound coming from the kitchen. Intrigued, she hopped off the window sill and tiptoed towards the source of the noise. Upon entering the kitchen, Mittens discovered a group of kittens huddled around a bowl of milk. Their tiny paws were eagerly reaching for the sweet liquid, and their eyes sparkled with delight. Mittens, being the adventurous cat she was, couldn't resist joining in on the fun. With a playful leap, Mittens landed gracefully in the midst of the kittens. She purred loudly, her tail swishing back and forth as she rubbed against their soft fur. The kittens, initially startled by the sudden intrusion, soon warmed up to Mittens' friendly presence. Together, they formed a circle around the bowl of milk, their whiskers twitching as they lapped up the delicious treat. Mittens, being the eldest and most experienced cat, took it upon herself to teach the kittens proper table manners. She showed them how to take turns and how to avoid spilling the milk. As the kittens learned and grew, they developed a deep bond with Mittens. They looked up to her as their mentor and protector. Mittens, in turn, cherished her role as the leader of the pack. She spent her days playing with the kittens, teaching them valuable life lessons and keeping them safe from harm. Word of Mittens' extraordinary kindness and wisdom spread throughout the town. People would often bring their cats to her, seeking her advice and guidance. Mittens welcomed each and every cat with open paws, offering them comfort, support, and a sense of belonging. And so, Mittens became known as the "Guardian Cat" of the town. She was loved and respected by all, both humans and cats alike. Her legacy lived on for generations, inspiring countless cats to follow in her paw prints and spread joy and kindness wherever they went. Result 2 Once upon a time, in a quaint little town nestled amidst rolling hills, there lived a mischievous cat named Mittens. Mittens was known throughout the neighborhood for her playful antics and her insatiable curiosity. One sunny afternoon, as Mittens was basking in the warmth of the sunbeam that streamed through the window, she noticed a peculiar sound coming from the kitchen. Intrigued, she hopped off the window sill and tiptoed towards the source of the noise. Upon entering the kitchen, Mittens discovered a group of kittens huddled around a bowl of milk. Their tiny paws were eagerly lapping up the delicious liquid, their whiskers quivering with delight. Mittens, unable to resist the temptation, joined the kittens and began to partake in the feast. As they drank, Mittens couldn't help but notice that one of the kittens was smaller and weaker than the others. It struggled to keep up with its siblings, and its eyes held a look of longing. Mittens, being the compassionate cat that she was, decided to help the little kitten. With a gentle nudge, Mittens pushed the other kittens aside and made room for the weaker one. She then curled her tail around the kitten, providing it with warmth and comfort. The little kitten, grateful for Mittens' kindness, nuzzled against her fur and began to purr softly. As the kittens continued to drink their milk, Mittens couldn't help but feel a sense of fulfillment. She had not only satisfied her own hunger but had also brought joy and comfort to a fellow creature. From that day forward, Mittens became known as the neighborhood's guardian angel. She would often be seen playing with the kittens, teaching them how to climb trees and chase butterflies. She would also bring them food and shelter when they were in need. The kittens, in turn, adored Mittens and would follow her everywhere she went. They would purr and rub against her legs, showing their affection and gratitude. And so, Mittens lived a long and happy life, surrounded by the love and companionship of her feline friends. She taught the town's residents the importance of kindness and compassion, and her legacy lived on long after she was gone. Notice that both start off the same and then diverge. To save on space, I'll skip to temperature 1 next. Result 1 Once upon a time, in a bustling city called Willow Brook, there lived a calico cat named Mittens. Mittens had a reputation for being a fearless explorer, always curious and eager for adventure. One day, Mittens embarked on her biggest expedition yet. She had heard rumors of a secret garden hidden deep within the city park, and she was determined to find it. When nightfall came, Mittens began her adventure, carefully sneaking out of her home and into the park. The park was silent, illuminated only by the soft glow of the moon. As she tiptoed through the winding paths, a faint scent of flowers carried by the wind caught her attention. Mittens followed the scent until she stumbled upon a large tree. Its branches were laden with bountiful blooms, and a gentle breeze sent petals raining down on her. Suddenly, a soft voice whispered, "Welcome, little traveler." Mittens looked around, her eyes widening in astonishment. Sitting on a branch was a beautiful cat; its fur shimmered like the night sky. "I am Esmerelda," the cat said, "and you are Mittens, the brave calico." Mittens was amazed. She had heard stories about Esmerelda, a magical cat said to hold the secret to unlocking the hidden garden. "Yes, Mittens," Esmerelda continued, "you have found the Enchanted Garden. But to enter, you must pass three challenges." Without hesitation, Mittens agreed. Her first challenge was to find a golden key hidden within the roots of an oak tree. With her sharp claws and determined spirit, Mittens discovered the key, its surface glowing brightly. Next, Esmerelda asked Mittens to gather dewdrops from the heart of a moonflower blossom. As Mittens gracefully leaped and climbed the tall stems, she carefully collected the sparkling dew in a tiny seashell. Finally, Mittens' last challenge was to sing a song that would make the trees sway and the flowers bloom. As Mittens lifted her voice, her melodious' tune enchanted the garden, which sprang to life with vibrant colors and dazzling lights. Esmeralda smiled, "Well done, little traveler. You have passed the challenges." With a gentle paw, Esmerelda touched the large oak tree, causing it to slowly open like a door, revealing an awe-inspiring paradise. Inside the Enchanted Garden, Mittens found lush meadows, sparkling fountains, and exotic creatures playing among the trees. It was a place of wonder and joy as if every storybook she had ever heard had come true. Mittens spent the entire night exploring the magical realm, amazed by its beauty. As dawn broke, she turned to Esmerelda and said, " Thank you for sharing this incredible place with me. Esmerelda purred softly. "You are welcome, Mittens. As long as you believe in magic, the garden will always be here for you to explore." From that day forward, Mittens became the guardian of the Enchanted Garden, a place where she could always find solace, friendship, and a sense of belonging among the natural beauty of Willow Brook. And so, the legend of the brave calico and the Enchanting Garden lived on, brought to life of the belief in magic and the wonders that can be found when one dares to explore beyond the ordinary. Result 2 Once upon a time, in a small and charming town called Willow Creek, nestled amidst rolling hills and blooming meadows, there lived two extraordinary cats. One was a sleek and graceful Siamese named Luna, whose shimmering white fur and piercing blue eyes radiated elegance and mystique. Her every movement exuded nimbleness, gliding through the streets of Willow Creek with an air of regal composure. Meet the second cat, a tabby by the name of Max, a playful and mischievous soul adorned with a coat of orange and black stripes. His sparkling green eyes twinkled with a mischievous glint; ears always perked, ever alert to the adventures that awaited him. His playful antics had become a legend among the townspeople, who were often greeted by his friendly antics and joyful meows. The companionship between Luna and Max was a sight to behold. They were inseparable, roaming the cobblestone streets together, their playful pursuits leading them to alleyways and secret paths known only to them. Their friendship was a true testament to the unwavering spirit and unbreakable bond between cats. During the day, they would bask lazily in the warm sunlight that bathed the town square, absorbing the melody of children playing and the laughter of friends sharing stories. At night, under the velvet sky adorned with shimmering stars, they would chase elusive fireflies and embark on daring expeditions, exploring the town's hidden nooks and crannies, their soft paw steps barely disturbing the tranquil silence. Many a local came to rely on the presence of Luna and Max, knowing that their playful chases and affectionate purrs brought an unexplainable joy and warmth to the heart. The elderly, feeling isolated, found solace in their presence, witnessing a simple yet profound beauty in their interactions. Children were captivated by their antics, watching in delight as they climbed trees or chased each other through the flowerbeds. One day, a traveling circus arrived in Willow Creek, filled with fanfare and vibrant colors. Luna and Max, captivated by the excitement, couldn't resist exploring the wonders this circus held. As they ventured into the largest tent, they were greeted with the mesmerising spectacle of trained cats, performing incredible feats of agility and balance. Inspired by their newfound passion, Luna and Max made a daring decision - they ran away to join the circus! They honed their skills tirelessly, practicing their balancing acts and performing stunning leaps. Their dedication and unwavering friendship caught the attention of the ringmaster, who recognized their talent and potential. Finally, the moment arrived when Luna and Max took center stage, their hearts pounding with excitement and anticipation. The audience, holding their breath in anticipation, witnessed an extraordinary performance, a mesmerizing ballet of agility and grace. Luna's elegant poise and Max's playful energy combined to create a symphony of motion that left the spectators awe-inspired. News of Luna and Max's incredible talents spread like wildfire, and they became stars of the circus, sharing their joy and laughter with audiences of all ages. Their unwavering friendship remained the heart of their performances, a symbol of the magical bond between cats that touched the hearts of all who witnessed their amazing journey. And so, Luna and Max, once ordinary cats roaming the streets of Willow Creek, found their destined path in the spotlight of the circus ring, leaving behind a legacy of a friendship that defied the ordinary and inspired the extraordinary in others. As you can tell, even if you only skimmed it, these are much more varied. I found having all these variations on screen at once, from the same prompt, a real easy way to help me understand the impact of temperature. If you want to try this yourself, you can grab the bits here: https://github.com/cfjedimaster/ai-testingzone/tree/main/temp_tester Download the code, npm i the required bits, and set an environment variable for your Google API key. Run the script (node script.js) and it will open up a web server on port 3000. Lastly, just open that up with your browser. As always, let me know what you think. I've got some ideas for other tools like this as a way of learning generative AI! Also published here.

Cat category Mittens Temperature

What Are Code Explainers? Code explainers are tools designed to make code more comprehensible. They work by breaking down complex lines of code into simpler, understandable chunks. They can highlight the logic behind each code block and depict the flow of data throughout the program. The ability to explain code is essential for software development teams to understand the functionality of the code, carry out debugging, and collaborate efficiently. Automating code explainers takes this a step further. Automated code explainers are advanced tools that use various techniques, including AI and machine learning, to automatically interpret and explain the code. They not only explain the code but also suggest improvements and detect potential errors. This automation can transform and scale up the code review process. Types of Automated Code Explainers Static Code Analysis Tools Static code analysis tools are software applications that examine source code without executing it. They identify potential errors, security vulnerabilities, and coding standard violations. These tools are effective for maintaining code quality and ensuring adherence to coding standards. They analyze the code for common programming errors, such as syntax errors, logical errors, and potential bugs. Static analysis tools can also check for compliance with coding conventions and guidelines, helping to maintain a consistent codebase. By using static analysis tools, developers can detect and fix problems early in the development process. This proactive approach reduces the likelihood of bugs and vulnerabilities in the final product. Additionally, these tools can automate the tedious and error-prone process of code review, enabling developers to focus on more complex tasks. Integration of static analysis tools into the continuous integration/continuous deployment (CI/CD) pipeline ensures continuous code quality checks throughout the development lifecycle. Code Visualization Tools Code visualization tools offer a graphical representation of the codebase, making it easier to understand complex code structures and relationships. They can display various aspects of the software, like class hierarchies, dependency graphs, and control flow diagrams. This visual approach helps developers comprehend the architecture and design patterns within the code, aiding in better decision-making during development and maintenance. These tools are particularly useful in large projects with intricate codebases, as they provide a macroscopic view of the software architecture. Visualization assists in identifying redundant or tightly coupled components, enabling refactoring efforts to improve code quality and maintainability. Code visualization tools also facilitate new team members' understanding of the existing codebase, speeding up the onboarding process. By integrating these tools into the development environment, teams can continuously monitor and analyze the evolving structure of their software. Automated Code Review Tools Automated code review tools are designed to analyze source code and suggest improvements, similar to a human reviewer. They check the code for common issues like coding standard violations, potential bugs, and performance issues. These tools use a combination of static code analysis, pattern recognition, and more recently, large language models (LLMs), to evaluate code quality and consistency. The use of automated code review tools streamlines the code review process, allowing teams to focus on more complex and subjective aspects of code quality. They also facilitate consistent code reviews across teams, reducing the variability that can occur with manual reviews. Integrating these tools into the development workflow can significantly speed up the review process and improve the overall quality of the codebase. Furthermore, automated reviews provide immediate feedback to developers, fostering a culture of continuous improvement and learning. AI Coding Assistants AI coding assistants use artificial intelligence and machine learning, most notably LLMs, to assist developers in writing code. They can suggest code completions, identify errors, and offer recommendations for code optimization. These assistants learn from a vast repository of code examples and adapt to the coding style and preferences of the developer. They can significantly speed up the coding process and reduce the likelihood of errors. AI coding assistants are particularly useful for repetitive coding tasks and boilerplate code, allowing developers to focus on more complex and creative aspects of software development. They also serve as an educational tool for novice developers, providing real-time feedback and suggestions. By integrating AI coding assistants into the development environment, developers can enhance their productivity and code quality. These assistants are continually evolving, becoming more sophisticated and helpful as they learn from more data and user interactions. When used as code explainers, AI coding assistants can dissect code line by line, providing explanations in plain language. They can clarify the purpose of specific functions, variables, and algorithms, making it easier for developers to grasp the underlying logic. This capability is invaluable for learning and understanding new codebases or programming paradigms. For example, when encountering an unfamiliar function or method, a developer can use an AI assistant to get an instant explanation of its purpose and usage, along with examples of similar code patterns. Benefits of Using Automated Code Explainers Efficiency in Understanding Code Automated code explainers can break down complicated code into simpler parts, making it easier for developers to grasp. They can also trace the flow of data and logic across the program, giving a visual representation of the code's functionality. Automated code explainers can also detect potential errors and bugs in the code. By using advanced analysis techniques and machine learning algorithms, they can foresee issues that might not be apparent to the human eye. This can save developers the time they would otherwise spend troubleshooting and debugging. Improved Collaboration Automated code explainers significantly improve collaboration among team members. By providing clear and concise explanations of the code, they ensure all team members have a shared understanding of the code. This shared understanding fosters better communication and collaboration among the team. Additionally, automated code explainers can serve as a neutral third party during code reviews. They can provide unbiased feedback on the code, preventing any personal biases from influencing the review process. This unbiased review promotes a fair and collaborative environment where the focus remains on improving the code. Learning and Development Automated code explainers are excellent learning tools for developers. They provide real-time feedback on the code, allowing developers to learn and improve as they code. Developers can see the impact of their code changes immediately, understanding what works and what doesn't. Moreover, for junior developers or those learning a new programming language, automated code explainers can serve as a valuable guide. They can help these developers understand complex code structures and patterns, accelerating their learning process. 5 Best Practices for Using Code Explainers Effectively 1. Integrate with Development Workflow Code explainers should be a part of your daily coding routine. For example, you can set up your explainer tool to automatically analyze your code whenever you commit changes. This approach ensures that you receive feedback on your code in real-time, allowing you to address any issues or inefficiencies promptly. 2. Regularly Review and Refine Suggestions Code explainers use static rules and machine learning algorithms to analyze your code and provide suggestions for improvement. As such, they are not infallible, and their suggestions should not be accepted blindly. Instead, you should take the time to review the suggestions and consider whether they make sense in the context of your code. You should also consider whether the suggested changes align with your coding style and the overall architecture of your project. 3. Maintain Code Readability While code explainers can help you identify potential issues and inefficiencies in your code, they can't replace the human understanding and intuition that is necessary to write readable and maintainable code. Readability is one of the most critical aspects of a good code. Readable code is easy to understand, debug, and maintain. Therefore, even though code explainers are available in your project, you should still take care to ensure that your code remains readable and understandable. 4. Balance Automation with Critical Thinking Remember, code explainers are simply tools that can provide useful insights and suggestions. They are not a substitute for human intelligence and intuition. It's important to remember that while code explainers can speed up the development process and improve code quality, they should not replace critical thinking. Always question the suggestions provided by the tool and use your judgment to decide whether they make sense in the context of your code. 5. Tailor the Settings to Suit Your Coding Style Most code explainers come with various settings that you can customize to fit your needs better. For example, you can adjust the sensitivity of the tool to control the number of suggestions it provides. Some types of tools allow you to customize the types of suggestions and additions they make to the code or even provide natural language instructions specifying how you want the tool to behave. In conclusion, automating code explainers can be a powerful ally in your software development process. However, to reap the maximum benefits of this technology, it's crucial to follow the best practices discussed in this article. By integrating the tool into your workflow, regularly reviewing and refining its suggestions, maintaining code readability, balancing automation with critical thinking, and tailoring the settings to suit your coding style, you can ensure that you get the most out of your code explainer tool.

Automated Code Code Explainers Explainers