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Security Vulnerabilities 
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security advisory moderate For organizations that run a self-hosted Git platform, it’s no longer just about hosting static code repositories. Today, Git servers are responsible for deployment pipelines, API tokens, SSH keys, package repositories, and the automation scripts that push code directly. Confirm that the upgrade addresses known vulnerabilities but also provides production environments. . That makes them trusted systems within the development environment and attractive targets for attackers looking to move...
Jul 20, 2026
Server Securitydata privacy automation
data privacy automation Every system admin has lived through the same Monday morning ritual. A queue of forty tickets, half of them password resets, permission errors, or disk space warnings that any experienced technician could resolve in under two minutes. The other half require actual judgment. For years, automation promised that software would eventually sort the two apart on its own. That promise is now being tested in production Linux environments. . Early results are reshaping how IT teams think about tier-1...
Jul 17, 2026
Privacydata collection automation
data collection automation You're running a web scraping project to collect pricing data from e-commerce sites. You set up a pool of datacenter proxies, launch your scripts, and within minutes — banned . CAPTCHAs everywhere. Your data pipeline stops before it really begins. . It's a frustrating scenario that plays out daily in ad verification, market research, and multi-account management. The website doesn't know you're doing legitimate research or monitoring. It just sees traffic coming from IP ranges it recognizes as...
Jul 17, 2026
Security Trends security advisory social engineering
security advisory social engineering Business Email Compromise used to be a numbers game — mass-blasted emails, broken English, an obvious "URGENT WIRE TRANSFER" subject line. That era is over. Generative AI has turned BEC into a tailored, low-noise operation that mimics writing style, voice, and even video presence. This piece looks at what's actually changed under the hood, what defenders are testing in response, and why so many organizations are still structurally unprepared for it. . The Infrastructure Problem Nobody Wants to...
Jul 17, 2026
Security Trends cybersecurity Linux documentation
cybersecurity Linux documentation Linux operating systems have gained prominence due to their stability, adaptability, and excellent security options. In the case of developing documentation, designing cybersecurity dashboards, or educational material, visuals are of vital importance when it comes to making things clear. The use of icons allows one to understand the message regarding alerts, authorization, encryption, authentication, or the state of the system just by looking at the visual cue without having to read long...
Jul 17, 2026
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209
open sourcecyber defensethreat detectionThe Role of AI in Cyber Defense: Enhancing Security and Response
The technology is advancing at an unprecedented rate, fueling cybersecurity concerns. Experts have gone the extra mile to tackle this issue, but they will not realize AI's potential to deal with cyber threats. . Let's face it: Machine learning, data analytics, and automated response systems enable this intelligent tech to process vast amounts of information quickly and efficiently, surpassing human capabilities. They improve threat detection and response time and enable organizations to anticipate risks before they develop into serious incidents. AI technology is revolutionizing how organizations defend against threats such as phishing attacks and ransomware attacks , improving defense capabilities against all kinds of security issues. In this article, we'll outline artificial intelligence development's many roles in improving cybersecurity by exploring its capacities for proactive threat identification and effective vulnerability management. An Overview of Modern Cybersecurity Challenges Cybersecurity refers to safeguarding digital systems, networks, devices, and programs against any form of malicious attack, unauthorized access, or data breach that might threaten them in an increasingly digital world. Securing technological assets has never been more essential. These cyber-threats range from basic phishing scams to ransomware attacks, which can have devastating outcomes. Data theft, financial loss, privacy violations, and system downtime are just a few potential outcomes of system integrity breaches. Traditional security measures, such as firewalls, antivirus software, and intrusion detection systems , have traditionally provided digital protection. However, their capabilities often can't keep pace with cybercriminal innovation or sophistication—such as more stealthy attacks using advanced malware that bypass traditional detection methods—nor with all of the data and transactions going online, making monitoring and protecting everything efficiently an uphill struggle. Relying solely on traditional security measures is no longer sufficient. Organizations must adopt an all-encompassing and proactive cybersecurity strategy that includes multilayered defense strategies, cutting-edge technologies like Artificial Intelligence and Machine Learning for threat detection, and regular patching or updates for known vulnerabilities. How Does AI Impact the Cyber Security Domain? For an artificial intelligence development company, staying informed about how cybersecurity has changed since AI is necessary. AI in Open Source Security AI is reshaping open-source security by improving vulnerability detection, mitigating threats, and analyzing vast datasets. Traditional methods, like manual code reviews, often fail to address complex cyber threats. AI tools like OWASP Nettacker and the Artificial Intelligence-Driven Software Vulnerability Scanner automate vulnerability detection by continuously scanning repositories, identifying risks, and suggesting fixes. This accelerates response times and strengthens codebase security. In addition, AI excels at automating threat responses. Platforms like Snort leverage AI to identify network traffic anomalies and mitigate real-time risks. This reduces the burden on human teams while ensuring faster action against sophisticated attacks. AI also transforms data analysis. Open-source tools like ELK Stack (Elasticsearch, Logstash, Kibana) employ machine learning to sift through massive security logs, flagging critical anomalies that could otherwise go unnoticed. These capabilities make AI indispensable for organizations relying on open-source systems, especially in the context of national security. Given the widespread use of open-source technology across industries, AI integration is not just an advantage—it’s essential for fortifying systems against evolving cyber threats. AI Threat Detection Traditional security relies on predefined rules and signatures to detect threats. This approach was effective in the past butis no longer effective because it feels short-sighted when faced with new and unknown threats. Due to this concern, AI is now a valuable asset in threat detection. It possesses advanced ML algorithms that continuously analyze data in real time to spot unusual patterns or breaches immediately. AI rapidly recognizes things that humans would otherwise miss, such as suspicious user activity and unfamiliar network activity. Artificial intelligence development experts quickly flag employees logging on at unusual hours or accessing files without authorization as suspicious activity - helping prevent potential unauthorized access before it happens! It learns from past data to detect new attacks, such as zero-day exploits that otherwise might go undetected. Automating Responses AI has again shown its worth by automating responses to cyber attacks. As security alerts flood in, human teams often become overwhelmed; AI automatically assesses each threat's severity before taking necessary actions. This intelligent tech quickly responds to sophisticated ransomware attacks by isolating infected systems from networks and stopping the further spread of the infection. Those who automated cyber threat responses have a solid improvement in mitigating cyber threats quickly and minimizing loss due to them. Predictive Analytics AI does more than just react to attacks; it predicts them. By applying predictive analytics driven by AI, large volumes of data can be analyzed to identify looming vulnerabilities and emerging attack patterns ahead of time and give early warning of cyber threats in general. Predictive analytics also helps organizations prepare contingency plans, improving their ability to pre-emptively neutralize risks. AI can identify weak points within an organization's infrastructure and helps rank orders of where patches are needed first. This proactive approach helps organizations take steps to prevent the attack before it happens and avoid a costly breach. StrengthenAuthentication Systems Authentication is a cornerstone of cybersecurity, yet traditional password-based methods no longer suffice. AI technology offers more secure yet convenient authentication solutions such as biometric recognition and behavioral biometrics for added peace of mind. AI-enhanced authentication systems are constantly evolving to counter new hacking techniques, ensuring user security remains a step ahead. AI-powered authentication includes fingerprint scans, facial recognition software, and keyboard typing analysis to verify users. Adding multiple layers of verification using AI makes it much more difficult for cybercriminals to gain unauthorized entry. AI-driven authentication systems leverage continuous learning to refine their accuracy and detect unusual login patterns, further strengthening security. AI constantly adapts and learns as it recognizes patterns in how users interact with systems, making breaches even harder. If you're exploring modern authentication tools that can help secure your systems, this overview of top identity verification software is a helpful resource to compare leading solutions in the space. Fraud Detection/Prevention Where rapid detection of suspicious behavior is crucial, artificial intelligence is also making tremendous progress toward fraud prevention in sectors such as banking and e-commerce. AI-powered fraud detection systems may, therefore, progressively learn from every new transaction to identify minor trends suggesting possible hostile conduct. AI's analytical abilities enable it to rapidly examine transaction patterns for anomalies—such as abnormally high transactions or requests for user location—that would point to fraudsters working behind them. Every transaction teaches AI, and over time, it may become even more skilled at spotting fraud. Integrated with machine learning models, fraud detection technologies find dishonest behavior and adapt to new frauds. By leveraging artificial intelligence technology, businesses canquickly detect and prevent fraud, minimizing losses and safeguarding both consumers and organizations. Advanced Malware Detection Unfortunately, malware authors simply adapt and find new methods to evade their discovery while making traditional security techniques lose their effectiveness. On top of that, it becomes an answer: Intelligent systems focus not just on their known malware signatures but also on detecting specific behavior. If certain things sound suspicious- for example, actions about encrypting files- the communicational activity with unidentified outward servers- AI would characterize it as malware based upon earlier detections; it has never seen anything different. To Sum Up The promising role of artificial intelligence development in enhancing cybersecurity can’t be overstated. AI has completely changed our approach to cyber threats from detecting to predicting future risks. The future is still uncertain. We might encounter many more complex digital threats that this intelligent technology will struggle to deal with. But for now, businesses must integrate and maximize security systems. . Explore how AI is revolutionizing cyber defense by enhancing threat detection, response, and vulnerability management.. technology, advancing, unprecedented, fueling, cybersecurity, concerns, experts. . MaK Ulac
Dec 26, 2024
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Security Trends
209
cybersecurityopen sourcecyber defenseAI Integration: Enhancing Business Automation and Cybersecurity Solutions
Artificial Intelligence in business is slowly becoming the norm and necessary in the competitive struggle. Today, it is a powerful tool for developing companies, solving business problems, performing deep analytics, and automating processes. . In this article, we’ll detail how application of Artificial Intelligence in business helps its development and how smart technologies can be introduced into business practice and cybersecurity. What is Artificial Intelligence? In plain English, computer systems can self-learn and carry out highly specialized tasks previously only possible for humans. AI reproduces human intellectual behavior, but it never gets tired, does not experience emotions, and does not make mistakes. AI in business helps automate routines, process massive amounts of data, predict decisions, make reports, and form conclusions. In the past, humans did all this work, but today, machines are much better at it. One of the most practical implementations is using AI chatbots for businesses to automate customer interactions, improve lead qualification, and enhance user experience. What Is the Role of Open Source in AI-Based Cybersecurity Advancements? Open-source software and tools have been a significant force in the rise of Artificial Intelligence and Machine Learning for cybersecurity. Open-source software and tools have democratized access to advanced AI technologies, allowing researchers and developers to collaborate without being constrained by proprietary systems. This collaborative environment has enabled the rapid development of AI algorithms and ML models, which are crucial for identifying, analyzing, and responding to cyber threats with unprecedented accuracy and speed. Open-source platforms allow cybersecurity solutions to adapt rapidly to new threats. They also benefit from the collective knowledge and contributions of an international community. This collaborative approach to development fosters innovation and ensures that cybersecurity technologies canevolve to adapt to ever-changing cyber threats. The transparency of open-source projects is also critical in cybersecurity. This allows various experts to evaluate and validate AI models rigorously. It ensures that these technologies are robust and secure and do not have hidden vulnerabilities. This is especially important, considering the sophistication of cyberattacks. AI-driven systems can only be exploited with proper scrutiny. Open Source facilitates an equitable distribution of the latest cybersecurity tools. This allows organizations of any size to defend themselves against cyber threats effectively. It also has the advantage of improving the security posture of the entire digital ecosystem as it enables smaller entities to deploy advanced AI-driven defense mechanisms. Fundamental AI Technologies in Business Machine Learning Machine Learning is an AI technique that improves systems' outcomes by learning from large databases. The key difference between machine learning and standard algorithms is adaptability and constant development. The more data and information an algorithm collects, the more its analytics will be more accurate. Examples of using machine learning in business: Chatbots that advise users. Machine learning helps develop a chatbot's knowledge base, and after 6-12 months, a virtual consultant can answer almost all questions. Personalization and improving customer experience. Machine learning improves customer engagement and satisfaction by offering personalized product selections based on recent purchases. Checking resumes and documentation. Machine learning makes it possible to create a profile of an ideal candidate, simplify the hiring process, and speed up the analysis of resumes. As a result, the amount of routine for HR specialists is reduced. Neural networks The most frequent representatives of Artificial Intelligence in business. It is a program code that processes data and imitates the work of the human brain. Neural networks have broadapplications in design, marketing, copywriting, customer service, statistics, calculations, industry, and banking. For companies aiming to enhance their AI capabilities, implementing agentic RAG can optimize retrieval and generation tasks, leading to more efficient and accurate AI-driven solutions. They are great at writing SEO texts, translating articles, and generating media. And at the same time, they do everything cheaper and faster. What can the most straightforward and most inexpensive neural network do? Writes texts based on specified keywords; Creates product descriptions, titles, and meta tags; Makes excerpts from texts; Generates images from text descriptions; Creates scripts for YouTube. NLP (natural language processing) NLP is a ML technology that allows computers to understand human language. Modern companies have huge amounts of voice and text data—email correspondence, messages, social media news, video, audio, etc. NLP technology processes all of this and uses it to the advantage of the business. For example, NLP can recognize three basic types of emotions - positive, negative, and neutral - with 95% accuracy. If predictions are to be believed, by 2025, half of online advertising will be based on this technology. Disney has already determined whether viewers like content available on a streaming platform. Ping An claims to have cut financial losses on loans by 60% thanks to new algorithms. As organizations increasingly rely on AI-generated content, verifying the authenticity and origin of text has become an important governance consideration. An AI detector can help identify machine-generated content and support content review, compliance, and risk-management processes where transparency and trust are critical. Robotics Businesses get robotic hotel administrators, goods pickers, and unmanned car drivers by combining robotics and AI. Robots with intelligence monitor their accuracy and performance, train, and improve themselves. Examples ofthe use of robotics in business: Medical robots. The most famous is the Da Vinci robotic surgeon, who used to perform tens of thousands of complex heart and brain surgeries worldwide every day. Software robots, or robotization. This is software code that mimics the user's work. In CRM companies, "robots" send emails, create documents according to a template, and schedule daily calls and meetings. Unmanned cars. One of the brightest and most popular technologies in robotics. On the roads, robocars are showing impressive promise. In the future, most cars will be driven by autopilots, significantly improving road safety. How Can I Implement AI in Business Practice? To briefly describe the process of implementing AI into business practice, the steps are as follows: Assessing needs and capabilities. Find out what Artificial Intelligence can do, and then identify problems that can be solved. Select the right technologies and tools. AI systems must meet business needs and objectives. Evaluate the potential financial value of implementing each AI technology and select the most promising and profitable one for your niche. Testing and implementation. The time to test AI depends on the complexity of the tool itself and the industry. The timeframe can range from 2-3 weeks to several months. During the testing period, monitor customer satisfaction and employee performance. If sales and productivity increase, order processing time decreases, and feedback improves, the right AI services are selected and implemented. Our Final Thoughts on Integrating AI into Business Practices Artificial Intelligence integration in business processes represents more than just a trend but an essential transformation in how companies function and thrive in today's digital environment. As we've seen, AI applications go beyond automating repetitive tasks to providing advanced analytic insights and personalized interactions that provide exceptional customer experiences. AI adoption involvesan exhaustive process of examining business needs, selecting suitable technologies, and testing to ensure alignment with business goals. AI's capacity to foster innovation, efficiency, and competitive advantage makes smart technologies essential for businesses to remain relevant and thrive in today's ever-evolving digital landscape. . Integrating AI into business frameworks boosts operational efficiency and drives innovation, enabling strategic decisions and optimized resource management. Artificial Intelligence, Business Operations, Open Source Security, AI Cybersecurity, Automation Solutions. . Brittany Day
Aug 17, 2024
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Security Trends
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security practicesthreat analysismalwareNoodle RAT Threat Analysis: Strategies For Linux Security
A new backdoor, "Noodle RAT" has caused widespread alarm across the cybersecurity landscape. Research highlights this previously undisclosed malware used by Chinese-speaking groups engaged in cybercrime and espionage activities. . This article seeks to provide a thorough understanding of this threat for Linux administrators who wish to better protect themselves against Noodle RAT and similar attacks. We'll focus specifically on the Linux variant of this cross-platform malware and how it infects targeted systems. Understanding Noodle RAT Since 2022, Noodle RAT has been under scrutiny due to targeted attacks in the Asia-Pacific region. At first, it was thought to be part of existing malware such as Gh0st RAT or Rekoobe, but intensive research revealed it as being brand new. The malware, available on Windows and Linux, has been employed by Chinese-speaking groups for espionage and cybercrime activities, demonstrating its widespread impact. Noodle RAT typically exhibits capabilities such as downloading/uploading files/running additional in-memory modules, and acting as TCP proxy on infected computers, underscoring its widespread usage among target systems. The Linux Version of Noodle RAT: How Does It Infect Targeted Systems? Linux.NOODLERAT stands out from its Windows counterpart through its design and capabilities, which have been widely employed for financial gain and espionage purposes by various groups for their ends. Employed for different motivations, including financial gains or spying operations, its design features include reverse shell functionality, file download/upload features, scheduling execution of scheduled processes, and SOCKS tunneling capabilities. After infiltrating public-facing applications, the backdoor copies itself to an identified location before performing process name spoofing and connecting back with its C&C server per predefined settings, making its design unique from its Windows counterpart regarding design vs. capabilities. Practical Advice for ProtectingAgainst Noodle RAT and Similar Threats With cyber threats evolving almost daily, Linux administrators must take proactive measures to ward off threats like Noodle RAT. Here are several practical steps you can take to reinforce the security posture of your systems: Implement Comprehensive Access Controls: Comprehensive access controls and user permissions can significantly limit unauthorized access and help stop the installation and execution of malicious payloads. Prioritize Regular System Updates and Patch Management: Timely installation of software updates and security patches can address known vulnerabilities exploited by backdoors like Noodle RAT. Implement Strong Authentication Measures: Establishing multifactor authentication and enforcing robust password policies are great strategies for protecting against any unauthorized access attempts. Utilize Network Segmentation: Dividing the network into distinct zones according to traffic patterns and user roles can help contain malware spread and limit its impact in case of breach. Implement Intrusion Detection and Prevention Systems: Installing and configuring effective intrusion detection and prevention systems is one way to detect and respond quickly to attempted infiltration by Noodle RAT or similar threats. Utilize Behavior-Based Monitoring: Behavior-based monitoring tools can enable administrators to detect suspicious and potentially malicious behaviors that indicate backdoor activities. Regular Security Audits and Penetration Testing: Conducting periodic security audits and penetration tests is one way to identify vulnerabilities before threat actors exploit them. User Education and Awareness Programs: Raising users' awareness of the potential dangers of social engineering tactics and phishing attacks can significantly lower the odds of successful backdoor installations. Our Final Thoughts on Noodle RAT & Preventing Attacks Noodle RAT's rise as an emerging backdoor threatunderscores the necessity of strong cybersecurity measures for Linux systems. By understanding its functionality and employing proactive security practices to strengthen defenses against this malicious malware, administrators can better protect themselves and reduce the risks from falling victim. As the cyber threat landscape changes rapidly, remaining vigilant and proactive when protecting essential infrastructure and sensitive data against emerging threats like Noodle RAT is imperative for maintaining and securing its integrity and safety. . Gain insights on Noodle RAT's impact on Linux systems and strategies to enhance security against this new backdoor threat.. backdoor, noodle, rat', caused, widespread, alarm, across, cybersecurity, landscape, researc. . Dave Wreski
Jun 11, 2024
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Hacks/Cracks
82
cyber defensenational securitysoftware securityUS Cyber Contest: AI Enhancing National Security And Software Safeguards
The White House launched a multimillion-dollar cyber contest to use artificial intelligence (AI) to detect and fix security vulnerabilities in the U.S. government's digital infrastructure in response to hackers' growing use of AI. . This strategic endeavor serves as a crucial step in improving national cybersecurity defenses and is a reaction to the rising worry about the harmful use of AI in cyberattacks. "The Linux Foundation's Open Source Security Foundation (OpenSSF), a project under its wing, will play a crucial role in ensuring that the winning software code immediately helps to strengthen the country's most crucial software systems. " . This calculated initiative stands as a vital move towards enhancing the country’s cybersecurity measures and leveraging artificial intelligence.. National Security, AI Cybersecurity, Software Protection, Open Source Solutions. . Brittany Day
Aug 14, 2023
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Government
209
cyber defensemobile securityremote workMobile Security Threats from APT Groups in Remote Work Environment
State-backed APT groups are increasingly targeting mobile devices in this new remote work environment. This article explores how the industry is fighting back. . The cyber defence industry is finally turning its attentions toward mobile devices as Covid-19 shines a light on remote working trends and strains . Unfortunately, they’re already 10 years behind the world’s most elite Advanced Persistent Threat (APT) contingent. While this period of lockdown, working from home, and siloed digital infrastructures have undoubtedly caught the eye of the most sophisticated – often state-run – hacking operations, it would be a mistake to think that such a focus is only just taking off. . The digital security sector is prioritizing the protection of handheld devices amid increasing risks from government-sponsored APT factions in flexible work environments.. Mobile Device Security, Cyber Defense Industry, APT Threats, Remote Work Threats. . Brittany Day
Jun 24, 2020
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Security Trends
82
cyber defenserisk assessmentcybersecurity legislationAnalyzing Hacking Back Risks in Cybersecurity Legislation
Sometimes when tech policymakers try to solve a problem, their proposed cure would only make matters much worse. That’s certainly the case with draft US legislation that would give victims of cyberattacks the chance to hunt their suspected attackers down. . Known as the Active Cyber Defense Certainty Act, or ACDC for short, the bill aims to let victims try to track down attackers by entering the systems of organizations they suspect the hackers have used to mount assaults. Often, these organizations may be other companies that are unaware their computers have been compromised. An existing US law forbids this kind of pursuit, which is known as “hacking back.” Only a few government agencies, like the FBI, have the authority to hunt down suspected hackers in this way. Supporters of the bill, which was recently introduced in the US Congress, say the FBI and other government agencies are already overwhelmed by an onslaught of cyberattacks, including “ransomware” that has paralyzed computer systems in cities like Atlanta and Baltimore and massive data thefts at large companies like the Marriott hotel chain. In theory, giving businesses and individuals the right to do their own hunting would support the agencies' efforts. The link for this article located at MIT Technology Review is no longer available. . Examining the proposed Active Cyber Defense Certainty Act and its implications for cybersecurity and legislation.. Active Cyber Defense Certainty Act,Cybersecurity Risks,Hacking Back Implications. . Brittany Day
Jun 24, 2019
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Government
82
cybersecuritycyber defensesecurity leadershipNew South Wales Cyber Security Initiative To Boost Cyber Defense
The New South Wales government has launched Cyber Security NSW in a bid to consolidate and lift the cyber capability of state entities. . To be led by chief cybersecurity officer Tony Chapman, who will perform the functions previously undertaken by the NSW government chief information security officer, Cyber Security NSW will sit within the Department of Customer Service. According to state government chief information and digital officer Greg Wells, the new initiative will "cement the leadership and coordination role needed to enhance cybersecurity and related decision-making across the NSW government". The link for this article located at ZDNet is no longer available. . Queensland unveils Safety Tech QLD to bolster protection measures for local organizations.. Cybersecurity Initiative, Security Leadership, Cyber Defense, NSW Government. . Brittany Day
May 20, 2019
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Government
82
cyber defensenational securityattack preventionNCSC Reports Tackling 10 Cyber Attacks Weekly Since Year 2016
The UK’s National Cyber Security Centre (NCSC) has blocked more than 10 cyber-attacks per week in its first two years of operation, blaming nation states for the majority of incidents.. The government body was spun out of GCHQ in 2016 with a goal of making the UK one of the safest places to live and work online. The link for this article located at InfoSecurity is no longer available. . The government body was spun out of GCHQ in 2016 with a goal of making the UK one of the safest plac. national, cyber, security, centre, (ncsc), blocked, cyber-attacks. . Brittany Day
Oct 17, 2018
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Government
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