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As technology advances and attackers develop ever-more sophisticated tactics, CISOs and security teams face a constant battle of trying to stay ahead of the curve. This year, several key themes are expected to dominate the cybersecurity landscape, shaping the priorities of CISOs and their teams.
As cyber threats grow more sophisticated, organizations are starting to turn to artificial intelligence (AI) to reinforce their security operations. But how widespread is the adoption of AI, and how effectively is it being leveraged?
As organizations grapple with the limitations of legacy security controls in the face of increasingly sophisticated cyber threats, integrating AI-driven threat detection and response capabilities presents a compelling opportunity to bolster their defenses.
The emergence of AI-generated attacks represents a paradigm shift in the cyber threat landscape, posing unprecedented challenges to traditional security solutions. Legacy solutions struggle to contend with intelligent attack automation techniques employed by threat actors, and the overwhelming flood of new malware samples and indicators makes it harder to defend against these attacks.
The history of cybersecurity is a tale of constant evolution, marked by the rise and fall of various defense mechanisms in the face of ever-changing threats. Security tools such as antivirus software and firewalls have long been the stalwarts of cyber defense, forming the bedrock of protection for organizations worldwide. While effective in their time, …
AI-driven threat detection and response solutions can significantly enhance the defense against ransomware attacks. These solutions provide advanced capabilities for detecting, analyzing, and responding to ransomware attacks.
Real-time threat detection is crucial for organizations to effectively maintain their security posture and gain enhanced visibility to defend against ever-evolving cyber threats. However, many organizations face challenges implementing and maintaining effective threat detection capabilities. Legacy rules-based solutions and signature-based threat detection are no longer sufficient to protect against malicious activity. And doing it alone can be costly.
In this buyers guide you’ll learn about the many approaches to AI Threat detection and Response, what to look for, benefits, drawbacks, and everything you need to know when choosing an AI platform for your security operations center.
he new State of Cloud Security Report from MixMode summarizes input from 588 security professionals and reveals significant gaps in organizations’ abilities to secure cloud platforms and workloads. Despite multi-cloud adoption reaching mainstream levels, critical capabilities for cloud security, such as real-time threat detection and response, comprehensive visibility, workload protection, and data security, still need to be improved.
Let’s take a closer look at the false narrative being propagated in the cybersecurity market and explore some more appropriate alternatives. An example of a legacy cyber tool vendor “feature” being touted as an ideal solution to the problem of automatic remediation is reliant on a standard (though rarely used for reasons we will explore in this article) function known as TCP Reset.
Mature cyber security teams understand a harsh reality often ignored by legacy cyber tools vendors: correlation must not be confused with causation.
Cybersecurity tool vendors understand that historically, the determining factors for a successful Security Operations Center (SOC) have been dependent entirely on 2 operational factors rather than the underlying technology.
Geoffrey Coulehan, Head of Sales for MixMode, pens our latest whitepaper on the misleading “one-click remediation” claims that many cybersecurity tool vendors are using in the marketplace.
Many vendor claims are unclear as to what they’re promising in this space, but they are quite insistent that without Zero Trust network architectures, organizations are at great risk for data breaches and other network sabotage.
How sure are you that log files represent the best source of information to base your entire Cybersecurity program upon? Log data is the cornerstone of every traditional cybersecurity platform including SIEM (Security Information and Event Management), UEBA (User and Entity Behavior Analytics), and xDR (Detection and Response).
As SIEM evolved, vendors began bolting on NDR (network detection and response) and NTA (network traffic analysis) to their base SIEM offerings. The hope (and promise) was that these tools would add the real-time security solution that was lacking with SIEM technology.
espite the availability of new technology, companies still have to depend on extracted, aggregated, and normalized historical data to operate. The inherent architecture of legacy solutions diverts focus away from fundamental business problems companies need to address.
A jumble of ineffective, incomplete, extremely expensive platforms that don’t meet the fundamental challenges faced by enterprise SOC teams in the early 2020s is not sustainable.
The following is an excerpt from our recent whitepaper, “Why Traditional Cybersecurity Tools Cannot Defend Against Zero-Day and No Signature Attacks,” in which we dive into how traditional cybersecurity tools work, why this fundamentally limits them from being able to detect zero-day or previously unknown attacks, why the industry standard for breach detection is around …
Most customers are surprised to learn that SOAR platforms rely on invoking 3rd party technologies, including next-generation firewalls and endpoint protection platforms via traditional API calls to isolate and quarantine malicious threats and users.