Independent tests show why orgs should use third-party cloud security services

Businesses don’t always get what they pay for in cybersecurity. Some of the most expensive cloud network firewall vendors are among the worst performers against exploits and evasions, according to the most comprehensive, independent testing CyberRatings.org has conducted to date.

Cisco, by far the most expensive cloud network firewall offering across the top 10 vendors on price per megabits per second, ranked seventh with an overall security effectiveness score of 53.5%, according to CyberRatings.org research released Wednesday. 

The trio of big cloud providers — Amazon Web Services, Microsoft Azure and Google Cloud Platform — fared even worse, each landing at the bottom of the pack with a 0% security effectiveness score. 

“We’ve been told to use cloud-native technologies, that they’re better suited than using bolt-ons. Well, that’s clearly not the case here,” CyberRatings.org CEO Vikram Phatak told CyberScoop.

“Any of the third-party firewalls you pick are going to be better at protecting you than what you have today with the AWS firewall, but also frankly Azure and GCP today as well,” he said.

Fortinet and Check Point earned the highest rating of 100%, followed by Versa Networks, Palo Alto Networks and Juniper Networks — each landing in the upper end of the 99th percentile, according to CyberRatings.org’s tests. Forcepoint’s security effectiveness score was 96.6%.

CyberRatings.org tested cloud network firewalls against more than 2,000 widely exploited vulnerabilities. The nonprofit, which paid for the tests and research in Q1 2025 without any vendor involvement, then applied 2,500 attacks spanning 27 evasion techniques across multiple network layers to bypass firewall defenses.

“This is what I consider to be the equivalent of an open-book test. It’s not super hard stuff,” Phatak said. 

“We want to know what a buyer, purchaser of the technology can count on in an adversarial situation where things are not always going their way,” he said. “This is not a Category 5 hurricane, and it’s also not a sunny day on the beach.”

CyberRatings.org’s tests showed wide disparities in cloud network firewalls’ ability to defend against publicly available exploits. Protecting organizations against exploits is the first line of defense, a core selling point and purpose of firewalls. 

AWS performed the worst on this front, blocking only 0.59% of exploits. The big problem for AWS is that its signature set for exploits is mismatched, Phatak said.

“If you put all your eggs in the AWS basket, you’re going to end up regretting it from a cybersecurity perspective at least,” Phatak said. 

Rounding out the bottom of the field, Microsoft Azure blocked 55.28%, Cisco blocked 90.68%, GCP blocked 96.6% and Forecepoint blocked 97.63% of exploits. Fortinet and Check Point blocked all of the exploits CyberRatings.org threw at their cloud network firewalls. Versa Networks, Juniper Networks and Palo Alto Networks each scored in the high 99th percentile on exploit prevention.

The overall results and rankings diverged further when CyberRatings.org measured cloud network firewalls’ performance against evasions.

Cisco, AWS, GCP and Microsoft Azure each failed to defend against evasion tactics between layer 3 and layer 7, network traffic originating from IP addresses and the content of application data.

Ultimately, the 0% security effectiveness score applied to AWS and GCP was due to the ease with which CyberRatings.org bypassed their firewalls with evasions. Both vendors earned a 0% score in preventing evasions.

Microsoft performed better than its cloud counterparts on evasions, scoring 78%. Yet, Microsoft’s “big issue is that if anything comes across encrypted with HTTPS, they’re blind. [It’s] the only firewall that doesn’t have HTTPS decryption built in,” Phatak said.

Microsoft’s lack of transport layer security (TLS) and secure sockets layer (SSL) support resulted in its overall 0% security effectiveness score, according to CyberRatings.org’s benchmarks. Cisco prevented 59% of CyberRatings.org’s evasion tests.

Forcepoint blocked 99% of evasions while Palo Alto Networks, Check Point, Juniper Networks and Versa Networks all blocked 100%, according to CyberRatings.org’s tests.

CyberRatings.org explained its testing framework, including why and the extent to which it deducted points from firewall vendors’ score across all categories tested. In many cases, it was the combination of exploit and evasion prevention tests, and other factors unique to specific factors that resulted in low security effectiveness scores.

In the case of AWS, its firewall didn’t block any live attacks, so CyberRatings.org couldn’t test it against evasions. With Microsoft’s firewall, CyberRatings.org evaded defenses by encrypting traffic or targeting a web server that’s encrypted.

Phatak directed his harshest criticism at AWS, which has consistently performed poorly in CyberRatings.org exploit prevention tests since 2014. “Amazon’s lack of improvement was shocking to us,” he said. “It just says that it’s not taking this seriously.”

The post Independent tests show why orgs should use third-party cloud security services appeared first on CyberScoop.

from CyberScoop https://ift.tt/v3tXHLj
via IFTTT

Dealing With Merger and Acquisition Driven Vault Sprawl: The Hidden Risks Of Multiple Secret Managers in Large Enterprises

Managing secrets, the API keys, authentication tokens, and encryption credentials that keep our applications securely running is a critical yet increasingly complex challenge in modern enterprises. Organizations use secret management tools like AWS Secrets Manager, HashiCorp Vault, and Azure Key Vault to protect sensitive access credentials. 

As businesses expand, particularly through mergers and acquisitions (M&A), they very often inherit multiple overlapping secret managers, creating hidden security and operational risks.

While redundancy might seem like a safeguard, in reality, managing secrets for mission-critical applications through multiple vaulting tools introduces security gaps, operational inefficiencies, and compliance challenges. 

A 2024 industry survey from CyberArk and GitGuardian found that the typical enterprise had at least six different secret management solutions in place. The larger the company, the more widespread and complex this problem of ‘vault sprawl’ inevitably becomes. As with any problem, the first step to addressing the issue is understanding how teams get here. 

Why Do Enterprises Use Multiple Secret Managers?

In an ideal world, every company would standardize on a single platform for secrets management. They need a way to safely store any credential, encrypted at rest, that can be programmatically called when needed throughout the software development lifecycle. These systems also offer insight into the non-human identity lifecycle, helping teams track when a secret was added and, importantly, rotated. Any good system will offer logs and make managing secrets a streamlined process. 

For small companies without many products or offerings, getting everything in one place is a realistic goal, especially if standardized on a single cloud platform, like AWS, Azure, or Google Cloud. All of these platforms offer secret management services like Azure KeyVault or AWS Secrets Manager.

As new projects are launched and companies continue to grow, they often adopt a multi-cloud strategy, introducing new secrets and management needs. In some cases, moving certain services to on-premise operations makes the most sense, meaning they end up in hybrid environments. Just the built-in tools can no longer handle secrets management, and it is at this stage of maturity that we see the adoption of enterprise secret management systems, such as HashiCorp Vault or CyberArk Conjur.

Merging Complex Organizations Amplifies Secret Management Risks

Standardizing on a single platform with any central planning is hard enough in a single organization with a shared culture and mission. What happens when a completely different organization is added to the mix and needs to be accounted for? 

This happens quite a lot.

According to research from PwC, approximately 50,000 merger and acquisition (M&A) deals were announced in 2024. 

Let’s assume that the company initiating the merger has an average of six vault solutions deployed, and the company being acquired is fairly small and only has two secret management platforms. The newly combined organization will then have eight systems to contend with overnight. That may sound manageable, but remember, secrets management is only one security consideration that this M&S activity brings. 

For very large organizations that acquire multiple companies a year, the problem of secrets to manage becomes exponential rather than linear. 

Operational Overhead And Complexity

The larger the organization, however, the more likely that multiple divisions and teams will have spun up their own instance of their secrets vaulting solution of choice. Even if the organization is standardized on a single tooling choice, the likelihood that there is one, and only one, centrally managed enterprise instance of the technology is very unlikely. With multiple secret managers in play, different teams may store and manage the same secrets separately, leading to:

  • Duplicated effort in storing, rotating, and auditing credentials
  • Confusing access control policies across departments
  • Delayed developer workflows due to integration issues

Cost is also a major concern with vault sprawl. As with any technology, the more of it you deploy, the higher your overall operational expenses are going to rise. Enterprise secrets management systems are a mission-critical infrastructure investment, costing tens or hundreds of thousands of dollars per year to license and operate. Having duplicate systems means paying that same fee through multiple contracts and, most likely, to multiple vendors. 

Risks From Secrets Redundancy

Fragmented secret management landscape is the reality of large enterprise and it increases the risk of orphaned or forgotten secrets. A 2023 study found that 90% of valid secrets detected remained active 5 days later, highlighting remediation as a challenge. 

Different secret managers enforce security policies unevenly. One tool may require monthly secret rotation, while another allows long-lived credentials indefinitely, creating compliance risks.

More systems mean more potential entry points for attackers. Each secret manager requires its own access controls, monitoring, and security patches. Security teams must learn and work with multiple platforms, increasing training costs and operational risk. Misconfigurations in just one of these tools can expose sensitive secrets.

There are also risks introduced as organizations attempt to manually solve the vault sprawl issue through the migration of secrets. When passing secrets between systems, secrets often get copied into temporary repositories or spreadsheets, increasing exposure risks. Anytime a person can read a secret in plaintext, that means there is a clear and simple attack path open to anyone who gains access to your internal environments. 

Multiple secret managers complicate audits and regulatory adherence. Regulations like GDPR and NIST standards require strict control over credentials and access logs, which become harder to enforce across disparate tools. When an auditor comes to your door, you do not want that to be the time you start trying to consolidate systems for visibility. 

Mitigating Vault Sprawl

With so many drawbacks and risks associated with vault sprawl, it is clear that security and IT leaders must work together to gain visibility into all the secrets throughout the enterprise. Addressing the existing complexity by gaining real-time visibility into the state of your secrets, how they are used, and when they need to be rotated, no matter where they are stored is the way forward. 

Secrets Discovery Is The Needed First Step

Teams should first focus on discovering secrets throughout all environments, including all secret managers, rather than trying to manage the mass migration of credentials between cloud and enterprise solutions.

Taking a visibility and discovery-focused approach will also help you find all the secrets not currently stored in vaults, helping you enforce standardization of secrets management. Without knowing about a secret, it will be impossible to ensure it is properly rotated or taken out of service when no longer needed. Long-lived “zombie credentials” are one of an attacker’s favorite paths.  

Automating Vault Consolidation

With the proper secrets detection tooling, enterprises can find redundancies as well, which can lead to lower operational costs and overhead. For example, if you find the same secret across multiple vaults, only one would be needed. Development teams lack this high-level insight. 

Doing this process manually is time and cost-prohibitive, especially when there are thousands of valid secrets in play. The larger the organization, the more automation is required. Detection solutions need to be addressable with scripting and automation tooling. If a script can open a pull request to update the code to call the correct vault, which already contains the needed secret, then the review process for merging that change should be seconds, not days of developer rework. 

Security can also help developers by investing in tools that can detect plaintext secrets before they leave the developer’s machine. Ideally any time a developer needs to invoke a new secret, their tooling should guide them down the proper path with the right documentation or even the automation to suggest the actual correct calls into the secrets management system. 

Prioritizing Secrets Management In The Enterprise At Scale

Addressing vault sprawl is not just a matter of convenience; it is a critical security and operational challenge that enterprises must proactively manage, especially as mergers and acquisitions continue to drive IT complexity. The costs are high, both from a financial perspective, as paying for redundant systems, and from an overhead perspective, requiring more time and effort from your already stretched teams to keep up with multiple platforms. 

The rapid accumulation of secret management tools across different business units creates unnecessary overhead, increases security blind spots, and elevates the risk of exposure due to inconsistent policies. While complete consolidation is often unrealistic in larger organizations, enterprises must prioritize visibility, standardization, and automation to mitigate these risks. 

By implementing robust discovery processes, enforcing uniform secret management policies, and leveraging automation to streamline migration and enforcement, organizations can ensure that secrets remain secure, auditable, and manageable at scale. As cyber threats evolve and businesses grow, security teams must take a proactive stance in managing secrets, turning what was once a hidden risk into a well-governed and resilient security practice.

__

Author BIO

Dwayne McDaniel – Senior Developer Advocate at GitGuardian

Dwayne has been working as a Developer Advocate since 2014 and has been involved in tech communities since 2005. His entire mission is to “help people figure stuff out.” He loves sharing his knowledge, and he has done so by giving talks at hundreds of events worldwide. He has been fortunate enough to speak at institutions like MIT and Stanford and internationally in Paris and Iceland. Dwayne currently lives in Chicago.

 

The post Dealing With Merger and Acquisition Driven Vault Sprawl: The Hidden Risks Of Multiple Secret Managers in Large Enterprises first appeared on Cybersecurity Insiders.

The post Dealing With Merger and Acquisition Driven Vault Sprawl: The Hidden Risks Of Multiple Secret Managers in Large Enterprises appeared first on Cybersecurity Insiders.

from Cybersecurity Insiders https://ift.tt/CFeGiHk
via IFTTT

Meet the AWS News Blog team!

Now that Jeff Barr has retired from the AWS News Blog as of December last year, the AWS News Blog team will keep sharing the most important and impactful AWS product launches the moment they become available. I want to quote Jeff’s last comment on the future of the News Blog again:

Going forward, the team will continue to grow and the goal remains the same: to provide our customers with carefully chosen, high-quality information about the latest and most meaningful AWS launches. The blog is in great hands and this team will continue to keep you informed even as the AWS pace of innovation continues to accelerate.

Since 2016, Jeff has been building the AWS News Blog as a team. Currently, we’re a group of 11 bloggers working in North America, South America, Asia, Europe, and Africa. We co-work with AWS product teams, testing new features firsthand on behalf of customers, and delivering key details in the News Blog the way Jeff has always done.

The Leadership Principles for AWS News Bloggers that Jeff shared on LinkedIn are a textbook for anyone writing for customers in tech companies. They’re the fundamentals that can help you understand and get started blogging quickly, and we’ll continue to stick to these principles with our team. This is why the AWS News Blog is different from other tech companies’ product news channels.

Voices from blog writers
You may be familiar with the names of News Blog writers, but you may not have had the chance to hear about them. Let us introduce ourselves!

Channy Yun (윤석찬)

I’m honored to continue Jeff’s legacy as a new lead blogger of the News Blog team; he is my role model. When I joined AWS in 2014, the first thing I did was to create the AWS Korea Blog and I started translating Jeff’s blog posts into the Korean language. During the journey, I learned how to write accurate, honest, and powerful guides to help customers get started with new AWS products and features.

Danilo Poccia

Since my first News Blog post in 2018, I have learned so much by being part of this team. Working with product managers and service teams is always an amazing experience. I am interested in serverless, event-driven architectures, and AI/ML. It’s incredible how technologies like generative AI are becoming part of software development implicitly (through AI-enabled development tools) and explicitly (by using models in code).

Sébastien Stormacq

I’m fortunate to have been a part of this team since 2019. When I don’t write posts, I produce episodes of the AWS Developers Podcast and le podcast AWS en français. I also work with the teams for Amazon EC2 Mac, AWS SDK for Swift, and the CodeBuild and CodeArtifact teams trying to make the AWS Cloud easier to use for Apple developers. My pet project is the Swift Runtime for AWS Lambda.

Veliswa Boya

The Amazon Leadership Principles (LPs) guide all that we do here at AWS, including the work we do as authors of the News Blog. As a developer advocate, I’ve taken the guidance of the LPs and used it to guide members of the AWS community who are looking to create technical content, especially those new in their technical content creation journey.

Donnie Prakoso

Just like brewing coffee, being a blog author has been a mix of fun, challenge, and reward. I’ve been particularly fortunate to observe how customer obsession is built into AWS teams. I’ve seen how they work backwards, transforming your feedback into services or features. I genuinely hope that you enjoy reading our articles and look forward to the next chapter of the News Blog team.

Esra Kayabali

As an author, I’m committed to delivering timely information about the latest AWS innovations and launches to our global audience of builders, developers, and technology enthusiasts. I understand the importance of providing clear, accurate, and actionable content that helps you use AWS services effectively. Happy reading everyone!

Matheus Guimaraes

My specialties are .NET development and microservices, but I’ve always been a jack-of-all-trades and writing for this blog helps me to keep my knife sharp across all corners of modern technology, while also helping others do the same. Thousands of people read the AWS News Blog and use it as a go-to source to keep up with what’s new and to help them make decisions, so I know that what we are doing is meaningful work with huge impact.

Prasad Rao

Through my blogs, I strive to highlight not just the “what” of new services, but also the “why” and “how” they can transform businesses and user experiences. As a solutions architect specializing in Microsoft Workloads on AWS, I help customers migrate and modernize their workloads and build scalable architecture on AWS. I also mentor diverse people to excel in their cloud careers.

Elizabeth Fuentes

Every time I start writing a new blog, I feel honored to be part of this team, to be able to experiment with something new before it’s released, and to be able to share my experience with the reader. This team is made up of specialists of all levels and from multiple countries and together, we are a multicultural and multi-specialty team. Thank you, reader, for being here.

Betty Zheng (郑予彬)

Joining the News Blog team has transformed how I communicate about technology. With an ever-curious mindset, I approach each new announcement aiming to make innovative services accessible and engaging. By bringing my unique and diverse perspective to technical content, I strive to help developers truly enjoy exploring our latest technologies.

Micah Walter

As a senior solutions architect, I support enterprise customers in the New York City region and beyond. I advise executives, engineers, and architects at every step along their journey to the cloud, with a deep focus on sustainability and practical design.

I also want to give credit to our behind-the-scenes editor-in-chief, Jane Watson, and program manager, Jane Scolieri, who play an essential role in helping us get product launch news to you as soon as it happens, including the 60 launches we announced in one week at re:Invent 2024!

Share your feedback
At AWS, we are customer obsessed. We’re always focused on improving and providing a better customer experience, and we need your feedback to do so. Take our survey to share insights about your experience with the AWS News Blog and suggestion for how we can serve you even better.

This survey is hosted by an external company. AWS handles your information as described in the AWS Privacy Notice. AWS will own the data gathered via this survey and will not share the information collected with survey respondents.

Channy

from AWS News Blog https://ift.tt/OnRFCgz
via IFTTT

Over 1,500 PostgreSQL Servers Compromised in Fileless Cryptocurrency Mining Campaign

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

from The Hacker News https://ift.tt/RY7wOtE
via IFTTT

The Unique Challenges of Securing Agentic AI

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.

from Cybersecurity Insiders https://ift.tt/InNV9zA
via IFTTT

Why China is considered a Big Cyber Threat to U.S. IT Infrastructure

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.

The post Why China is considered a Big Cyber Threat to U.S. IT Infrastructure first appeared on Cybersecurity Insiders.

The post Why China is considered a Big Cyber Threat to U.S. IT Infrastructure appeared first on Cybersecurity Insiders.

from Cybersecurity Insiders https://ift.tt/diNfKFH
via IFTTT

Over 1.5m personal photos from dating apps leak online

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.

The post Over 1.5m personal photos from dating apps leak online first appeared on Cybersecurity Insiders.

The post Over 1.5m personal photos from dating apps leak online appeared first on Cybersecurity Insiders.

from Cybersecurity Insiders https://ift.tt/TnGzLDf
via IFTTT

Upgrading Email Security: Why Legacy Systems Struggle with Modern Threats and How to Fix Them

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.

The post Upgrading Email Security: Why Legacy Systems Struggle with Modern Threats and How to Fix Them appeared first on Cybersecurity Insiders.

from Cybersecurity Insiders https://ift.tt/Qam05zO
via IFTTT

Accelerate operational analytics with Amazon Q Developer in Amazon OpenSearch Service

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.

— Esra


How is the News Blog doing? Take this 1 minute survey!

(This survey is hosted by an external company. AWS handles your information as described in the AWS Privacy Notice. AWS will own the data gathered via this survey and will not share the information collected with survey respondents.)

from AWS News Blog https://ift.tt/05vuw1Z
via IFTTT