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By David Bunting
When it comes to managing AWS cloud security, a growing concern for security operations (SecOps teams) is the increasing sophistication of digital threats. While conventional cyber threats deploy widely known tools and techniques in crude, all-or-nothing attempts to breach enterprise security controls, sophisticated attacks known as Advanced Persistent Threats (APTs) employ more advanced technologies and methods to gain and maintain access to secure systems for long periods of time.
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By David Bunting
Cyberattacks are becoming more advanced, and groups like Scattered Spider are leading the way with their sophisticated techniques. This group is notorious for using social engineering methods like SIM swapping, voice phishing, and SMS phishing to trick employees into giving them access to sensitive systems. By pretending to be IT administrators, they bypass traditional security defenses, moving through networks unnoticed and stealing valuable data.
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By David Bunting
Security Operations Centers (SOCs) are critical to protecting organizations against cyber threats. Tasked with monitoring networks, analyzing data, and responding to incidents, these teams rely heavily on threat intelligence to detect and mitigate risks. However, one of the most significant challenges they face is the issue of false positives — when benign activities are flagged as potential threats.
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By David Bunting
Cyber threats against AI systems are on the rise, and today’s AI developers need a robust approach to securing AI applications that address the unique vulnerabilities and attack patterns associated with AI systems and ML models deployed in production environments. In this blog, we’re taking a closer look at two specific tools that AI developers can use to help detect cyber threats against AI systems.
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By David Bunting
In the world of enterprise security, most teams are laser-focused on defending organizational IT assets from external actors: cybercriminals, digital fraudsters, state-backed hackers, and other external adversaries. But data on the frequency and cost of insider attacks suggests that security teams should shift their focus toward threats that originate from inside their organizations.
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By David Bunting
Modern SecOps teams use Security Information and Event Management (SIEM) software to aggregate security logs, detect anomalies, hunt for threats, and enable rapid incident response. While SIEMs enable accurate, near real-time detection of threats, today's SIEM solutions were never designed to handle the volume of security data organizations generate daily. As daily log ingestion grows, so do the costs of data management.
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By David Bunting
Managed Detection and Response (MDR) is a cybersecurity service offered by a Managed Security Services Provider (MSSP) that combines human security expertise with modern security tools to deliver managed threat detection, security monitoring, and incident response capabilities for both SMBs and enterprise clients.
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By David Bunting
Managed Detection and Response (MDR) services play a critical role in cybersecurity. These technologies remotely monitor, detect, and respond to threats, blending threat intelligence with human expertise to hunt down and neutralize potential risks. However, one of the biggest challenges MDRs face is managing the sheer volume and variety of threat intelligence data they receive.
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By David Bunting
The 2024 Global Digital Trust Insights survey from PwC reports that 36% of businesses have experienced a data breach that cost more than $1 million to remediate. Cyber threats are clearly on the rise and in today’s volatile threat environment, it is a matter of when - not if - a cybersecurity incident will occur. Digital adversaries are becoming more sophisticated and relying on weak links to exploit company applications and infrastructure.
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By Dave Armlin
SecOps teams at midsize companies face a unique set of challenges when it comes to managing organizational cybersecurity. Midsize companies (those with 100-999 employees and $50 million-$1 billion in annual revenue, according to Gartner) possess significant financial resources and valuable data that may be targeted by digital adversaries.
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By ChaosSearch
ChaosSearch + Databricks Deliver on the best of Databricks (open Spark-based data lakehouse) and ELK (efficient search, flexible live ingestion, API/UI) via ChaosSearch on Databricks. Log analytics for observability / security with unlimited retention at a fraction of the cost now with Databricks’ AI/ML. Watch as ChaosSearch CEO, Ed Walsh, shares the power of ChaosSearch in your Databricks environment.
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By ChaosSearch
The leader in cybersecurity, Blackpoint Cyber, has teamed up with ChaosSearch, to create a next-generation data platform for log analytics for observability & security. We look forward to working with the Blackpoint team on tackling the rising costs & pain of ELK, while significantly increasing data retention, building a future-proof data platform for the increasingly challenging cybersecurity environment & AI-driven world.
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By ChaosSearch
Now you can actually have a conversation with your data! The Chaos AI Assistant is a breakthrough feature that elevates log and event data analytics. Seamlessly integrating with the ChaosSearch Platform, it utilizes AI and Large Language Models (LLMs), enabling you to talk to your data to unveil actionable insights.
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By ChaosSearch
Now you can actually have a conversation with your data! The Chaos AI Assistant is a breakthrough feature that elevates log and event data analytics. Seamlessly integrating with the ChaosSearch Platform, it utilizes AI and Large Language Models (LLMs), enabling you to talk to your data to unveil actionable insights.
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By ChaosSearch
Now you can actually have a conversation with your data! The Chaos AI Assistant is a breakthrough feature that elevates log and event data analytics. Seamlessly integrating with the ChaosSearch Platform, it utilizes AI and Large Language Models (LLMs), enabling you to talk to your data to unveil actionable insights.
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By ChaosSearch
Now you can actually have a conversation with your data! The Chaos AI Assistant is a breakthrough feature that elevates log and event data analytics. Seamlessly integrating with the ChaosSearch Platform, it utilizes AI and Large Language Models (LLMs), enabling you to talk to your data to unveil actionable insights.
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By ChaosSearch
CHAOSSEARCH is a fully managed Log Analysis SaaS solution built on our innovative architecture and revolutionary, patent-pending index technology. Our solution delivers log analysis at cloud-scale and eliminates data movement - the first SaaS solution to provide infinite data storage by accessing your data in your Amazon S3.
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ChaosSearch makes it simple for organizations to run cloud-scale log analytics in their own Amazon S3 cloud storage. It uniquely transforms your cheap, secure, and durable cloud object storage into a distributed analytic data lake where scale is infinite, cost is disruptive, and access is universal.
Traditional log analytics weren’t designed for today’s tsunamis of log data. They require brute force (adding more and more compute) to search and analyze huge stores of logs. This means businesses must continually choose between spending more money or reducing data retention.
ChaosSearch’s SaaS data platform was built for a data-entrenched world. It’s based on the company’s patent-pending index technology and architecture that remove the limits, cost, and complexity inherent in conventional solutions.
- Performance at Scale: Easily scales to petabytes and beyond so you can analyze what you need, whenever you need.
- Fully Managed Service: There’s no software or hardware for you to deploy, configure or maintain.
- All on Your Amazon S3: ChaosSearch stores and analyzes data directly in your own Amazon S3 cloud object storage. It does not hold or store any data.
- Disruptive Pricing: Costs up to 80% less than other solutions, thanks to Chaos Index’s unique properties that eliminate the need to manually shard data and enable unparalleled compression ratios.