Exposed PostgreSQL instances are the target of an ongoing campaign designed to gain unauthorized access and deploy cryptocurrency miners.
Cloud security firm Wiz said the activity is a variant of an intrusion set that was first flagged by Aqua Security in August 2024 that involved the use of a malware strain dubbed PG_MEM. The campaign has been attributed to a threat actor Wiz tracks as
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The cybersecurity artificial intelligence (AI) model and agent will help organizations improve threat detection and incident response.
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Introduction
The rise of Agentic AI has become one of the most talked about trends in the AI world. The move to autonomous AI Agents promises to be as big a leap forward as Generative AI was over traditional AI models. Whereas traditional AI assisted with analysis and recommendations, Agentic AI works by understanding the environment, making decisions, and taking action without human involvement. It is no surprise that Gartner lists Agentic AI as one of the top strategic trends in 2025 and anticipates it will resolve 80% of customer service issues by 2029.
But with these massive advantages come new types of risks and threats. These risks go way beyond traditional AI problems like data poisoning and model poisoning due to the autonomy that AI agents possess. As Agentic AI can make decisions and interact with other AI agents in its own unique ecosystem, we are facing security challenges that conventional security has not encountered before. In this article, we will look at a few of these challenges and how to face them.
The Problem with Autonomous Agents
As mentioned, the key feature that defines Agentic AI is autonomy, i.e., the ability to take actions without human involvement. This also creates security problems, such as rogue or compromised AI agents causing havoc in IT environments. For example, a security AI Agent could be taken over and used to lock users out of critical systems, make incorrect decisions, and weaken the security posture of an environment. This also poses the question of accountability, i.e., who is responsible for the actions that an AI agent takes? Is it the company using it, the vendor, or the team deploying it?
The Agentic AI Ecosystem
AI agents are not designed to work in isolation but operate in an ecosystem of AI Agents, which helps them execute complex workflows for increased efficiency. This opens up new attack vectors, such as the following:
1.Compromised AI Agents: Attackers may compromise AI Agents or introduce their malicious agents into this ecosystem to subtly influence their behavior and cause them to make faulty decisions.
2.Collusion Attackers: As AI Agents work together in collusion towards a common goal, they may develop malicious behavior that was never intended, either as a result of influence or due to new “emergent” behavior
3.Competitive exploitation: In some patterns, AI Agents are designed to compete against each other to achieve their goals. Attackers may influence this behavior and essentially “trick” AI agents into prioritizing false goals or fake threats to waste their time and resources.
4.Agentic AI “Worms”: As AI Agents learn by autonomously updating and sharing knowledge with other agents, attackers can exploit this ability and cause malicious behaviors to spread within an ecosystem.
The Problem of Unpredictability
We briefly touched upon emergent behavior in the previous section, and it is a key risk with agentic AI. It refers to AI agents executing unexpected actions as they learn and interact with their environment, which deviates from their original training. As attackers understand this behavior, they can use it for their malicious purposes by influencing an AI Agent to take actions that go against the interest of the company using it. This “goal misalignment” can be extremely hard to detect due to its subtle nature. For example, an attacker can trick an AI agent running in a cloud environment into thinking that security systems are causing unnecessary overhead and shut them down.
Getting ready for Agentic AI threats
Agentic AI presents challenges for monitoring, adoption, and implementation. One must grasp the possible hazards and implement a multistep security plan including the following to help to reduce them:
1.Continuous Monitoring: Agentic AI abnormalities can be monitored in real-time using AI-powered surveillance. Any deviations should be noticed and followed.
2.Secure communication and authentication: To protect agentic AI ecosystem from unauthorized manipulation, mutual authentication between agents and a trust-based ecosystem must be present to protect its integrity.
3.AI explainability: AI Agents must not be “black boxes,” and the logic behind any actions taken must be transparent and explainable. Where possible, human-in-the-loop failsafe should be present before AI agents take action on mission-critical systems.
Conclusion
Agentic AI will introduce unanticipated attack vectors and hazards for which conventional security models are inadequate. Novel cybersecurity systems have to be built for such risks, and security controls for Agentic AI have to be developed and applied. By understanding this new threat landscape, CISOs and Cybersecurity teams can implement Agentic AI to take advantage of its immense power while mitigating any potential risks it may introduce.
The post The Unique Challenges of Securing Agentic AI first appeared on Cybersecurity Insiders.
The post The Unique Challenges of Securing Agentic AI appeared first on Cybersecurity Insiders.
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In recent years, cyber threats have become one of the most significant security concerns for nations around the world. Among the most notable players in this growing arena is China, whose cyber capabilities have made it a major threat to the United States’ information technology (IT) infrastructure. With advancements in technology, increasing political tensions, and a history of cyber operations, China’s influence in the cyber domain has raised alarms for U.S. security officials. But what makes China such a significant threat to U.S. IT infrastructure? Let’s break down the reasons behind this escalating concern.
1. Advanced Cyber Capabilities and State-Sponsored Hacking
China is widely recognized as having some of the most sophisticated and well-funded cyber capabilities in the world. The Chinese government has invested heavily in cyber warfare, creating a powerful network of hackers and cyber specialists who are capable of executing advanced persistent threats (APTs). These attacks are often prolonged and stealthy, designed to infiltrate systems without detection and maintain access over time.
The Chinese government is also believed to sponsor or tolerate cyber operations conducted by state-backed groups like APT1, APT10, and APT41. These groups are responsible for carrying out espionage, intellectual property theft, and disrupting critical infrastructure. With the backing of the state, these groups can conduct operations with fewer limitations and greater resources, making them far more effective than independent hackers or even private cybercriminal organizations.
2. Intellectual Property Theft
One of China’s most notorious tactics in the cyber domain is the theft of intellectual property (IP). For years, Chinese hackers have targeted U.S. companies, universities, and government agencies to steal sensitive research, trade secrets, and patents. The theft of intellectual property can be incredibly damaging to U.S. businesses, as it undermines their competitive advantage and erodes their market share.
The stolen IP often benefits Chinese state-owned enterprises, allowing them to produce goods more cheaply, improve their technological capabilities, and gain a competitive edge in industries like telecommunications, defense, and technology. This theft not only harms U.S. economic interests but also threatens national security by potentially arming China with sensitive defense and technological advancements.
3. Targeting Critical Infrastructure
China’s cyber threat to U.S. IT infrastructure goes beyond stealing information—it also involves efforts to compromise the very systems that support national security and public services. China has been linked to several attempts to infiltrate and potentially disrupt critical U.S. infrastructure, including energy grids, water systems, and transportation networks. A successful attack on these systems could lead to wide-scale disruption and even loss of life.
China’s interest in critical infrastructure is twofold. First, by infiltrating such systems, China can monitor and potentially disrupt U.S. operations in times of conflict or national emergency. Second, weakening or damaging infrastructure could be used as a strategic advantage during a military confrontation, making it harder for the U.S. to mobilize resources or respond effectively.
In 2020, reports surfaced that Chinese hackers had gained access to vulnerabilities in U.S. energy infrastructure through cyberattacks. Though the intent was likely espionage and intelligence gathering, these kinds of breaches highlight the risks of Chinese infiltration into systems critical to U.S. defense and economy.
4. Cyber Espionage and Surveillance
Cyber espionage is one of China’s most persistent strategies in its cyber threat operations. By infiltrating government and corporate networks, China seeks to gather intelligence on U.S. policies, military capabilities, and economic strategies. The Chinese government is believed to engage in surveillance operations not only against the U.S. government but also against private companies, including tech giants like Google, Microsoft, and Apple, in a bid to gather secrets related to emerging technologies and global trade.
These espionage efforts aim to give China a strategic advantage in diplomatic negotiations, military strategies, and technology development. The information stolen from such operations can also be used to anticipate U.S. actions or counter its moves on the global stage.
5. Increasingly Aggressive Cyber Operations
China’s cyber operations have become increasingly aggressive over the years. Not only are they highly organized, but they also involve a wide range of tactics, from spear-phishing and social engineering to exploiting vulnerabilities in widely used software and hardware. These techniques are used to infect systems with malware, gain unauthorized access to databases, and plant malicious code to maintain long-term surveillance and control.
In addition to direct attacks on government agencies, China has expanded its cyber activities to include attacks on private sector companies, particularly those in critical industries like healthcare, energy, and defense. This broad range of targets makes it harder for the U.S. to effectively defend against China’s cyber operations.
China’s interest in expanding its cyber capabilities is evident in its “cyber sovereignty” policies, which aim to control internet traffic within its borders while conducting surveillance and cyberattacks globally. This approach has put pressure on international norms surrounding cybersecurity and left the U.S. vulnerable to an ever-evolving set of threats.
6. Influence Through Cyber Diplomacy and Supply Chain Vulnerabilities
China has leveraged its influence in the global technology supply chain, creating vulnerabilities for the U.S. and its allies. Chinese companies, particularly in telecommunications and hardware manufacturing, play a central role in supplying critical infrastructure components, such as networking equipment, semiconductors, and cloud services. The most well-known example is the Chinese company Huawei, which has been accused of embedding backdoors into its products to facilitate espionage for the Chinese government.
By controlling access to the global tech supply chain, China can potentially compromise U.S. systems on a massive scale. The potential for espionage through these supply chain vulnerabilities extends to areas beyond just consumer devices, including military-grade technologies and infrastructure systems.
7. Economic and Political Motivations
China’s cyber activities are also driven by broader economic and political objectives. By engaging in cyber operations against the U.S., China seeks to challenge U.S. global dominance, particularly in the tech and defense sectors. Cyberattacks can disrupt the U.S. economy, undermine confidence in digital systems, and weaken the nation’s geopolitical standing.
Furthermore, China’s increasing cyber capabilities are seen as a tool to protect its growing global influence, particularly in Africa, the Middle East, and Latin America, where China is investing heavily in infrastructure projects. These cyber capabilities allow China to monitor and safeguard its interests in these regions while putting pressure on U.S. allies.
Conclusion: A Growing Cyber Threat
China’s increasing cyber threat to U.S. IT infrastructure is one of the most complex and dangerous challenges in the modern cybersecurity landscape. From intellectual property theft to espionage and attacks on critical infrastructure, China’s state-sponsored cyber operations are designed to undermine U.S. national security, economic stability, and technological supremacy. As China continues to invest in and refine its cyber capabilities, the U.S. must remain vigilant, investing in defense measures, strengthening international cooperation, and enhancing cybersecurity protocols to counter these evolving threats. The stakes are high, and addressing this growing cyber challenge is paramount for the future of U.S. security.
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In what can be described as a significant security breach, over 1.5 million personal photographs have been exposed and are now accessible online, all due to a human error that led to the leak of sensitive information. This incident has raised serious concerns, especially considering the nature of the data that was compromised.
Among the leaked images, many are linked to individuals from niche and marginalized communities, including those involved in BDSM and the LGBT community. This exacerbates the situation, as the nature of the leaked photos includes intimate verification images, photos that had been previously rejected by site moderators, as well as private pictures that were shared and circulated among users. The compromised nature of this data makes the breach particularly worrying, as the affected individuals might face severe personal and social consequences.
The breach was traced back to a cloud platform operated by MAD Mobile, a technology service provider for several niche websites, including Translove, Chica, Brish, and Pink. The cause of the leak remains unclear: it is still uncertain whether cybercriminals managed to infiltrate the cloud database directly, or if the security measures implemented by MAD Mobile were insufficient, allowing the breach to occur in the first place.
A detailed investigation into the breach revealed that the hack was primarily enabled by a human mistake—specifically, a failure to patch a known vulnerability within the system. This oversight gave hackers a window of opportunity to exploit the flaw, ultimately leading to the unauthorized access and theft of sensitive data.
However, a spokesperson from MAD Mobile, based in Florida, responded to the incident by confirming that the vulnerability has now been addressed and that the cause was indeed human error. The representative also stressed that, to their knowledge, the exposed information had not been fraudulently accessed or misused online. While this may provide some relief, it does little to erase the damage caused by the breach, especially for the individuals whose private information was exposed.
This incident highlights the ongoing importance of cybersecurity and the need for stringent protocols to protect personal data. It also emphasizes the potentially harmful impact on vulnerable communities when their private lives are compromised in such a manner. The event has left many questioning the adequacy of the security measures in place at MAD Mobile and other similar service providers, as well as the broader responsibility of tech companies to safeguard user privacy.
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For years, businesses have relied on email as their primary communication tool, trusting legacy security systems to keep sensitive information safe. But cyber threats have changed. The simple spam filters and antivirus tools that once seemed sufficient now fail against modern phishing schemes, ransomware, and AI-driven fraud. Sticking to outdated security measures isn’t just risky—it’s an open invitation for attackers.
Yet, many companies hesitate to upgrade their email security. Concerns about cost, disruption, and complexity hold them back. But waiting for a breach to happen isn’t a strategy—it’s a liability. As Trinetix points out, modernization isn’t just about replacing old software; it’s about ensuring systems are adaptive, resilient, and built for the future. Organizations that fail to update their email security risk losing more than just data—they risk customer trust, financial stability, and compliance with evolving regulations.
Understanding the Modern Threat Landscape
Email-based attacks have evolved far beyond generic phishing attempts. Cybercriminals now deploy AI-driven scams, deepfake-powered impersonations, and sophisticated ransomware campaigns that exploit outdated security models. These threats are dynamic, constantly adapting to bypass traditional security measures.
Advanced Phishing Attacks and Social Engineering
Phishing has become hyper-personalized. Attackers scrape social media, breach databases, and use AI-generated text to craft emails that mimic real employees. Business Email Compromise (BEC) scams have led to billion-dollar losses by fooling finance teams into wiring money to fraudulent accounts. Legacy security filters, trained on outdated threat signatures, often fail to detect these highly customized attacks.
The Rise of Ransomware via Email
Ransomware attacks are no longer just random. Attackers use tailored email lures, hiding malware in documents that seem harmless. Some advanced ransomware strains even remain dormant for weeks, silently exfiltrating data before locking systems down. Without real-time behavioral analysis, legacy email security tools can’t detect these slow, stealthy attacks.
AI-Powered Threats and Deepfake Scams
Attackers aren’t just using AI for automation—they’re using it to manipulate reality. Deepfake voice and video scams allow cybercriminals to impersonate executives, instructing employees to transfer funds or share confidential information. These scams bypass traditional email security measures because they exploit human psychology rather than technical vulnerabilities.
The Key Weaknesses of Legacy Email Security Systems
Many organizations assume their existing security measures are “good enough.” But email security solutions built a decade ago simply aren’t equipped to handle today’s threat landscape. The limitations of these outdated systems create significant gaps that cybercriminals easily exploit.
Businesses relying on these outdated methods are playing defense with a rulebook that’s no longer relevant.
How to Upgrade Email Security for the Modern Threat Landscape
A modern email security strategy isn’t about adding another filter—it’s about creating a proactive, adaptive system that keeps up with evolving threats.
Implementing AI-Driven Threat Detection
Instead of relying on predefined rules, AI-driven solutions continuously learn from real-time email activity, spotting anomalies that indicate phishing, malware, or account compromise. This allows businesses to stop attacks before they reach employees.
Strengthening Email Authentication with DMARC, SPF, and DKIM
Email authentication protocols ensure that emails actually come from who they claim to be. By enforcing DMARC, SPF, and DKIM policies, organizations can prevent domain spoofing—one of the most common tactics in phishing attacks.
Adopting Zero Trust Security for Email Access
Zero Trust principles eliminate the assumption that any device or user is inherently safe. By requiring continuous verification and applying least-privilege access, companies can prevent attackers from gaining access—even if they steal login credentials.
Utilizing End-to-End Encryption and Secure Email Gateways
Encrypting emails ensures that even if intercepted, they remain unreadable to unauthorized parties. Secure Email Gateways (SEGs) add another layer of defense, scanning email traffic for malicious attachments, links, and behavioral anomalies.
Enhancing Incident Response and Security Awareness Training
Technology alone won’t solve email security problems. Employees remain the weakest link if they aren’t trained to recognize suspicious emails. Regular phishing simulations and clear reporting protocols help build a more security-aware workforce.
The Role of Software Development in Modern Email Security
While businesses often rely on third-party security tools, custom software development can create security solutions that align with unique operational needs.
Developing Custom Security Solutions for Enterprises
Pre-built email security solutions often struggle to integrate seamlessly with an organization’s existing infrastructure. Custom-built security tools can address specific vulnerabilities while ensuring compliance with industry regulations.
Leveraging Cloud-Native Email Security Solutions
Legacy on-premise security solutions lack the agility needed to respond to modern threats. Cloud-native security platforms offer real-time threat intelligence, automated security updates, and scalable protection across multiple devices and locations.
Future Trends: AI-Driven Security Automation and Blockchain for Email Integrity
AI-powered security automation allows businesses to detect and neutralize threats in real time—without human intervention. Meanwhile, blockchain technology could revolutionize email security by enabling verifiable sender identities and tamper-proof email records.
What Happens Next?
Outdated email security isn’t just a technical challenge—it’s a business risk. As attacks grow more sophisticated, companies that fail to modernize will find themselves playing catch-up in a game where losing means data breaches, financial losses, and reputational damage.
Upgrading email security isn’t about staying ahead of threats—it’s about ensuring they never reach you in the first place. Organizations that integrate AI-driven security, enforce strict authentication, and adopt Zero Trust principles will be the ones that stay secure in an increasingly hostile digital environment.
The post Upgrading Email Security: Why Legacy Systems Struggle with Modern Threats and How to Fix Them first appeared on Cybersecurity Insiders.
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Today, I’m happy to announce Amazon Q Developer support for Amazon OpenSearch Service, providing AI-assisted capabilities to help you investigate and visualize operational data. Amazon Q Developer enhances the OpenSearch Service experience by reducing the learning curve for query languages, visualization tools, and alerting features. The new capabilities complement existing dashboards and visualizations by enabling natural language exploration and pattern detection. After incidents, you can rapidly create additional visualizations to strengthen your monitoring infrastructure. This enhanced workflow accelerates incident resolution and optimizes engineering resource usage, helping you focus more time on innovation rather than troubleshooting.
Amazon Q Developer in Amazon OpenSearch Service improves operational analytics by integrating natural language exploration and generative AI capabilities directly into OpenSearch workflows. During incident response, you can now quickly gain context on alerts and log data, leading to faster analysis and resolution times. When alert monitors trigger, Amazon Q Developer provides summaries and insights directly in the alerts interface, helping you understand the situation quickly without waiting for specialists or consulting documentation. From there, you can use Amazon Q Developer to explore the underlying data, build visualizations using natural language, and identify patterns to determine root causes. For example, you can create visualizations that break down errors by dimensions such as Region, data center, or endpoint. Additionally, Amazon Q Developer assists with dashboard configuration and recommends anomaly detectors for proactive alerting, improving both initial monitoring setup and troubleshooting efficiency.
Get started with Amazon Q Developer in OpenSearch Service
To get started, I go to my OpenSearch user interface and sign in. From the home page, I choose a workspace to test Amazon Q Developer in OpenSearch Service. For this demonstration, I use a preconfigured environment with the sample logs dataset available on the user interface.
This feature is on by default through the Amazon Q Developer Free tier, which is also on by default. You can disable the feature by unselecting the Enable natural language query generation checkbox under the Artificial Intelligence (AI) and Machine Learning (ML) section during domain creation or by editing the cluster configuration in console.
In OpenSearch Dashboards, I navigate to Discover from the left navigation pane. To use natural language to explore the data, I switch to PPL language in order to show the prompt box.
I choose the Amazon Q icon in the main navigation bar to open the Amazon Q panel. You can use this panel to create recommended anomaly detectors to drive alerting and use natural language to generate visualization.
I enter the following prompt in the Ask a natural language question text box:
Show me a breakdown of HTTP response codes for the last 24 hours
When results appear, Amazon Q automatically generates a summary of these results. You can control the summary display using the Show result summarization option under the Amazon Q panel to hide or show the summary. You can use the thumbs up or thumbs down buttons to provide feedback, and you can copy the summary to your clipboard using the copy button.
Other capabilities of Amazon Q Developer in OpenSearch Service are generating visualizations directly from natural language descriptions, providing conversational assistance for OpenSearch related queries, providing AI-generated summaries and insights for your OpenSearch alerts, and analyzing your data, and suggesting appropriate anomaly detectors.
Let’s look into how to generate visualizations directly from natural language descriptions. I choose Generate visualization from Amazon Q panel. I enter Create a bar chart showing the number of requests by HTTP status code in the input field and choose generate.
To refine the visualization, you can choose Edit visual and add style instructions such as Show me a pie chart or Use a light gray background with a white grid.
Now available
You can now use Amazon Q Developer in OpenSearch Service to reduce mean time to resolution, enable more self-service troubleshooting, and help teams extract greater value from your observability data.
The service is available today in US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (London), Europe (Paris), and South America (São Paulo) AWS Regions.
To learn more, visit the Amazon Q Developer documentation and start using Amazon Q Developer in your OpenSearch Service domain today.
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Today, we are launching IPv6 support for Amazon API Gateway across all endpoint types, custom domains, and management APIs, in all commercial and AWS GovCloud (US) Regions. You can now configure REST, HTTP, and WebSocket APIs, and custom domains, to accept calls from IPv6 clients alongside the existing IPv4 support. You can also call API Gateway management APIs from dual-stack (IPv6 and IPv4) clients. As organizations globally confront growing IPv4 address scarcity and increasing costs, implementing IPv6 becomes critical for future-proofing network infrastructure. This dual-stack approach helps organizations maintain future network compatibility and expand global reach. To learn more about dualstack in the Amazon Web Services (AWS) environment, see the IPv6 on AWS documentation.
Creating new dual-stack resources
This post focuses on two ways to create an API or a domain name with a dualstack IP address type: AWS Management Console and AWS Cloud Development Kit (CDK).
AWS Console
When creating a new API or domain name in the console, select IPv4 only or dualstack (IPv4 and IPv6) for the IP address type.
As shown in the following image, you can select the dualstack option when creating a new REST API.
For custom domain names, you can similarly configure dualstack as shown in the next image.
If you need to revert to IPv4-only for any reason, you can modify the IP address type setting, with no need to redeploy your API for the update to take effect.
REST APIs of all endpoint types (EDGE, REGIONAL and PRIVATE) support dualstack. Private REST APIs only support dualstack configuration.
AWS CDK
With AWS CDK, start by configuring a dual-stack REST API and domain name.
IPv6 Source IP and authorization
When your API begins receiving IPv6 traffic, client source IPs will be in IPv6 format. If you use resource policies, Lambda authorizers, or AWS Identity and Access Management (IAM) policies that reference source IP addresses, make sure they’re updated to accommodate IPv6 address formats.
For example, to permit traffic from a specific IPv6 range in a resource policy.
Summary
API Gateway dual-stack support helps manage IPv4 address scarcity and costs, comply with government and industry mandates, and prepare for the future of networking. The dualstack implementation provides a smooth transition path by supporting both IPv4 and IPv6 clients simultaneously.
To get started with API Gateway dual-stack support, visit the Amazon API Gateway documentation. You can configure dualstack for new APIs or update existing APIs with minimal configuration changes.
Special thanks to Ellie Frank (elliesf), Anjali Gola (anjaligl), and Pranika Kakkar (pranika) for providing resources, answering questions, and offering valuable feedback during the writing process. This blog post was made possible through the collaborative support of the service and product management teams.
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It’s AWS Summit season! Free events are now rolling out worldwide, bringing our cloud computing community together to connect, collaborate, and learn. Whether you prefer joining us online or in-person, these gatherings offer valuable opportunities to expand your AWS knowledge. I’ll be attending the AWS Amsterdam Summit and would love to meet you—if you’re planning to be there, please stop by to say hello! Visit the AWS Summit website today to find events in your area, sign up for registration alerts, and reserve your spot at an AWS Summit near you.
Speaking of AWS news, let’s look at last week’s new announcements.
Last week’s launches
Here are the launches that got my attention.
AWS WAF integration with AWS Amplify Hosting now generally available – You can now directly attach AWS WAF to your AWS Amplify applications through a one-click integration in the Amplify console or using infrastructure as code (IaC). This integration provides access to the full range of AWS WAF capabilities, including managed rules that protect against common web exploits like SQL injection and cross-site scripting (XSS). You can also create custom rules based on your application needs, implement rate-based rules to protect against distributed denial of service (DDoS) attacks by limiting request rates from IP addresses, and configure geo-blocking to restrict access from specific countries. Firewall support is available in all AWS Regions in which Amplify Hosting operates.
Amazon Bedrock Custom Model Import introduces real-time cost transparency – If you’re using Amazon Bedrock Custom Model Import to run your customized foundation models (FMs), you can now access full transparency into compute resources and calculate inference costs in real time. Before model invocation, you can view the minimum compute resources (custom model units or CMUs) required through both the Amazon Bedrock console and Amazon Bedrock APIs. As models scale to handle increased traffic, Amazon CloudWatch metrics provide real-time visibility into total CMUs used, enabling better cost control through near-instant visibility. This helps you make on-the-fly model configuration changes to optimize costs. The feature is available in all Regions where Amazon Bedrock Custom Model Import is supported, with additional details available in Calculate the cost of running a custom model in the Amazon Bedrock User Guide.
Amazon Bedrock Knowledge Bases now supports Amazon OpenSearch Managed Cluster for vector storage – Amazon Bedrock Knowledge Bases securely connects FMs to company data sources for Retrieval Augmented Generation (RAG), delivering more relevant and accurate responses. With this launch, you can use Amazon OpenSearch Managed Cluster as a vector database while using the full suite of Amazon Bedrock Knowledge Bases features. This integration expands the list of supported vector databases, which already includes Amazon OpenSearch Serverless, Amazon Aurora, Amazon Neptune Analytics, Pinecone, MongoDB Atlas, and Redis. The native integration with vector databases helps mitigate the need to build custom data source integrations. This feature is now generally available in all existing Amazon Bedrock Knowledge Bases and OpenSearch Service Regions.
Amazon Bedrock Guardrails announces the general availability of industry-leading image content filters – This new capability offers industry-leading text and image content safeguards that help you block up to 88% of harmful multimodal content without building custom safeguards or relying on error-prone manual content moderation. Image content filters can be applied across all categories within the content filter policy including hate, insults, sexual, violence, misconduct, and prompt attacks. Amazon Bedrock Guardrails provides configurable safeguards to detect and block harmful content and prompt attacks, define topics to deny and disallow specific topics, redact personally identifiable information (PII) such as personal data, and block specific words. It also provides contextual grounding checks to detect and block model hallucinations and to identify the relevance of model responses and claims, and to identify, correct, and explain factual claims in model responses using Automated Reasoning checks. This capability is generally available in the US East (N. Virginia), US West (Oregon), Europe (Frankfurt), and Asia Pacific (Tokyo) Regions. To learn more, visit Amazon Bedrock Guardrails image content filters provide industry-leading safeguards in the AWS Machine Learning Blog and Stop harmful content in models using Amazon Bedrock Guardrails in the Amazon Bedrock User Guide.
Scenarios capability now generally available for Amazon Q in QuickSight – This capability guides you through data analysis by uncovering hidden trends, making recommendations for your business, and intelligently suggesting next steps for deeper exploration using natural language interactions. Now you can explore past trends, forecast future scenarios, and model solutions without needing specialized skill, analyst support, or manual manipulation of data in spreadsheets. With its intuitive interface and step-by-step guidance, the scenarios capability of Amazon Q in QuickSight helps you perform complex data analysis up to 10x faster than spreadsheets. Whether you’re optimizing marketing budgets, streamlining supply chains, or analyzing investments, Amazon Q makes advanced data analysis accessible so you can make data-driven decisions across your organization. This capability is accessible from any Amazon QuickSight dashboard, so you can move seamlessly from visualizing data to asking what-if questions and comparing alternatives. Previous analyses can be easily modified, extended, and reused, helping you quickly adapt to changing business needs.
For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.
We launched existing services and instance types in additional Regions:
Other AWS events
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That’s all for this week. Check back next Monday for another Weekly Roundup!
This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!
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Every week, someone somewhere slips up—and threat actors slip in. A misconfigured setting, an overlooked vulnerability, or a too-convenient cloud tool becomes the perfect entry point. But what happens when the hunters become the hunted? Or when old malware resurfaces with new tricks?
Step behind the curtain with us this week as we explore breaches born from routine oversights—and the unexpected
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