For years, I’ve assumed that most people don’t need third-party antivirus tools and have cheerily passed this suggestion along to others. After all, Microsoft’s Windows Security suite (also known as Windows Defender or Microsoft Defender) provides built-in virus protection for your PC,

Is Windows antivirus software still necessary in 2023?

Despite increased spend on defences, nearly 70% of organisations have been breached by cyber-attacks at least once in the past year, according to Forrester. As an industry, we are clearly getting a negative return on that investment.

Cyber security in modern construction: Preparing for the inevitable

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The U.S. on Monday sued a software company targeted in a massive Russian cyber espionage campaign.    The Securities and Exchange Commission (SEC) suit against Texas-based SolarWinds is seeking civil penalties,

US sues software company targeted in massive Russian cyber espionage campaign

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This research from Sonatype, a U.S.-based company specializing in software supply chain management and security, also covers developers’ challenges and the possible benefits to using AI security ...

Software Supply Chain Security Attacks Up 200%: New Sonatype Research

In this month’s CW EMEA ezine, we look at HR software ... security sector already, consider the data privacy challenges associated with generative AI, and find out why it is important for ...

Enterprise software

In this article, I will delve into whether artificial intelligence (AI), particularly the emergence of tools like generative AI (GenAI), will replace classical software outsourcing as we know it.

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In today’s digital age, where cyber threats lurking around every corner, protecting our devices and personal information has become more crucial than ever. Whether you’re a seasoned tech guru or someone who simply loves browsing the internet,

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Qihoo 360 Technology Company Ltd. supplies internet security services. The Company researches, designs, develops internet security software and sells third party anti-virus software, as well as system optimization products.

Qihoo 360 Technology Co. Ltd. (NYSE: QIHU) is a leading Internet company in China. The Company is also the number one provider of Internet and mobile security products in China as measured by its user base, according to iResearch. Qihoo 360 also provides users with secure access points to the Internet via its market leading web browsers and application stores. The Company has built one of the largest open Internet platforms in China and monetizes its massive user base primarily through online advertising and through Internet value-added services on its open platform.

360 SECURITY

Employee’s Endpoint security Internal Survey-Template ★ I have designed an , moreover consider it as a , you can even this survey and add questions specific to your organization’s needs and goals. internal employee survey on endpoint security survey template customize ★ This Endpoint security survey an to the most relevant conclusions on the current state of into the with a focus on cyber-security development. helps individual organization identify IT security’s policy, methods, and logical insight IT security maturity level , To download this survey click here B*%EnD_$20-sEc-!ty Passkey: ★ Your employees need to understand what is all about?  Explain the survey topic and its ★ Your introduction only needs to be in a paragraph or two more paragraphs at most.  Please, Include the following useful information in your introduction: Your name or the name of the company or organization you represent, and other informations as like mentioned in this survey. Purpose - Survey Introduction: ★ We are conducting an internal employee survey on endpoint security, which will be conducted online from now on. Thank you for your participation and hope to hear from you. The network security team is investigating employees’ endpoint protection and security solutions. We invite all employees to take part in the survey, and the active participation of employees will provide the ideal results for the team. ★ The survey itself contains and takes about to complete. To ensure the privacy and confidentiality of all your responses to the company, we only ask which department you work in, which will help us collect and analyze the data. 40 questions 5–10 minutes ★ Please note that this is an anonymous survey. We will not see your personal response: the automated program will aggregate and provide a survey without a name or email address. We must answer All questions. Please, do not click Yes/No before reading the question. Thank you for your understanding. Note: Please take a moment to complete the following quick survey. *Required 1. What department do you work in*? Please, choose the applicable department from the given below list *. Executives Director Senior Vice President (VP) Vice President (VP) Accounting and Finance HR Marketing & Communications Business Strategy Legal Commerce Department Product Department R&D Department Sales Pre-sales solution Department Customer Care Department Network Department Operation and Maintenance Department Physical security Reception Add alt text 2. What type of devices are you using at present*? Windows MAC Unix distributions (ALL) 3. If you are a Windows user, which version of Windows OS installed on the computer*? Type in the windows search box and press Enter it will display the operating system name Tip: winver Windows 10 Windows 8.1 Windows 8 Windows 7 Windows Vista Windows XP I do not know 4. If you are using windows 10, can you choose the correct updated version from your device*? Type in the windows search box and press Enter it will display the operating system Version. Tip: winver Version 1709 Version 1803 Version 1809 Version 1903 Version 1909 Version 2004 Not applicable 5. If you are a MAC user, at present, which version of MAC do you have*? Click the Apple menu icon in the upper left corner of the screen and then select the “About This Mac” command. Tip: MacOS 10.15: Catalina (Jazz) MacOS 10.14: Mojave MacOS 10.13: High Sierra MacOS 10.12: Sierra OS X 10.11: El Capitan OS X 10.10: Yosemite OS X 10.9 Mavericks Not applicable 6. When did you last updated your Windows Operating system*? Click Windows “Settings,” -> Click “Update Security” -> Click “Windows Update” -> Click “Update History,”. Tip: I set it to update automatically This Month Last Month Sometimes when I remember Delay it/ignored notifications I don’t know what is windows update Never Not applicable 7. When did you last updated your MAC Operating system*? I set it to update automatically This Month Last Month Sometimes when I remember Delay it/ignored notifications I don’t know what is windows update Never Not applicable 8. How many laptops do you carry to the work*? one Two Three None 9. How many smart devices do you carry to work*? Example: Smartphones, iPhone, iPad, Smart-watch, Bluetooth headphones/headsets*? 1 2 3 4 5 10. Do you have an antivirus installed on your PC/MAC*? Yes No I don’t know 11. Do you have an antivirus installed on your Mobile*? Yes No I don’t know 12. which PC antivirus Application are you using*? If applicable, Choose multiple*? 360 Security Mobile Tencent Protect Trend Micro Avast Microsoft(Windows Defender Antivirus) ESET Symantec AVG Avira Kaspersky McAfee Bitdefender Other's type it: 13. Are you an Android or iPhone User*? Android iPhone Windows phone BlackBerry OS Others: 14. If you answered above yes, can you tell us how many times once you perform an automatic or manual scan for a virus*? Automatic This month Last month Sometimes when I remember Delayed/ignored notifications When my PC slow down Never 15. Have you ever found a virus or Trojan on your computer at work in the past*? Yes, my computer has been infected before. No, my computer has never been infected. I do not know, what is a virus or Trojan horse*? 16. Do you lock your computer when you leave the work desk*? Yes, I do (Yes; I do) No, I don’t do No one touches my PC 17. Do your PC/MAC screens automatically lock after 10 minutes in idle*? Yes No 18. Which web browser do you normally use *? If applicable, Choose multiple. Internet Explorer Q360 Google Chrome Mozilla Firefox Opera Safari (Apple) Other's type it: 19. Do you classify your data, identifying sensitive data versus non-sensitive*? Yes, I do No, I don’t Not Applicable 20. Are you taking any measures to protect sensitive data (document) under your control*? Yes, I do Partially take care of it No, I don’t Not Applicable 21. Is the most valuable or company’s sensitive data protected using encryption*? Yes, I do (Yes; I do with encryption) Yes, but not with any encryption protocol No, I don’t Never heard about encryption Not Applicable 22. Are you or Can you use your own personal devices, such as your mobile phone, Thumb drive), to store or transfer confidential company information*? Yes, I do No, I don’t Not Applicable 23. Do you follow any procedure for creating a retrievable backup and archival copies of the company’s critical information*? Yes, I do No procedures, store randomly No, I don’t I don’t take a backup Not Applicable 24. Do you have any procedures for disposing of documents*? Yes, I do No, I don’t No procedures, Direct disposal Not Applicable 25. Does your desk have any sensitive files*? Yes, I do No, I don’t Not Applicable 26. Where do you place the company’s confidential files*? On the desk Secure cabinet Personal Cabinet Unattended 27. How often do you take information from the office and use your computer at home to work on it*? Almost every day At least once a week At least twice a week At least once a month Not applicable Never 28. How many days once you change your computer password*? Every week 30 days once 60 days once 90 days once Once in a year Never 29. Are you using a secure password that exceeds 8 or more characters*? Yes (8 or more characters) No (less than 8 characters) No Password 30. Can you ensure that only authorized personnel has access to your computers*? Only myself Share with colleagues/team I’m not sure 31. Whether the password of the work PC has been authorized or notified to others, has the password been changed*? Changed Not Changed I don’t Know Not applicable Other's type it: 32. are you using windows firewall, is it turned on or off*? Yes, it’s enabled No, it’s not enabled I do not know what a firewall is 33. Have you found any virus in your PC in the past 3 months*? Yes No I do not know 34. Do you open any advertisement, eCommerce, event invitation emails from unknown sources*? Yes No There is nothing wrong with opening an attachment from them 35. Have you downloaded and installed any unknown third-party software on your computer at work in the past 3 months*? Yes No Well, I don’t remember it 36. Do you know what an email scam is and how to identify one*? Yes, I do No, I do not I don’t care 37. My computer has no value to hackers; they do not target me) What do you think*? True False 38. Do you know whom to contact in case your computer is infected or locked by malware*? Yes, I know who to contact No, I don’t know who to contact 39. If you delete a file from your computer, Flash-drive, or hard drive, that information can no longer recover*? True False 40. How secure do you feel your computer is*? Very secure Secure Not secure No idea — — — — — — — — — End of the Survey! 👏 👏 👏 — — — — — — — Thank you very much! To download this survey, click here Passkey: B*%EnD_$20-sEc-!ty Also published at https://medium.com/@gtmars/employees-endpoint-security-internal-survey-template-61a16480a08

How To Make an Internal Employee Survey on Endpoint Security

As an AI expert, let me be blunt - cyber threats are a massive, unrelenting risk that no business with an online presence can afford to ignore these days. Whether you're running an e-commerce site, logistics operation, or tech firm, phishing, ransomware attacks, or data breaches - these scourges can cripple a company, leading to devastating financial losses, irreparable brand damage, and even regulatory penalties that could bury you. I've personally seen the aftermath of cyber strikes on SMBs with limited security resources and tight budgets. In those cases, traditional cybersecurity just doesn't cut it against today's attack of threats. But that's exactly where artificial intelligence (AI) emerges as a total game-changer. discovered that organizations leveraging AI and automation extensively saved a mind-blowing $1.76 million on average compared to their less AI-savvy counterparts. IBM's 2023 Cost of Data Breach Report And I can testify that AI-powered cyber defense solutions truly earn those savings. By unleashing cutting-edge AI techniques like machine learning, deep learning models, and natural language processing, modern AI cybersecurity acts like an indispensable digital force multiplier reinforcing our defenses against even the wiliest adversaries. As an AI expert, I've deployed these capabilities for clients - it's like having an entire squad of cybersecurity sentries patrolling the digital premises 24/7 to keep the bad actors at bay. Moving forward, I don't believe adopting advanced AI will be a luxury for organizations - it's a flat-out necessity we can't ignore. Whether you're a small business or a giant enterprise, you'd better get proactive and start leveraging AI's offensive cybersecurity potential to safeguard your vital digital assets and ensure continuous operations. In my opinion, AI is quickly separating the cybersecurity haves from the have-nots. AI's Cyber Offense: How It Turbocharges Threat Detection I can't overstate how AI is revolutionizing cybersecurity by unleashing cutting-edge threat detection and response capabilities never before possible. Just look at the rapidly growing market - projects that AI in the cybersecurity sector will explode from $22.4 billion in 2023 to $60.6 billion by 2028. And there are good reasons behind that meteoric growth. MarketsandMarkets Machine learning algorithms excel at quickly identifying patterns and anomalies within massive datasets - making them invaluable assets for recognizing potential cyber threats amid tons of network traffic, user activity logs, and other data. By training these algorithms on historical data, we can have them recognize known attack signatures and deviations signaling new threats before they can wreak havoc. One study I find particularly compelling is from MDPI, showing machine learning models achieved up to 99% malware detection accuracy using techniques like Decision Trees, Convolutional Neural Networks, and Support Vector Machines. That's the level of precision AI can deliver against emerging threats. There are deep learning models that I've deployed to rapidly analyze and classify malware samples with incredible accuracy. The latest deep-learning architectures can see patterns invisible to the naked eye. However, some of the most exciting AI cybersecurity applications my team has tested involve reinforcement learning for adaptive threat response. These self-learning systems can dynamically adjust defensive actions on the fly based on their experiences against evolving attack vectors. Allied Market Research predicts reinforcement learning will see explosive 41.5% annual growth from 2023 to 2032, with cybersecurity as a prime use case. Let's not overlook natural language processing (NLP) for automating incident analysis. I've personally overseen NLP deployments that can rapidly comprehend human language data from reports, intelligence feeds, and more - streamlining our incident response workflows and prioritizing genuine threats over false positives. Combining all these AI disciplines is delivering incredible offensive capabilities to counter even the trickiest cyber adversaries. As an expert and founder in this space, I truly believe AI's ability to autonomously detect and shut down threats before impact will utterly transform cybersecurity over the coming years. Why UEBA and User Behavior Monitoring Matter (And How AI Excels) The cyber risk from malicious insiders or compromised user accounts is one we can't overlook either. That's why I consider user and entity behavior analytics (UEBA) powered by advanced AI/ML models to be paramount for comprehensive, 360-degree security visibility. At a basic level, these AI-driven UEBA solutions leverage machine learning to establish baselines modeling each user's normal behavior based on their activity patterns. Once those baselines are established, the AI can continuously monitor for deviations that may indicate insider threats, privilege abuse, compromised accounts, and other insider risk vectors. What makes this application of AI so powerful is its ability to dynamically score the risk level of unusual user actions based on contextual factors like their role, access privileges, the sensitivity of data/systems involved, and more. This enables real-time flagging of potentially malicious insider activity for further investigation - something that was highly prone to human error with traditional, rigid rule-based approaches. Another area where I've seen UEBA with AI shine is detecting compromised privileged user accounts, which are prime targets for external threat actors seeking a foothold. By understanding the unique behavior patterns of different privileged user roles, AI can rapidly identify the subtle anomalies of a privileged account under hostile control - giving our teams a chance to shut down that breach before catastrophic damage occurs. In my opinion, deploying AI for insider and privileged user threat detection by understanding human behavior is an absolute game-changer. Monitoring our people and accounts is just as vital as external threat monitoring - without it, we're leaving a gaping hole in our defenses that skilled adversaries will inevitably find and exploit. Of course, my teams always emphasize that AI-powered UEBA is just one layer in a comprehensive, defense-in-depth strategy. But it's a crucial layer that lets us get in front of insider incidents before they escalate - buying time that can mean the difference between a contained issue and a full-blown crisis. The Flip Side: Defending Against AI-Powered Threats As amazing as AI's cybersecurity offensive capabilities are, I have to address the flip side too: hackers are actively working on ways to weaponize AI against us. Adversarial attacks designed to bypass, poison, or steal our AI models are a clear and present danger we can't ignore. One disturbing forecast from research analysts indicates: Up to 30% of AI cyberattacks will leverage training data poisoning, model stealing, or adversarial examples to attack AI-powered systems. But we're not defenseless - there are proven ways to harden AI systems against these tactics if we invest in robust AI security controls from the start. Approaches like adversarial training, where models are intentionally exposed to deceptive inputs during the learning process, can improve resilience against evasion. Differential privacy techniques can also obscure model behavior to thwart extraction attacks. We follow best practices around secure AI development Life Cycle, subjecting our models to rigorous adversarial testing and employing defensive AI techniques to stay ahead of emerging threats. I don't mean to sound alarmist, but the cybersecurity industry at large needs to prioritize battling AI-powered threats just as much as leveraging AI for defense. It's a two-way street - we must secure the AI models underpinning our cyber defenses with the same vigor we apply AI offensively. Neglecting AI security WILL be exploited by sophisticated hackers. So while I'm incredibly confident about AI's potential to revolutionize cyber threat detection and response, I'm also pragmatic. We simply can't ignore the dark side and must proactively invest in developing and deploying AI securely to maintain a decisive strategic advantage. Integrating AI Across Security Operations Of course, AI alone is not a silver bullet for cybersecurity. Its true power comes from thoughtful integration across existing processes, teams, and technology stacks. As an enthusiastic AI Expert, I emphasize this force-multiplier effect to clients constantly. AI should augment and empower human expertise, not replace it entirely. That's why the most successful deployments I've seen use AI to offload tedious, repetitive tasks to machines - freeing up skilled personnel to focus on higher-level analysis, investigation, and decision-making that requires human judgment. That's also why AI is rapidly becoming essential for SOC analysts and incident response teams: by automating alert triage, log analysis and basic response workflows, AI drastically reduces burnout from low-value "grunt work" while improving overall efficiency. Research from Capgemini revealed organizations using AI for security operations saw a 12% increase in breach detection rates and an impressive 19% reduction in time-to-respond. Those are major gains I've validated through my own startup's AI deployments. AI and machine learning are also driving huge advances in security orchestration, automation, and response (SOAR) tools that streamline entire incident response processes. With SOAR, AI handles tasks like correlating disparate security signals, surfacing relevant threat intelligence, and even executing semi-automated response playbooks. It's a huge step towards smarter, more autonomous incident handling. Ultimately though, AI is a complement to skilled human teams, not a wholesale replacement. Cybersecurity operations will always require human expertise, analysis, and judgment. But by intelligently augmenting our people with AI automation and assistance, we can concentrate their talents on higher-impact duties while optimizing productivity and efficiency. I already see this human-machine symbiosis enhancing the industry's ability to outpace threats. As AI integration continues maturing, I'm confident embracing this collaborative model is the only way we'll realistically close the cybersecurity skills gap plaguing our field. AI's Cybersecurity Superpowers By rapidly analyzing network data, user activities, system logs, and more, AI can identify malicious behavior patterns and potential threats with superhuman speed - giving us an early warning to shut down attacks before escalation. Threat Detection & Prevention: While phishing lures and malware grow more devious, AI algorithms can precisely distinguish malicious files and emails from legitimate ones by evaluating content, sender metadata, behavioral signals, and other artifacts that often evade human analysis. Phishing and Malware Detection: Rather than rigid rules, AI lets us dynamically model normal user activity baselines. It can then rapidly detect anomalies indicative of insider threats, compromised accounts, data exfiltration attempts, and more - all in real-time. User Behavior Analytics: I've deployed AI to prioritize vulnerabilities based on their risk and exploit potential, automating the triaging process. AI can also correlate vulnerabilities with active threats, showing us which exposures need patching first. Automated Vulnerability Management: Modern AI-powered SIEM solutions can correlate security events across networks, endpoints, and other sources to rapidly identify genuine incidents amidst the noise. AI also streamlines response workflows based on alert contexts. Smart SIEM & Incident Response: Across incident triage, alert analysis, threat hunting, and more, AI is automating repetitive, labor-intensive security tasks - amplifying the impact of human personnel while reducing burnout and fatigue. Security Ops Automation: I could go on, but you get the idea. As an AI expert and entrepreneur, I've seen these capabilities utterly transform cybersecurity operations into an amazingly proactive, autonomous counter-threat force. And AI's offensive cyber capabilities are still rapidly evolving. The Way Forward: Practical AI Cyber Defense But when I gaze into the future of AI-powered cybersecurity, I see incredible potential beyond just better threat detection and response. Used wisely, I believe AI can fundamentally reshape and elevate our entire profession into a truly proactive, predictive security posture - finally outpacing even the wiliest cyber adversaries. However, realizing this AI-driven future won't happen automatically. It requires us as an industry to thoughtfully and securely integrate AI across our people, processes, and technology stacks with a keen focus on augmenting human expertise and capabilities rather than wholesale automation. At an operational level, this will mean embracing increasingly autonomous security workflows offloaded to AI systems - handling tedious triaging and basic response while escalating only the most critical issues to skilled analysts for analysis and key decisions. It's a pragmatic balance of human and machine capabilities. We'll also need a new class of cybersecurity professionals fluent in interpreting AI system outputs and translating them into strategic guidance. These AI-savvy analysts must be adept at not just using but explaining and justifying AI system behaviors and decisions to leadership stakeholders. It plays a crucial role in building organizational trust and accountability around AI systems. Additionally, organizations must adopt secure AI system development lifecycles, proactively battling adversarial AI threats through approaches like robust model training, adversarial testing, privacy-preserving analytics, and defensive AI architectures. We simply can't leave our AI systems vulnerable to adversarial subversion. Thankfully, I see positive momentum towards these goals across the AI security startup ecosystem and cybersecurity community. But we must keep pressing forward holistically - investing in skilling our people, refining our processes, and pioneering new AI-centric technologies securely and ethically. Only then can we responsibly wield AI's incredible cyber defense potential without enabling worse nightmares. Despite all the work ahead, I'm hugely optimistic as an AI expert and founder. I've already deployed these transformative AI capabilities in the field, experiencing their game-changing impact firsthand. AI gives us a truly decisive advantage in combating even the most sophisticated threat actors - if we successfully fuse machine intelligence and human expertise. It won't be easy, but I'm convinced the payoff will be a safer, more secure digital world actively hardening itself against cyber threats in real-time. A world where novel attacks are neutralized before impact, where vulnerabilities are patched before exploitation, and where malicious insiders and compromised accounts are stopped in their tracks. Best of all, AI cyber defense done right should free up our human personnel for higher-impact strategic work, not tedious data grunt work. AI should empower us to be the cybersecurity experts, creative problem-solvers, and strategic leaders we always aspired to be - not menial attack analysts. So to my fellow AI professionals, founders, and innovators - the path ahead is clear. Let's blaze this trail TOGETHER, pioneering the new era of practical, intelligent, and ethical AI-powered cyber defense. The future of digital safety depends on us doing this right. And with our unique combination of human ingenuity and machine intelligence, I'm confident we're up to the immense challenge. Let's get to work.

Applications of Artificial Intelligence in Cybersecurity: Boosting Threat Defense System

Check out the latest platforms and tools to deploy and manage Microservices here, in this blog! Today, ‘Monolith to Microservices’ is one of the most sought-after application modernization initiatives taken by the world's best technology leaders. Leading enterprises worldwide are embracing this approach to achieve microservices architecture benefits such as increased resilience, rapid delivery, improved scalability, and faster time to market. In 2021, 45 percent of respondents stated that data analytics/business intelligence applications use microservices, says Statista. Microservices are a cloud-native architectural approach that typically has their own technology stack, such as a data management model and database, and can communicate with one another via APIs. Here are 5 major platforms and microservices tools that can help DevOps & SRE teams to manage, build and deploy Microservices. Let’s take a look! Microservice Architecture: What is it? Microservices is an architectural style and approach to writing software applications wherein the applications are broken down into smaller, independent components. The Microservices architecture methodology promotes application development as a collection of autonomous, smaller programs. Each program is designated a functionality and communicates with other programs through APIs to solve a complex business problem. The main goal is to facilitate the deployment process and develop high-end, cloud-ready software programs fast. By decomposing the application into multiple smaller components, it becomes easier to scale, modify, and deploy the apps. Technologies That Make Microservices Architecture Development Easier! Teams can deploy Microservices using a variety of tools and platforms some of which are: - Docker & Kubernetes - Prometheus - BuildPiper - Consul - REST Let’s discuss these microservice tools in detail! Docker and Kubernetes Docker is an open-source platform to build, deploy, and manage containerized applications. Since each of the containers is self-reliant in terms of configurations and resources that are required to run microservices, Docker containers can be deployed practically at any place. Problems and severe complexities of operations arise when the microservices are scaled across multiple servers. Kubernetes is then used as a complement to Docker to resolve these complexities. Kubernetes (also known as k8s or “Kube”) is an open-source container orchestration platform that automates most of the manual tasks that are involved in deploying, managing, and scaling containerized applications. Docker along with Kubernetes is a popular Microservice tool in the industry. They together form an ideal pair for creating a robust and flexible base for managing operational complexities when Microservices are scaled up and down as the workload increases or decreases. Source: Kubernetes.io Prometheus Developed at SoundCloud, Prometheus is an open-source alerting and system monitoring Microservice tool. With Prometheus, DevOps teams can implement a multidimensional data model with data stores and data scrapers. Here, the data is stored in the form of key-value pairs in memory cache files. Based on a simple query language, Prometheus helps in monitoring tasks. It uses a convenient, user-friendly graphical interface that helps in visualizing monitoring information and supports time-based tracking so that anomalous patterns can be detected. When compared to traditional monitoring systems in complex and real-world environments, Prometheus performs a good job. Prometheus is widely used in the development of minimalist applications and serves the best when it comes to building up simple microservices. Source: Prometheus.io BuildPiper BuildPiper is an end-to-end Kubernetes & Microservices Application Delivery Platform that helps in seamless onboarding & securely manage Kubernetes & Microservices application setup and deployments along with the ability to run zero-touch, fully-automated & secured CI/CD pipelines. Here’s how this robust Microservices & DevSecOps platform helps in delivering the dockerized code and critical business functionalities from a coder’s workstation to the scalable, secured and monitored production environment. It helps in setting up a new Kubernetes cluster and enables the onboarding of an existing one. It enables onboarding and management of Microservices in a hassle-free manner. Comprehensive CI analysis and customizable CI gate checks enabled CD Pipelines for Macro & Micro builds and deployments. Cluster Onboarding in a few simple clicks: Seamless Onboarding of Microservices: Secure setup of CI/CD Pipelines: Ensures comprehensive security and compliance via some of the best industry tools such as ISTIO, Hashicorp Vault, etc. Leverages 360-degree observability through a user-friendly Kubernetes dashboard. Complete Security & Compliance: 360-degree Cluster Observability: Source: BuildPiper.io Consul Next on the list of Microservices tools is Consul. It is a multi-cloud service networking platform that helps to connect and secure services across any runtime platform and public or private cloud. Used for service discovery, Consul helps microservices communicate with one another. Consul has some outstanding features which make it so popular, DNS interface and Consul Template provide Consul with the flexibility allowing Consul to be used in integration with many technologies. -It provides support for DNS and has an HTTP REST API. -Configuration files can be auto-generated by using Consul Template. -While performing health checks, Consul can exclude services from service discovery ( in case the health checks fail). REST REST (Representational State Transfer) is an architectural style to develop and build web services. Also known as Representational State Transfer, REST is a communication protocol that allows microservices to be used for interaction or communication with others. REST is a technology that is used to build RESTful APIs. It allows microservices to communicate directly with each other via HTTP. The request and response are exchanged in HTML, XML, or JSON formats. Using these platforms and Microservices tools, DevOps teams can manage and deploy Microservices to reduce time-to-market, enhance app stability and augment app security. Also Published Here

5 Best Technologies You Can Use to Deploy and Manage a Microservices Architecture

Security is a massive global industry and it is extremely diverse. Whether it is the protection of prize racehorses, or guarding utility infrastructures, the ‘threatscape’ is increasingly complex and requires a convergence of cybersecurity and the more traditional, physical forms of preventing theft and other forms of criminal activity. Artificial Intelligence (AI) is the most promising tool for deploying digital security, but as Louis Columbus remarks in a recent Forbes article, “What needs to be the top priority is improving the accuracy, insight, and speed of response to remote threats that AI-based video recognition systems provide.” Remote Vigilance is the Goal Remote security monitoring is the way forward. Companies want video cameras capable of night vision, infrared, and thermal imaging that provide 24/7 monitoring of equipment, sites, and valuable assets. So, where should we look for the most rapid advances in providing AI-led, remote security systems? One such company is Twenty20 Solutions, which is integrating machine learning with real-time video data feeds of remote sites. Its system is also able to identify any activity anomalies in real time, something that the market is clamouring for. Columbus says, “What’s noteworthy about this approach is the need many industries have to integrate cyber and physical security systems and get a 360-degree view of remote location threats.” What is a SCADA System? Twenty20 Solutions uses a SCADA system, which is the acronym for “Supervisory control and data acquisition.” This type of system has become the gold standard in industries such as telecommunications, water and waste control, energy, oil and gas refining, and transportation. Typically a SCADA system “integrates sensors, gauges, and devices to provide data telemetry and real-time information.” It’s a Big Market Research company IMARC has predicted worldwide growth in the SCADA market, assessing its value in 2024 at around $26 billion – a CAGR of 5.7% between 2019 and 2024. How AI Solves Security Issues One of the most important things to remember about AI and machine learning technology is that both are excellent at picking out visual anomalies via video recognition systems. There are three types of machine learning algorithms that support this ‘talent’, and will form a part of future-generation video recognition systems. One is ‘Supervised Learning Algorithms’. Here the algorithms are trained via data sets “to identify correct images of objectives, so when an anomalous image appears, they can identify it.” For example, supervised machine learning algorithms can identify, track, and monitor vehicle, machinery, asset, and remote location use patterns. Another is ‘Unsupervised Learning Algorithms’. These identify new patterns in images, and the oil and gas industry find it extremely useful for monitoring infrared and thermal data from remote equipment and assets. Lastly, there are ‘Reinforcement Learning Algorithms’. With this format, AI-based video recognition systems use algorithms to correct how they identify and update known images. In the case of industries that are heavily dependent on expensive equipment, this type of algorithm “helps to ensure the consistency, compliance levels, and safety of remote equipment located in diverse geographical locations.” The future of AI-led security is also important from the perspective of the Internet of Things, with video emerging as the most powerful sensor, and as Columbus remarks, “Agriculture, construction, oil & gas, utilities, and critical infrastructure industries need to consider how their IoT platforms can be integrated into a broader cybersecurity strategy to gain a 360-degree view of multifaceted threats being launched at their locations with increasing frequency.” Ultimately, it is the ability to identify threats in real-time that will boost the use of AI in this sector. It will close the gap between the traditional physical security measures and cybersecurity, thwarting criminal activity in ways the criminals will have to work much harder to find a way around them, if there is indeed a way to get around them at all.

How AI Solves SCADA System Questions Around Remote Security

Occasionally all of us stumble upon some news from the information industry, often covering consequences of recent cyber attacks or data breaches that occurred as a result. security This information is forming our understanding of the security landscape, but it isn’t systematic and mostly resembles a set of do’s and don’ts that we might keep in mind, for a while. Not everyone has time to research and ingest relevant content on a regular basis. Consequently, threat actors and coverage of their malicious activity is regarded as “something that my AV or IT guy should deal with.” This approach is naive and there are plenty of individuals and organizations that have learned it the hard way through breaches and data loss. Researchers and security awareness pros that security habits and awareness training must be an ongoing and collective task for all organizations. agree Awareness training should provide users with a 360-degree view of the modern security landscape both from the security side and that of the threat actors. In a way, the user is the prize in a battle of 2 rival ecosystems. However, users who understand the risks and are informed about the underlying connections between different types of malware and possible attack vectors are less likely to be hacked. In order to know the enemy better, today we will discuss business and social engineering attacks popular among hackers for stealing credentials or spreading malware. We will also point out the details of cybercrime economy, trade and new business models among hackers operating on the Dark Web. email phishing Why Is Phishing Security Important? Phishing goes hand in hand with ransomware and other malware often serving as the “delivery method”. According to Ventures, ransomware damage costs for 2017 were at $5 billion in May 2017. However, long-term follow-up estimates published in November that year set the bar much higher. Global damages are to exceed $11.5 billion annually, with businesses attacked nearly every 14 seconds by the end of 2019. The threat landscape is expanding, phishing business is prosperous and more adversaries are joining the hunt for money and sensitive data. There are no signs of it stopping in the foreseeable future, so staying informed is crucial to every internet user. Cybersecurity estimated predicted Furthermore, according to PhishLab’s , threat actors have been adjusting the way of monetizing attacks, shifting from simply using a victim’s credentials to immediately steal the money to reusing credentials in hopes of gaining access accounts. 2017 Phishing Trends and Intelligence to more Monetization types are also diversifying. Now it is increasingly common to sell massive sets of credentials on marketplaces. In line with the changing approach, cyber crooks have become more focused on obtaining victim’s’ phone numbers due to growing usage of 2-factor authentication. Dark Web What Is the State of the Phishing Threats? 2017 report shows that phishing and social engineering techniques represented “98% of incidents and breaches that involved social action.” A whopping 95% of phishing attacks leading up to a breach involved malware installation. In general, in 66% of cases, malware installation occurs via email as attachments. The findings are based on a data set of 1616 incidents and 828 confirmed disclosures. Verizon Data Breach Investigations Email is the primary channel for malware delivery. Source: 2017 Verizon Data Breach Investigations Report Interestingly, according to data from organizations contributing to reports, 7.3% of more than 3 million unique users have been lured into clicking malicious link or opening an attachment. Moreover, 15% of those who fell victim once, were tricked for the 2nd time. 3% clicked more than twice. A small amount of users clicked more than 3 times. These stats shouldn’t be attributed solely to users’ gullibility, because threat actors are constantly improving the quality of their spoof emails. What is Driving Phishing Attackers? he findings on motivation of threat actors listed in Verizon DBIR are in line with observations made by other researchers: Other reasons adversaries engage in phishing include fun, ideology (hacktivism), and holding a grudge (ex-employees). 66% of cases involving social action are financially motivated, with espionage occupying the second place with 33% respectively. Motivation behind malware distribution and attacks according to 2017 Verizon Data Breach Investigation Report The Dark Web and the Shadow Economy of Phishing Business From an adversary prospective, phishing is an effective tool, powering their lucrative business. As already mentioned, they monetize in several ways, some of them staying invisible to general public. While most of us are using the visible web (the part of internet indexed by search engines ) or the Deep Web (the part of the web not indexed by search engines like your email account), adversary dealings, like selling victims’ personal data occur in the “walled off” segment of the internet, known as the Dark Web. One of the motivators for using the Dark Web is that it’s not accessible without special software. Its decentralization and greater anonymity of communication protocols are among other reasons why government agencies and and law enforcement are not able to regulate it stringently, with the exceptions of occasional takedowns of separate Dark Web websites. Still it doesn’t mean that Dark web is 100% anonymous and not monitored at all — on one of the websites can get you jailed. buying a bomb There is no lack of marketplaces where various illegal goods are sold, ranging from drugs to credit card credentials and malware. Payments are processed in (Bitcoin, Monero, etc.) which contributes to even greater anonymity, if certain precautions are met. Due to this, hacking communities are quite active on the Dark Web and one can find a variety of services for sale and hackers for hire. cryptocurrency It Is Easier Than Ever to Start a Phishing Business A big part of the Dark Web economy that supplies security researchers with new threats to work on every day is based on evolution of the malware business model. Nowadays coding skills are not a prerequisite for someone who decides to make money from distributing malware or enter the phishing business “niche”. The entry-level is considerably lower due to new types of offers promoted on the Dark Web and on some hacking forums on the visible web. They are known as Ransomware as a Service (RaaS) or Phishing as a Service (PhaaS). The business model is borrowed from legitimate software vendors. Basically, you no longer have to write malicious code yourself. You can buy it! Highly skilled malware authors do the hard work of creating a RaaS or PhaaS software that they offer to less experienced criminals. In some cases, they may go even further to develop a sort of affiliate platform that combines a stats dashboard and control panel their customers can use. Cyber crime is becoming more organized and structured, just like their opposition in infosec and AV industry. Adversaries implement organization models where each participant takes on certain set of tasks, from development of specific hacking tools, to marketing and distribution via numerous Dark web outlets. Hackers offer full scale services with support and infrastructure for rent, acting very much like software as a service (SaaS) companies. Virtually anyone who’s able to get on the Dark Web, can pay an RaaS author to start an extortion campaign of their own. RaaS distribution may be taken care of by purchasing a PhaaS product and a database of email addresses to send to. Threat authors use different payment models,from one-time payment to fixed revenue share percentage for every victim paying ransom. Some RaaS “products” are built on the basis of certain ransomware families and their further customization evokes more new strains that circulate on the web. Let’s take a glimpse at some of the Dark Web marketplaces that offer hacking tools and services. Dark web marketplaces offer guides on phishing business, malware distribution as well as stolen personal data. There is a number of marketplaces selling hacking tutorials and various types of personal data such as emails, credit card info, social security numbers etc. Sellers have ratings and buyers are able to leave reviews based on their experience, much like on legit websites across the visible web. Dark web actors embrace customer service practices by offering “satisfaction guarantee” policies and “support.” However, fraud is widespread on Dark web, it’s scammers trading with scammers, after all. This RaaS (Ransomware as a service website), called “Ranion” has been around for a while, offering configured and compiled ransomware tool along with Dark web based Command and Control Dashboard. It allows threat actors to operate the extortion business and collect ransom covertly . Ransomware authors are offering several packages with varying set of features, depending on price. They boast using unbreakable encryption too. Notice the phony disclaimer saying: “Our products are for educational purposes only” — fairly weak attempt at humor. Ranion RaaS main page Ranion Ransomware FAQ provides information for potential buyers, including the type of files it encrypts, support and paid addons. Ironically, RaaS authors even promise to take care of buyers’ privacy with their no-logging server policy. Ranion RaaS FAQ: support, privacy and other info to convince “potential customers” Finally, the most interesting section of Ranion RaaS website, Reviews. Site owners proudly link to legitimate security website that posted an article about their “product”. Bleepingcomputer Ranion RaaS Reviews section One more RaaS listing on one of the hacking forums I came across on Dark web. It is called “Princess” and has detection bypass and evasion functionality built into it. Crooks also claim that no free decryptor exists and won’t exist in future. Conditions listed in “Partnership” section resemble those of legitimate software vendors advertising their offer to affiliates on ad network, including commission structure. They propose 60% Revenue share deal between the criminal group and ransomware distributors, which is a pretty standard deal. Other traditional services that affiliates normally request from the program like partner dashboard,support and product localization are also provided. Princess RaaS authors recruiting distribution partners on Dark web hacking forum Dark web is also a place where less ethical hackers offer their services, here’s an example for you to take a look at. Rent-A-Hacker website contains “product packages” and hacker’s “CV” A Final Word on Phishing Business Email is one of the handiest inventions that accompanied the Internet, but at the same time it’s an Achilles heel of personal online security and IT infrastructure. Changes in the cybercrime ecosystem and growing availability of on-demand malware require new approaches from users and organizations. The old paradigm, which relied on endpoint protection and signature-based detections, isn’t viable in the present day threat landscape. Cyber crooks constantly innovate and a failure to keep up will most likely result in financial losses or data breaches. Modern enterprise security should be aimed at prevention, proactive monitoring and sandboxing techniques deployed across the vast infrastructure. An appropriate level of automation is crucial in order for IT teams to maintain control,visibility and take full advantage of email security frameworks. Companies investing in continuous employee training including , are more likely to avoid the consequences of network security attacks and identify employees whose safety skills may need improvement. simulated phishing attacks

Phishing Is Surprisingly Easy To Execute. How’s Your Phishing Security?

Generate and Pray: Using SALLMS to Evaluate the Security: Conclusion & References

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https://youtu.be/hSP9vZEdDZQ?embedable=true In the presentation above, Dominik Muhs, Senior Security Engineer from ConsenSys Diligence, provides an in-depth analysis of the components that make up an oracle system. Dominik presents this talk on behalf of Shayan Eskandari, CTO of Ether Capital. Before diving into this presentation, here are some important concepts to note. What is an Oracle? An oracle is a piece of blockchain infrastructure that connects blockchains to real-world data. Oracles help to fetch and verify data from multiple external sources. This data is then delivered to smart contracts, allowing them to be executed based on off-chain data. The Oracle Problem Blockchains and smart contracts are useful and exciting because they are decentralized, immutable, and censorship-resistant. However, blockchains cannot transmit data to and from any external system. External data is required for almost all use cases of smart contracts. Some of these use cases include stablecoins, prediction markets, identity, randomness, decentralized exchanges (DEXs), dynamic non-fungible tokens (NFTs), and, of course, price feeds. Such systems would require confidence in the origin of the real-world data. At the same time, a blockchain’s isolation and resulting inability to connect with real-world data is the exact quality that also gives it its security. The oracle problem can thus be defined as the conflict arising from the trustless execution of smart contracts and a blockchain’s overreliance on third-party oracles for external data. If oracles are centralised or corruptible, they become a single point of failure, potentially defeating the entire purpose of blockchain and smart contract technology. Oracle’s Modular Workflow Prior to writing the research paper, “ ”, and his colleagues came across the oracle problem while attempting to build a decentralised derivatives market as an academic exercise. Decentralized derivative markets are peer-to-peer marketplaces where derivatives are traded. In traditional finance, derivatives are contracts (or securities) that derive their value from a chosen asset’s performance. Some common types of derivatives include futures, options, and bonds. DeFi derivatives differ from their traditional counterparts in that they do not require a broker or a third party to ensure the contract is fulfilled. Instead, the terms can be programmed into smart contracts and automatically settled on-chain once the conditions have been met. Some examples of decentralized derivative markets include , , and . SoK: Oracles from the Ground Truth to Market Manipulation Shayan Synthetix dYdX Vega Protocol The main purpose of the paper is to divide smart contract oracle systems into separate parts or “modules”. Studying each module individually makes it much easier to analyse oracle design principles, possible attacks, and ways they can be mitigated. The modules are as follows: Ground Truth Data Sources Data Feeders Selection of Data Feeders Aggregation Dispute Phase – The first challenge of oracle design starts with a philosophical question: What is the truth? Is the truth subjective or objective? Ground Truth The “ground truth” refers to the exact piece of information that oracles would put on-chain. An example would be the real price of Ethereum. This could be an aggregated price from different data sources, such as a centralised exchange (CEX) like Gemini, or a decentralised exchange (DEX) like Uniswap. In the ground truth module, oracle designers try to find the best way of collecting raw data from various data sources and aggregate them to achieve a reasonable level of data quality. Oracle designers must try to distil the data in a way that is consumable for systems, and in a deterministic way, in which no randomness is involved. – Data sources are passive entities that store and measure the representation of the aforementioned ground truth. According to Dominik, examples of common types of data sources include: Data Sources Databases & API – Centralised exchange prices. Sensors: Blockchain-based supply chain systems Humans: Prediction markets Smart Contracts: On-chain markets, such as Uniswap as the oracle data source A combination of the above is also possible. Data sources are thus the quantifiers of the ground truth. For instance, if the ground truth is the price of Ethereum, then the data source is centralized exchange prices. – Data Feeders are responsible for transferring data from external or off-chain data sources to on-chain oracles. As such, it is crucial that a set of security provisions are made, such as source authentication and confidentiality. Data Feeders Data feeders themselves do not verify the reliability of the data. Instead, the external data is pushed through the feeders, which carry out security checks such as source authentication. Depending on the feeder, there are different ways of authenticating sources. In his presentation, Dominik cites the example of being connected to a , and authenticating the API (application programming interface), which uses with in order to have an attestation for the correctness of the HTTP data that is being gathered. Alternatively, and can be used. TEE is an environment for executing code separated from the main operating system. It enables end-to-end security and provides a trusted environment where data is stored, processed, and protected. However, in both cases, trust is allocated to third parties like the TLS Notary or the Intel chip manufacturer. REST API HTTPS TLS Notary Intel SGX Trusted Execution Environments (TEE) Freeloading Attacks and Other Threats Another security provision that data feeders need to meet is confidentiality to prevent common attacks such as “mirroring attacks” and “freeloading attacks” in oracle systems. Freeloading attacks occur when a data feeder copies data provided by feeders or a public off-chain source without verifying that the data is accurate. This way, the data feeder is able to maximise profits and minimize the work required to get the result. Mirroring attacks are a type of Sybil attack that can complement freeloading attacks. A Sybil attack is a type of attack in which a bad actor creates a large number of pseudonymous identities and uses them to gain a disproportionately large influence over the entire system. In the case of oracles, an attacker can simply collect data from a single centralized data source and copy the result across multiple nodes. This would result in the final data point largely relying on that single data source. According to Dominik, commit reveal schemes can be used to prevent such attacks as they help to ensure that no one else can “peek” at other data feeder submissions. This article provides more information about . Non-repudiation can also guarantee that a data feeder’s submission into the system cannot be manipulated or denied. This can be accomplished through to account for the possibility of corruption in the data submission process. commit reveal schemes on Ethereum cryptographic signature schemes – Aggregating all the data provided by data feeders would be very expensive if data feeders must be rewarded for every contribution made. However, according to Dominik, the resilience of the oracle system is known to increase with the number of data feeders inside the network. To form a community of data feeders, a selection process has to take place. There are several ways to select data feeders for an oracle network. In his presentation, Dominik elaborates on the different selection processes being used by oracles like , , and , as well as process from 2019. Selection of data feeders Chainlink MakerDAO BAND Protocol Tellor’s staked proof-of-work Tellor no longer uses Proof-of-Work. Tellor’s latest upgrade, named Tellor 360, continues to use a staking model, where reporters stake $1500 or $150 worth of TRB Tokens on Ethereum or Polygon respectively. Reporters providing good data get tips and rewards, while dishonest reporters risk losing their stake. To find out more, read and watch this space! More details on the Tellor 360 upgrade are coming soon. Important to note: this blog post Dominik also explained some of the shortcomings of these processes, including the example of B Protocol using a flash loan to sway the Maker V2 governance vote in order to add their own oracle to the data feeder allow list. Read more about this in by our Media Partner, Beincrypto. this article – Aggregation refers to the process of combining the selected data feeds into one single output. End users must be able to extract value from the data feeders. This can be done by applying different methods of statistics, such as calculating the mean or median of the given data. There are advantages and drawbacks to each statistical computation, and oracle designers must carefully select which to utilize. Aggregation – There are several ways of disputing incorrect data and punishing the providers of incorrect data. The point of reference for any dispute should be the correct data. Projects may make use of an economic game of staking where participants stake a certain amount of tokens to challenge an incoming piece of data. An outcome could be tentative first and only confirmed after a dispute window is completed. If a piece of data is disputed, the provider of the bad data could be removed or they could have their staked tokens confiscated or their reputation score slashed. Augur, a decentralized prediction market platform, and Asteria, which aims to build an options-based infrastructure for DeFi, are examples of protocols that dispute data this way. Dispute phase Another way to dispute data would be through a game of arbitrage. For example, when there is incorrect price data in a decentralised market, an arbitrage opportunity would arise due to the difference in prices being reported. In such cases, a miner could resolve the arbitrage trade. Miners are incentivised to resolve these trades due to the additional profit that can be made, also known as . MEV is a term used when miners can extract additional value by “jumping the queue” or reordering transactions within a block to complete trades. Miner Extractable Value (MEV) The Dark Forest Problem Towards the end of his presentation, Dominik refers to the “Dark Forest” problem. “Dark Forest” is a term popularized by Dan Robinson and Georgios Konstantopoulos from investment firm, Paradigm, in blog post. The term was inspired by the science fiction book, “The Dark Forest,” in which the dark forest is an environment where detection leads to certain death at the hands of predators. In the post, Dan likens the Ethereum mempools to a “dark forest”. Mempools are databases of all pending transactions. Once a transaction is confirmed, it is removed from the mempool. According to the “dark forest” concept, any pending transaction detected in the Ethereum mempool will be vulnerable to attacks by arbitrage bots. this Where do we go from here? According to Dominik, certain aspects of oracle system design, such as staking, must be strengthened. Oracles use their governance token for staking, the mechanism whereby users pledge their tokens to support a network’s improved operation in exchange for token rewards. This provides an additional layer of security to the oracle system by giving it more guarantees. For this to be effective, however, the token’s market capitalization must remain significant. If the token’s value crashes, the entire oracle system could be in danger of collapsing, and staking would prove counterproductive. The tokens must also be fairly and evenly distributed for the token value to maintain its integrity, which would improve the effectiveness of staking. Moving forward, the oracle industry also needs to examine potential attacks closely and develop the relevant strategies to prevent each one of them from happening in the future. More detailed information on oracle manipulation can be found in by ConsenSys Diligence. this Github article The Blockchain Oracle Summit was the world’s first conference to focus solely on the importance of oracle systems and their design. Leading oracle builders and researchers from across the industry gathered in Berlin to take deep dives into their work to address the biggest challenges. Find out more about Ether Capital: Ether Capital Website Ether Capital Twitter Shayan Eskandari Twitter Dominik Muhs Twitter

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