Recent Evolution of Browser-based Cyber Threats, and What to Expect Next

In 2024, browser security faced some of the most advanced cyber threats to-date. As enterprises continue to transition to and from remote work environments, relying on SaaS platforms, cloud-based applications, hybrid work setups, and BYOD policies, attackers have become hyperfocused on the browser as the connective tissue linking and supporting almost all work and personal activities.  

The rise of AI-powered attacks, abusive cloud hosting services, phishing-as-a-service (PhaaS), and zero-day vulnerabilities that focus on enterprise browsers have underscored the need for a new approach to browser security. Traditional network and endpoint security tools alone are no longer enough. Menlo Security’s annual “State of Browser Security Report” reveals a significant surge in browser-based attacks, particularly those utilizing artificial intelligence (AI) and sophisticated impersonation methods. 

Key Research Findings 

The modern browser transcends its traditional role as a web access tool; it’s now a primary entry vector for advanced cyberattacks. Attackers are increasingly leveraging browser vulnerabilities to pilfer sensitive data and circumvent conventional security measures. Menlo researchers identified a dramatic 140% surge in browser-based phishing attacks year-over-year, coupled with a 130% increase in zero-hour phishing incidents specifically. 

Credential phishing continued to run rampant in 2024, largely because traditional security measures like firewalls, secure web gateways, and antivirus tools remain ineffective against these, and other sophisticated techniques used by cybercriminals. In fact, six days is the average window of exposure before legacy security tools can detect threats from zero-hour phishing attacks. While many enterprises have endeavored to improve browser security, they tend to focus on security at the network or endpoint level, which are not equipped to combat evasive threats like obfuscating malicious code, fileless malware and memory-only payloads. These techniques hide malicious activity within seemingly legitimate web traffic, making detection more difficult.  

Cloud-network services have attempted to mitigate the growing problem of browser-based attacks, but they often introduce added complexity and significant management costs without delivering robust protection against advanced phishing tactics. Compounding these challenges is the escalating trend of attackers exploiting cloud services themselves to host malicious content, including phishing sites and ransomware. Notably, AWS and CloudFlare accounted for nearly 50% of all instances of abused cloud hosting in 2024. This concentration underscores the allure of major cloud providers as targets for malicious actors who seek to leverage their extensive infrastructure for illicit activities, highlighting a critical security gap that existing solutions are failing to adequately address. 

Continuing Trends 

The data in the Menlo State of Browser Security Report is a clear indication of the current threat landscape, and what enterprises can expect in 2025 and beyond. Here are our research-based predictions for the months to come: 

1.Ransomware will continue to reign supreme. Ransomware will remain a highly prolific attack type, with cybercriminals targeting critical infrastructure to extract financial gains. We expect threat actors to increasingly use browser-based attacks to deploy ransomware, targeting sectors like healthcare, energy and transportation, and using the advanced techniques described above to bypass traditional defenses. The significant impact of ransomware attacks, such as the phishing campaign against Change Healthcare in 2024, highlights the need for organizations to prioritize browser security, adopt strong security measures and stay updated with the latest threat intelligence and business continuity protocols.  

2.AI-driven deepfakes will aid in bypassing traditional security tools. The volume of AI-driven cyber fraud has not yet reached its peak – we will see this attack type continue to rise in 2025 and beyond. Scam activities such as fake AI tools posing as legitimate platforms offering premium AI services will be used to steal login credentials and personal data, or direct users to phishing forms. Exploitation of user trust through sophisticated social engineering techniques will be key to targeting social media platforms and search engines.  

3.The cyber gap between small and large businesses will continue, leaving smaller businesses more vulnerable to attack. Larger enterprises are among the first to begin incorporating browser security strategies and security tooling that incorporates AI, helping with defenses that leave too much room for human error. On the other hand, we will see a larger proportion of small businesses continue to be affected by ransomware and other browser-based threats due to fewer resources, lack of dynamic security controls in the browser, and their inability to effectively monitor user behavior. Organizations will also start to leverage AI to level out their Security Operations Centers (SOCs), so that they don’t need as many resources to run it. Regardless of size, browser security is no longer optional but a fundamental survival strategy requiring proactive protection and preventative security.  

4.Threats to edge and IoT devices will rise. Edge and Internet of Things (IoT) devices are becoming prime targets for cybercriminals, particularly due to their often-limited security measures and widespread use in both personal and corporate settings. From smart cameras and wearables to home assistants, there will be more zero-day vulnerabilities exploited in the wild, with threat actors identifying and exploiting these weaknesses to gain control of these devices, use them for DDoS attacks and other malicious activities. 

5.Left unsecured, remote and hybrid environments will exacerbate insider threats. In the months to come, insider threats will increasingly originate from well-intentioned users who fall victim to sophisticated targeted attacks, exacerbated by remote and hybrid work environments. New tools and technologies will emerge to assist users in avoiding these risks, removing the burden of identifying and mitigating potential risks on their own. These tools will be able to detect malicious activity and perform far above the capacity of manual human analysis.  

Browser security will remain a critical area of focus for both security teams and end users, affecting both equally. The cyber threat landscape is shifting quickly, driven by advancements in technology such as AI and also changes in how and where people work. Cybercriminals are constantly refining their attack tactics – organizations must be doing the same on the defensive side, looking to implement robust security measures, prioritizing browser safety, and leveraging innovative tools to detect and thwart threats.  

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Join AWS Cloud Infrastructure Day to learn cutting-edge innovations building global cloud infrastructure

I want to introduce the AWS Cloud Infrastructure Day to provide a comprehensive showcase of latest innovations in AWS cloud infrastructure. This event will highlight cutting-edge advances across compute, artificial intelligence and machine learning (AI/ML), storage solutions, networking capabilities, serverless, and accelerated technologies, and global infrastructure.

Join us for AWS Cloud Infrastructure Day, a free-to-attend one-day virtual event on May 22, 2025, starting at 11:00 AM PDT (2:00 PM EDT). We will stream the event simultaneously across multiple platforms, including LinkedIn Live, Twitter, YouTube, and Twitch.

Here are some of the highlights you can expect from this event:

Willem Visser, VP of EC2 Technology will open with the introduction of the AWS journey since 2006, when Amazon Elastic Compute Cloud (Amazon EC2) was launched with the goal of customer-obsessed innovation. He will speak about the progress made over nearly two decades in cloud infrastructure to support both startups and enterprise workloads based on scale, capacity, and flexibility.

You can learn how AWS developed beyond computing instances to create a complete cloud infrastructure, including the parallel evolution of services like storage and networking capabilities.

Todd Kennedy, Principal Engineer, GoDaddy, will share GoDaddy’s Graviton adoption journey and the benefits it reaped from Graviton. Todd will walk through an example to demonstrate moving Rust workloads to Graviton. Learn how GoDaddy achieved 40 percent compute cost savings and over 20 percent performance gains.

This event covers a variety of topics related to AWS Cloud infrastructure. Here are interesting topics that caught my interest:

  • Generative AI at the edge – You can learn how to select, fine-tune, and deploy small language models (SLMs) for on-premises and edge use cases due to data residency requirements using AWS hybrid and edge services.
  • Serverless for agentic AI auditability – You can learn how AWS Step Functions and AWS Lambda transform opaque agentic AI system operations into transparent, auditable workflows.
  • Accelerated computing – You can get a close look at AWS innovation across silicon, server, and data centers and learn how customers are using AI chips. Learn how you can get started and reduce your generative AI costs.
  • Networking capability – You can learn how AWS infrastructure—from physical fiber to software-defined networking—enables unparalleled performance and reliability at global scale. The session covers modern application networking patterns while emphasizing secure connectivity solutions for hybrid environments.

This event is perfect for technical decision-makers and developers and offers deep technical insights and hands-on demonstrations of the latest AWS Cloud infrastructure solutions.

To learn more details, review the event schedule and register for AWS Cloud Infrastructure Day.

Channy


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Amazon Inspector enhances container security by mapping Amazon ECR images to running containers

When running container workloads, you need to understand how software vulnerabilities create security risks for your resources. Until now, you could identify vulnerabilities in your Amazon Elastic Container Registry (Amazon ECR) images, but couldn’t determine if these images were active in containers or track their usage. With no visibility if these images were being used on running clusters, you had limited ability to prioritize fixes based on actual deployment and usage patterns.

Starting today, Amazon Inspector offers two new features that enhance vulnerability management, giving you a more comprehensive view of your container images. First, Amazon Inspector now maps Amazon ECR images to running containers, enabling security teams to prioritize vulnerabilities based on containers currently running in your environment. With these new capabilities, you can analyze vulnerabilities in your Amazon ECR images and prioritize findings based on whether they are currently running and when they last ran in your container environment. Additionally, you can see the cluster Amazon Resource Name (ARN), number EKS pods or ECS tasks where an image is deployed, helping you prioritize fixes based on usage and severity.

Second, we’re extending vulnerability scanning support to minimal base images including scratch, distroless, and Chainguard images, and extending support for additional ecosystems including Go toolchain, Oracle JDK & JRE, Amazon Corretto, Apache Tomcat, Apache httpd, WordPress (core, themes, plugins), and Puppeteer, helping teams maintain robust security even in highly optimized container environments.

Through continual monitoring and tracking of images running on containers, Amazon Inspector helps teams identify which container images are actively running in their environment and where they’re deployed, detecting Amazon ECR images running on containers in Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS), and any associated vulnerabilities. This solution supports teams managing Amazon ECR images across single AWS accounts, cross-account scenarios, and AWS Organizations with delegated administrator capabilities, enabling centralized vulnerability management based on container images running patterns.

Let’s see it in action
Amazon ECR image scanning helps identify vulnerabilities in your container images through enhanced scanning, which integrates with Amazon Inspector to provide automated, continual scanning of your repositories. To use this new feature you have to enable enhanced scanning through the Amazon ECR console, you can do it by following the steps in the Configuring enhanced scanning for images in Amazon ECR documentation page. I already have Amazon ECR enhanced scanning, so I don’t have to do any action.

In the Amazon Inspector console, I navigate to General settings and select ECR scanning settings from the navigation panel. Here, I can configure the new Image re-scan mode settings by choosing between Last in-use date and Last pull date. I leave it as it is by default with Last in-use date and set the Image last in use date to 14 days. These settings make it so that Inspector monitors my images based on when they were running in the last 14 days in my Amazon ECS or Amazon EKS environments. After applying these settings, Amazon Inspector starts tracking information about images running on containers and incorporating it into vulnerability findings, helping me focus on images actively running in containers in my environment.

After it’s configured, I can view information about images running on containers in the Details menu, where I can see last in-use and pull dates, along with EKS pods or ECS tasks count.

When selecting the number of Deployed ECS Tasks/EKS Pods, I can see the cluster ARN, last use dates, and Type for each image.

For cross-account visibility demonstration, I have a repository with EKS pods deployed in two accounts. In the Resources coverage menu, I navigate to Container repositories, select my repository name and choose the Image tag. As before, I can see the number of deployed EKS pods/ECS tasks.

When I select the number of deployed EKS pods/ECS tasks, I can see that it is running in a different account.

In the Findings menu, I can review any vulnerabilities, and by selecting one, I can find the Last in use date and Deployed ECS Tasks/EKS Pods involved in the vulnerability under Resource affected data, helping me prioritize remediation based on actual usage.

In the All Findings menu, you can now search for vulnerabilities within account management, using filters such as Account ID, Image in use count and Image last in use at.

Key features and considerations
Monitoring based on container image lifecycle – Amazon Inspector now determines image activity based on: image push date ranging duration 14, 30, 60, 90, or 180 days or lifetime, image pull date from 14, 30, 60, 90, or 180 days, stopped duration from never to 14, 30, 60, 90, or 180 days and status of image running on the container. This flexibility lets organizations tailor their monitoring strategy based on actual container image usage rather than only repository events. For Amazon EKS and Amazon ECS workloads, last in use, push and pull duration are set to 14 days, which is now the default for new customers.

Image runtime-aware finding details – To help prioritize remediation efforts, each finding in Amazon Inspector now includes the lastInUseAt date and InUseCount, indicating when an image was last running on the containers and the number of deployed EKS pods/ ECS tasks currently using it. Amazon Inspector monitors both Amazon ECR last pull date data and images running on Amazon ECS tasks or Amazon EKS pods container data for all accounts, updating this information at least once daily. Amazon Inspector integrates these details into all findings reports and seamlessly works with Amazon EventBridge. You can filter findings based on the lastInUseAt field using rolling window or fixed range options, and you can filter images based on their last running date within the last 14, 30, 60, or 90 days.

Comprehensive security coverage – Amazon Inspector now provides unified vulnerability assessments for both traditional Linux distributions and minimal base images including scratch, distroless, and Chainguard images through a single service. This extended coverage eliminates the need for multiple scanning solutions while maintaining robust security practices across your entire container ecosystem, from traditional distributions to highly optimized container environments. The service streamlines security operations by providing comprehensive vulnerability management through a centralized platform, enabling efficient assessment of all container types.

Enhanced cross-account visibility – Security management across single accounts, cross-account setups, and AWS Organizations is now supported through delegated administrator capabilities. Amazon Inspector shares images running on container information within the same organization, which is particularly valuable for accounts maintaining golden image repositories. Amazon Inspector provides all ARNs for Amazon EKS and Amazon ECS clusters where images are running, if the resource belongs to the account with an API, providing comprehensive visibility across multiple AWS accounts. The system updates deployed EKS pods or ECS tasks information at least one time daily and automatically maintains accuracy as accounts join or leave the organization.

Availability and pricing – The new container mapping capabilities are available now in all AWS Regions where Amazon Inspector is offered at no additional cost. To get started, visit the AWS Inspector documentation. For pricing details and Regional availability, refer to the AWS Inspector pricing page.

PS: Writing a blog post at AWS is always a team effort, even when you see only one name under the post title. In this case, I want to thank Nirali Desai, for her generous help with technical guidance, and expertise, which made this overview possible and comprehensive.

— Eli


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AWS Weekly Roundup: Strands Agents, AWS Transform, Amazon Bedrock Guardrails, AWS CodeBuild, and more (May 19, 2025)

Many events are taking place in this period! Last week I was at the AI Week in Italy. This week I’ll be in Zurich for the AWS Community Day – Switzerland. On May 22, you can join us remotely for AWS Cloud Infrastructure Day to learn about cutting-edge advances across compute, AI/ML, storage, networking, serverless technologies, and global infrastructure. Look for events near you for an opportunity to share your knowledge and learn from others.

What got me particularly excited last Friday was the introduction of Strands Agents, an open source SDK that you can use to build and run AI agents in just a few lines of code. It can scale from simple to complex use cases, including local development and production deployment. By default, it uses Amazon Bedrock as model provider, but many others are supported, including Ollama (to run models locally), Anthropic, Llama API, and LiteLLM (to provide a unified interface for other providers such as Mistral). With Strands, you can use any Python function as a tool for your agent with the @tool decorator. Strands provides many example tools for manipulating files, making API requests, and interacting with AWS APIs. You can also choose from thousands of published Model Context Protocol (MCP) servers, including this suite of specialized MCP servers that help you get the most out of AWS. Multiple teams at AWS already use Strands for their AI agents in production, including Amazon Q Developer, AWS Glue, and VPC Reachability Analyzer. Read it all in Clare’s post.

Strands Agents SDK agentic loop

Last week’s launches
Here are the other launches that got my attention:

Additional updates
Here are some additional projects, blog posts, and news items that you might find interesting:

  • Securing Amazon S3 presigned URLs for serverless applications – Focusing on the security ramifications of using Amazon S3 presigned URLs, explaining mitigation steps that developers can take to improve the security of their systems using S3 presigned URLs, and walking through an AWS Lambda function that adheres to the provided recommendations.
    Architectural diagram.
  • Running GenAI Inference with AWS Graviton and Arcee AI Models – While large language models (LLMs) are capable of a wide variety of tasks, they require compute resources to support hundreds of billions and sometimes trillions of parameters. Small language models (SLMs) in contrast typically have a range of 3 to 15 billion parameters and can provide responses more efficiently. In this post, we share how to optimize SLM inference workloads using AWS Graviton based instances.
    AWS Graviton processors.

Upcoming AWS events
Check your calendars and sign up for these upcoming AWS events:

  • AWS Summits – Join free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Register in your nearest city: Dubai (May 21), Tel Aviv (May 28), Singapore (May 29), Stockholm (June 4), Sydney (June 4–5), Washington (June 10-11), and Madrid (June 11)
  • AWS Cloud Infrastructure Day – On May 22, discover the latest innovations in AWS Cloud infrastructure technologies at this exclusive technical event.
  • AWS re:Inforce – Mark your calendars for AWS re:Inforce (June 16–18) in Philadelphia, PA. AWS re:Inforce is a learning conference focused on AWS security solutions, cloud security, compliance, and identity.
  • AWS Partners Events – You’ll find a variety of AWS Partner events that will inspire and educate you, whether you’re just getting started on your cloud journey or you’re looking to solve new business challenges.
  • AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world: Zurich, Switzerland (May 22), Bengaluru, India (May 23), Yerevan, Armenia (May 24), Milwaukee, USA (June 5), and Nairobi, Kenya (June 14)

That’s all for this week. Check back next Monday for another Weekly Roundup!

Danilo

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SafeLine WAF: Best Security Choice for Small Businesses

As a website owner, one of my top priorities is to ensure that my website is protected from cyber threats. After trying various web application firewalls (WAFs), I recently discovered SafeLine WAF, and I’m thoroughly impressed. If you’re looking for an affordable, yet powerful WAF solution, SafeLine is the perfect choice.

What is SafeLine WAF?

SafeLine WAF is a web application firewall designed to protect websites from a variety of attacks, including SQL injections, cross-site scripting (XSS), and zero-day attacks. It acts as a shield between your website and malicious traffic, ensuring that your website remains secure while still allowing legitimate users to interact with your site.

How SafeLine Works

 

What sets SafeLine apart from other WAF solutions is its semantic analysis engine, which goes beyond traditional signature-based detection. Instead of just identifying known attack patterns, SafeLine analyzes the behavior and context of incoming traffic to detect even sophisticated, zero-day attacks. This makes it not only effective but also highly adaptable to evolving threats.

Key Features of SafeLine WAF

1.Semantic Analysis for Advanced Threat Detection

SafeLine’s semantic analysis engine sets it apart from other WAFs. Unlike traditional signature-based firewalls that can only detect known threats, SafeLine looks at the behavior and context of traffic, enabling it to detect sophisticated attacks that are not yet widely recognized. This means your website is protected from both known and unknown threats.

2.Bot Protection

SafeLine provides multi-layered defense against bot attacks like malicious crawlers through CAPTCHA verification, dynamic protection, and anti-replay protection.

3.HTTP Flood DDoS Protection

The most common way to defend against HTTP flood DDoS attacks is to limit the rate of visits from source IPs. But it’s not enough. Skilled attackers will find ways to bypass detection. Therefore, in addition to rate limiting, SafeLine also supports Waiting Room, to limit user traffic.

4.Identity and Access Management

SafeLine provides unified identity management for both on-premise and cloud applications through standard protocols.

5.Customizable Security Rules

SafeLine provides the ability to customize security rules based on your specific needs. Whether it’s blocking certain types of traffic or monitoring suspicious activity, you can fine-tune the firewall to provide the exact level of protection your website needs. 

6.User-Friendly Setup and Management

Not only is SafeLine one of the most affordable WAF solutions, but it is also incredibly easy to use. The setup process is fast and straightforward, making it perfect for those who don’t have extensive technical knowledge. 

Once installed, the intuitive dashboard (See SafeLine Demo here) makes managing and monitoring your website’s security effortless. You can easily access attack logs, view real-time alerts, and make custom adjustments without a steep learning curve.

Why SafeLine is the Best Choice for Small Businesses

When it comes to WAFs, price can often be a limiting factor, especially for small businesses or personal websites. Many high-quality WAFs can cost hundreds of dollars per month, making them inaccessible to those with limited budgets. 

However, SafeLine is a game-changer in this regard. It provides a Free edition for personal use. The Lite edition costs $10 per month. For users needing more advanced features, the Pro edition is also available at a competitive price of $100 per month, giving you full flexibility and powerful protection.

The key takeaway here is that SafeLine offers the best value for the features it provides. Whether we’re a small business, an individual site owner, or an enterprise, SafeLine is here to keep our websites safe from cyber threats. 

 

 

 

 

 

 

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Experts React: Coinbase Discloses Breach, Faces Up to $400 Million in Losses

Coinbase, one of the largest cryptocurrency exchanges, has disclosed a significant data breach that exposed sensitive customer information, including government-issued IDs. The attackers contacted Coinbase on May 11, demanding a $20 million ransom to prevent the public release of the stolen data.

The breach could result in losses of up to $400 million, depending on regulatory fines, legal actions, and customer compensation. Coinbase has launched an internal investigation and is cooperating with law enforcement. It has also notified affected customers and offered support.

The implications of the Coinbase breach are significant for crypto users and investors, spanning financial, regulatory, and trust-related concerns.

For crypto users, the risks are substantial. If government-issued IDs and personal data were stolen, users could face identity theft, phishing attacks, or SIM swapping. This could lead to unauthorized access to other financial accounts or crypto wallets. Users may lose confidence in Coinbase’s ability to protect their data, prompting them to move assets to other platforms or cold storage. Coinbase might implement stricter security protocols or temporarily limit certain services, affecting user experience. Affected users might be eligible for compensation or become part of class-action lawsuits.

For investors, the breach could lead to stock price volatility. Publicly traded companies like Coinbase (COIN) often see sharp stock price drops after breaches due to shaken investor confidence. The breach could trigger investigations by the SEC or other regulators, potentially leading to fines or new compliance requirements. Coinbase will likely need to invest heavily in cybersecurity upgrades, legal defense, and customer support. Long-term brand damage could reduce user acquisition and retention, impacting revenue growth.

David Stuart, Cybersecurity Evangelist at Sentra, commented on the breach, saying, “The Coinbase breach highlights the growing challenge of protecting sensitive customer data in highly interconnected digital ecosystems. Financial platforms, in particular, carry an outsized responsibility to safeguard personal and financial information against increasingly sophisticated threats. Full visibility into where sensitive data resides, how it moves, and who can access it is essential, especially as data spans cloud, SaaS, and third-party environments. Without continuous monitoring, access governance, and proactive risk management, even well-defended systems can become vulnerable. Organizations must prioritize a data-first security model that ensures sensitive information remains protected at every layer, beyond just perimeter defenses.”

Clyde Williamson, Senior Product Security Architect at Protegrity, added, “Coinbase says the affected customer base impacted in this attack is less than 1% of its 9.7 million customers to minimize the impact. That’s still around 1 million people whose sensitive information has been compromised, and the financial damage to Coinbase itself isn’t small. Malicious actors can do significant damage with your name and contact information; imagine what they’ll do with masked bank information and Social Security numbers. This attack was only possible because contractors and support personnel were allowed access to this information. This was an entirely avoidable situation on Coinbase’s part, and now they’re expecting the customers who trusted the organization with their highly sensitive information to perform damage control. It’s great that Coinbase was legally required to disclose this attack quickly, but those customers will be haunted by this breach. Disclosure without real action is data security’s ‘thoughts and prayers.’ Consumers deserve better than to live in constant fear of their data.”

The breach underscores the critical need for robust cybersecurity measures to protect sensitive customer information..

 

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[Webinar] From Code to Cloud to SOC: Learn a Smarter Way to Defend Modern Applications

Modern apps move fast—faster than most security teams can keep up. As businesses rush to build in the cloud, security often lags behind. Teams scan code in isolation, react late to cloud threats, and monitor SOC alerts only after damage is done.
Attackers don’t wait. They exploit vulnerabilities within hours. Yet most organizations take days to respond to critical cloud alerts. That delay isn’t

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New Amazon EC2 P6-B200 instances powered by NVIDIA Blackwell GPUs to accelerate AI innovations

Today, we’re announcing the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P6-B200 instances powered by NVIDIA B200 to address customer needs for high performance and scalability in artificial intelligence (AI), machine learning (ML), and high performance computing (HPC) applications.

Amazon EC2 P6-B200 instances accelerate a broad range of GPU-enabled workloads but are especially well-suited for large-scale distributed AI training and inferencing for foundation models (FMs) with reinforcement learning (RL) and distillation, multimodal training and inference, and HPC applications such as climate modeling, drug discovery, seismic analysis, and insurance risk modeling.

When combined with Elastic Fabric Adapter (EFAv4) networking, hyperscale clustering by EC2 UltraClusters, and advanced virtualization and security capabilities by AWS Nitro System, you can train and serve FMs with increased speed, scale, and security. These instances also deliver up to two times the performance for AI training (time to train) and inference (tokens/sec) compared to EC2 P5en instances.

You can accelerate time-to-market for training FMs and deliver faster inference throughput, which lowers inference cost and helps increase adoption of generative AI applications as well as increased processing performance for HPC applications.

EC2 P6-B200 instances specifications
New EC2 P6-B200 instances provide eight NVIDIA B200 GPUs with 1440 GB of high bandwidth GPU memory, 5th Generation Intel Xeon Scalable processors (Emerald Rapids), 2 TiB of system memory, and 30 TB of local NVMe storage.

Here are the specs for EC2 P6-B200 instances:

Instance size GPUs (NVIDIA B200) GPU
memory (GB)
vCPUs GPU Peer to peer (GB/s) Instance storage (TB) Network bandwidth (Gbps) EBS bandwidth (Gbps)
P6-b200.48xlarge 8 1440 HBM3e 192 1800 8 x 3.84 NVMe SSD 8 x 400 100

These instances feature up to 125 percent improvement in GPU TFLOPs, 27 percent increase in GPU memory size, and 60 percent increase in GPU memory bandwidth compared to P5en instances.

P6-B200 instances in action
You can use P6-B200 instances in the US West (Oregon) AWS Region through EC2 Capacity Blocks for ML. To reserve your EC2 Capacity Blocks, choose Capacity Reservations on the Amazon EC2 console.

Select Purchase Capacity Blocks for ML and then choose your total capacity and specify how long you need the EC2 Capacity Block for p6-b200.48xlarge instances. The total number of days that you can reserve EC2 Capacity Blocks is 1-14 days, 21 days, 28 days, or multiples of 7 up to 182 days. You can choose your earliest start date for up to 8 weeks in advance.

Now, your EC2 Capacity Block will be scheduled successfully. The total price of an EC2 Capacity Block is charged up front, and the price doesn’t change after purchase. The payment will be billed to your account within 12 hours after you purchase the EC2 Capacity Blocks. To learn more, visit Capacity Blocks for ML in the Amazon EC2 User Guide.

When launching P6-B200 instances, you can use AWS Deep Learning AMIs (DLAMI) to support EC2 P6-B200 instances. DLAMI provides ML practitioners and researchers with the infrastructure and tools to quickly build scalable, secure, distributed ML applications in preconfigured environments.

To run instances, you can use AWS Management Console, AWS Command Line Interface (AWS CLI) or AWS SDKs.

You can integrate EC2 P6-B200 instances seamlessly with various AWS managed services such as Amazon Elastic Kubernetes Services (Amazon EKS), Amazon Simple Storage Service (Amazon S3), and Amazon FSx for Lustre. Support for Amazon SageMaker HyperPod is also coming soon.

Now available
Amazon EC2 P6-B200 instances are available today in the US West (Oregon) Region and can be purchased as EC2 Capacity blocks for ML.

Give Amazon EC2 P6-B200 instances a try in the Amazon EC2 console. To learn more, refer to the Amazon EC2 P6 instance page and send feedback to AWS re:Post for EC2 or through your usual AWS Support contacts.

Channy


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Proofpoint to acquire Hornetsecurity for over $1 billion

Proofpoint has entered into an agreement to acquire Hornetsecurity Group, a Germany-based provider of Microsoft 365 security services, in a deal reportedly valued at more than $1 billion.

The acquisition, described as the largest in Proofpoint’s history, comes amid accelerating consolidation in the cybersecurity industry as companies seek to broaden their offerings to enterprise customers of all sizes. While Proofpoint did not disclose terms, CNBC reports the deal is “well over” $1 billion. 

Hornetsecurity, headquartered in Hannover, Germany, serves more than 12,000 managed service providers (MSPs) and 125,000 small and mid-sized businesses (SMBs) primarily across Europe. According to a press release announcing the deal, Hornetsecurity brings in $160 million in annual recurring revenue, with growth exceeding 20% year over year. 

For Proofpoint, the acquisition provides an entry point into the SMB market through Hornetsecurity’s established MSP network.

“As attackers grow more sophisticated and people remain the primary target, organizations need security that protects them wherever they work — across email, cloud applications, and every digital channel,” said Sumit Dhawan, CEO of Proofpoint. “With the addition of Hornetsecurity, we’re excited to extend our industry-leading, human-centric security platform to better serve the unique needs of MSPs and SMBs. We look forward to deepening our investment in the European markets as part of our global growth strategy.”

Both companies concentrate on offering products that work within Microsoft’s cloud platform. Hornetsecurity’s flagship product, 365 Total Protection, provides MSPs with a multi-tenant platform that includes email security, backup, security awareness training, access control, and domain fraud protection. Proofpoint, which also touts a security software suite aimed at protecting Microsoft 365 instances, also recently expanded its partnership with Microsoft.

The deal follows several major acquisitions in the cybersecurity sector. In March, Google announced plans to acquire Israeli-founded cloud security startup Wiz for $32 billion, while Palo Alto Networks revealed its intention in April to purchase AI-focused startup Protect AI.

The transaction comes as Proofpoint, which was taken private by Thoma Bravo in 2021 for $12.3 billion, is exploring an IPO, according to the CNBC report

The Hornetsecurity transaction is expected to close in the second half of 2025. 

The post Proofpoint to acquire Hornetsecurity for over $1 billion appeared first on CyberScoop.

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Accelerate CI/CD pipelines with the new AWS CodeBuild Docker Server capability

Starting today, you can use AWS CodeBuild Docker Server capability to provision a dedicated and persistent Docker server directly within your CodeBuild project. With Docker Server capability, you can accelerate your Docker image builds by centralizing image building to a remote host, which reduces wait times and increases overall efficiency.

From my benchmark, with this Docker Server capability, I reduced the total building time by 98 percent, from 24 minutes and 54 seconds to 16 seconds. Here’s a quick look at this feature from my AWS CodeBuild projects.

AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment. Building Docker images is one of the most common use cases for CodeBuild customers, and the service has progressively improved this experience over time by releasing features such as Docker layer caching and reserved capacity features to improve Docker build performance.

With the new Docker Server capability, you can reduce build time for your applications by providing a persistent Docker server with consistent caching. When enabled in a CodeBuild project, a dedicated Docker server is provisioned with persistent storage that maintains your Docker layer cache. This server can handle multiple concurrent Docker build operations, with all builds benefiting from the same centralized cache.

Using AWS CodeBuild Docker Server
Let me walk you through a demonstration that showcases the benefits with the new Docker Server capability.

For this demonstration, I’m building a complex, multi-layered Docker image based on the official AWS CodeBuild curated Docker images repository, specifically the Dockerfile for building a standard Ubuntu image. This image contains numerous dependencies and tools required for modern continuous integration and continuous delivery (CI/CD) pipelines, making it a good example of the type of large Docker builds that development teams regularly perform.


# Copyright 2020-2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Amazon Software License (the "License"). You may not use this file except in compliance with the License.
# A copy of the License is located at
#
#    http://aws.amazon.com/asl/
#
# or in the "license" file accompanying this file.
# This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, express or implied.
# See the License for the specific language governing permissions and limitations under the License.
FROM public.ecr.aws/ubuntu/ubuntu:20.04 AS core

ARG DEBIAN_FRONTEND="noninteractive"

# Install git, SSH, Git, Firefox, GeckoDriver, Chrome, ChromeDriver,  stunnel, AWS Tools, configure SSM, AWS CLI v2, env tools for runtimes: Dotnet, NodeJS, Ruby, Python, PHP, Java, Go, .NET, Powershell Core,  Docker, Composer, and other utilities
COMMAND REDACTED FOR BREVITY
# Activate runtime versions specific to image version.
RUN n $NODE_14_VERSION
RUN pyenv  global $PYTHON_39_VERSION
RUN phpenv global $PHP_80_VERSION
RUN rbenv  global $RUBY_27_VERSION
RUN goenv global  $GOLANG_15_VERSION

# Configure SSH
COPY ssh_config /root/.ssh/config
COPY runtimes.yml /codebuild/image/config/runtimes.yml
COPY dockerd-entrypoint.sh /usr/local/bin/dockerd-entrypoint.sh
COPY legal/bill_of_material.txt /usr/share/doc/bill_of_material.txt
COPY amazon-ssm-agent.json /etc/amazon/ssm/amazon-ssm-agent.json

ENTRYPOINT ["/usr/local/bin/dockerd-entrypoint.sh"]

This Dockerfile creates a comprehensive build environment with multiple programming languages, build tools, and dependencies – exactly the type of image that would benefit from persistent caching.

In the build specification (buildspec), I use the docker buildx build . command:

version: 0.2
phases:
  build:
    commands:
      - cd ubuntu/standard/5.0
      - docker buildx build -t codebuild-ubuntu:latest .

To enable the Docker Server capability, I navigate to the AWS CodeBuild console and select Create project. I can also enable this capability when editing existing CodeBuild projects.

I fill in all details and configuration. In the Environment section, I select Additional configuration.

Then, I scroll down and find Docker server configuration and select Enable docker server for this project. When I select this option, I can choose a compute type configuration for the Docker server. When I’m finished with the configurations, I create this project.

Now, let’s see the Docker Server capability in action.

The initial build takes approximately 24 minutes and 54 seconds to complete because it needs to download and compile all dependencies from scratch. This is expected for the first build of such a complex image.

For subsequent builds with no code changes, the build takes only 16 seconds and that shows 98% reduction in build time.

Looking at the logs, I can see that with Docker Server, most layers are pulled from the persistent cache:

The persistent caching provided by the Docker Server maintains all layers between builds, which is particularly valuable for large, complex Docker images with many layers. This demonstrates how Docker Server can dramatically improve throughput for teams running numerous Docker builds in their CI/CD pipelines.

Additional things to know
Here are a couple of things to note:

  • Architecture support – The feature is available for both x86 (Linux) and ARM builds.
  • Pricing – To learn more about pricing for Docker Server capability, refer to the AWS CodeBuild pricing page.
  • Availability – This feature is available in all AWS Regions where AWS CodeBuild is offered. For more information about the AWS Regions where CodeBuild is available, see the AWS Regions page.

You can learn more about the Docker Server feature in the AWS CodeBuild documentation.

Happy building! —

Donnie Prakoso


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