#user and entity behavioral analytics (ueba)

[xaltius]

A Data Leak Detection Guide for the Tech Industry in 2025

For the tech industry, data is more than just information; it's the lifeblood of innovation, intellectual property, and customer trust. A data leak – the unauthorized exposure of sensitive information – can be an existential threat, far more insidious than a visible malware attack. Leaks can trickle out slowly, going unnoticed for months, or erupt in a sudden torrent, exposing source code, customer PII, design documents, or proprietary algorithms.

In 2025's hyper-connected, cloud-centric, and API-driven world, detecting these leaks is a unique and paramount challenge. The sheer volume of data, the distributed nature of development, extensive third-party integrations, and the high value of intellectual property make tech companies prime targets. Proactive, multi-layered detection is no longer optional; it's essential for survival.

Here's a comprehensive guide to detecting data leaks in the tech industry in 2025:

1. Advanced Data Loss Prevention (DLP) & Cloud Security Posture Management (CSPM)

Gone are the days of basic keyword-based DLP. In 2025, DLP needs to be intelligent, context-aware, and integrated deeply with your cloud infrastructure.

Next-Gen DLP: Deploy DLP solutions that leverage AI and machine learning to understand the context of data, not just its content. This means identifying sensitive patterns (e.g., PII, PHI, financial data), source code fragments, and intellectual property across endpoints, networks, cloud storage, and collaboration tools. It can detect unusual file transfers, unauthorized sharing, or attempts to print/download sensitive data.

Integrated CSPM: For tech companies heavily invested in cloud, Cloud Security Posture Management (CSPM) is non-negotiable. It continuously monitors your cloud configurations (AWS, Azure, GCP) for misconfigurations that could expose data – like publicly accessible S3 buckets, overly permissive IAM roles, or unencrypted databases. A misconfigured cloud asset is a leak waiting to happen.

2. User and Entity Behavior Analytics (UEBA) Powered by AI

Data leaks often stem from compromised accounts or insider threats. UEBA helps you spot deviations from the norm.

Behavioral Baselines: UEBA tools use AI to learn the "normal" behavior patterns of every user (employees, contractors, customers) and entity (servers, applications) in your environment. This includes typical login times, locations, data access patterns, and resource usage.

Anomaly Detection: When behavior deviates significantly from the baseline – perhaps a developer suddenly downloading gigabytes of source code, an administrator accessing systems outside their routine hours, or a sales executive emailing large customer lists to a personal address – UEBA flags it as a high-risk anomaly, indicating a potential compromise or malicious insider activity.

Prioritized Alerts: UEBA helps cut through alert fatigue by assigning risk scores, allowing security teams to focus on the most critical threats that signify potential data exfiltration.

3. Network Traffic Analysis (NTA) with Deep Packet Inspection

Even if data bypasses endpoint or application controls, it still has to travel across the network. NTA is your eyes and ears for data exfiltration.

Real-time Monitoring: NTA (often part of Network Detection and Response - NDR) continuously monitors all network traffic – internal and external – using deep packet inspection and machine learning.

Exfiltration Signatures: It identifies suspicious patterns like unusually large outbound data transfers, communication with known command-and-control (C2) servers, attempts to tunnel data over non-standard ports, or encrypted traffic to unusual destinations.

Detecting Post-Compromise Movement: NTA is crucial for detecting lateral movement by attackers within your network and the final stages of data exfiltration, often providing the earliest warning of a breach in progress.

4. Specialized Source Code & Repository Monitoring

For the tech industry, source code is the crown jewel, and its accidental or malicious leakage can be catastrophic.

VCS Integration: Deploy solutions that deeply integrate with your Version Control Systems (Git, GitHub, GitLab, Bitbucket) and internal code repositories.

Credential/Secret Detection: These tools scan commits and push requests for hardcoded credentials, API keys, private keys, and other sensitive information that could be accidentally committed and exposed.

IP Leakage Prevention: They monitor for unauthorized pushes to public repositories, large-scale cloning or downloading of proprietary code, and suspicious activity within the development pipeline, acting as a crucial line of defense against intellectual property theft.

5. Dark Web & Open-Source Intelligence (OSINT) Monitoring

Sometimes, the first sign of a leak appears outside your perimeter.

Proactive Reconnaissance: Subscribe to specialized dark web monitoring services that scan illicit marketplaces, forums, paste sites (like Pastebin), and private channels for mentions of your company, leaked credentials (emails, passwords), customer data samples, or even fragments of proprietary code.

Public Repository Scans: Regularly scan public code repositories (like public GitHub, GitLab) for inadvertently exposed internal code or configuration files.

Early Warning System: These services provide crucial early warnings, allowing you to invalidate compromised credentials, assess the scope of a leak, and respond before widespread damage occurs.

6. API Security Monitoring

Modern tech stacks are heavily reliant on APIs. A compromised API can be a wide-open door for data exfiltration.

API Traffic Baselines: Establish baselines for normal API call volumes, types, and user access patterns.

Anomaly Detection: Monitor for unusual API call spikes, unauthorized access attempts (e.g., using stolen API keys), attempts to bypass authentication/authorization, or large data extractions via API calls that deviate from normal usage.

Automated Response: Integrate API security solutions with your WAFs and SIEMs to automatically block malicious API requests or revoke compromised keys.

Beyond Detection: The Response Imperative

Detecting a leak is only half the battle. A well-rehearsed incident response plan is critical. This includes clear steps for containment, investigation, eradication, recovery, and communication. Regular tabletop exercises and simulations are vital to ensure your team can act swiftly and decisively when a leak is detected.

In 2025, data leaks are an existential threat to the tech industry. By adopting a multi-faceted, AI-driven detection strategy, deeply integrated across your infrastructure and focused on both human and technical anomalies, you can significantly enhance your ability to spot and stop leaks before they spiral into full-blown crises, safeguarding your innovation and maintaining customer trust.

[coredgeblogs]

Top Cloud Security Challenges in 2025—and How to Solve Them

As cloud adoption accelerates in 2025, so do the complexities of securing cloud environments. From sophisticated threats to regulatory pressures and misconfigurations, organizations face a dynamic and evolving cloud security landscape. This blog explores the top cloud security challenges in 2025—and actionable strategies to overcome them.

1. Misconfigurations and Human Error

Challenge:

Despite advances in automation, cloud misconfigurations remain the leading cause of data breaches. These errors often arise from overly permissive IAM policies, unencrypted storage buckets, or default security settings left unchanged.

Solution:

Implement Infrastructure as Code (IaC) with security baked in.

Use automated cloud security posture management (CSPM) tools.

Regularly conduct compliance audits and red team assessments.

2. Identity and Access Management (IAM) Complexity

Challenge:

As organizations adopt multi-cloud and hybrid environments, managing identity and access across platforms has become increasingly difficult. Poorly managed IAM can lead to privilege escalation and lateral movement by attackers.

Solution:

Enforce least privilege access and zero trust principles.

Use federated identity and single sign-on (SSO).

Continuously monitor access with behavioral analytics.

3. Supply Chain and Third-Party Risks

Challenge:

In 2025, supply chain attacks have become more sophisticated, targeting third-party APIs, open-source software, and CI/CD pipelines integrated into cloud workflows.

Solution:

Perform SBOM (Software Bill of Materials) assessments.

Use runtime security tools to detect anomalous behavior.

Vet vendors with strict security SLAs and continuous assessments.

4. Data Residency and Compliance

Challenge:

Global data privacy regulations (like GDPR, CCPA, and new regional laws) impose strict controls on where and how data is stored. Multi-national businesses struggle to maintain compliance across jurisdictions.

Solution:

Use geo-fencing and cloud-native encryption with customer-managed keys.

Choose cloud providers that offer region-specific data control.

Automate data classification and policy enforcement.

5. Insider Threats

Challenge:

Insider threats—whether malicious or negligent—pose significant risks to cloud environments, especially where sensitive data and critical infrastructure are involved.

Solution:

Deploy User and Entity Behavior Analytics (UEBA).

Establish segregation of duties and audit trails.

Provide regular security awareness training.

6. API and Microservices Vulnerabilities

Challenge:

APIs and microservices are the backbone of modern cloud-native applications, but they expand the attack surface. Common issues include broken authentication, excessive data exposure, and lack of rate limiting.

Solution:

Use API gateways with integrated security policies.

Adopt OpenAPI/Swagger specifications to enforce standards.

Regularly scan APIs for OWASP Top 10 vulnerabilities.

7. Ransomware and Extortionware in the Cloud

Challenge:

Ransomware is evolving to target cloud workloads, backups, and even object storage. Attackers now combine encryption with data theft to pressure victims.

Solution:

Implement immutable backups and multi-versioning.

Use behavioral threat detection for unusual file access patterns.

Employ endpoint detection and response (EDR) across cloud workloads.

8. Inadequate Visibility and Monitoring

Challenge:

Cloud environments—especially multi-cloud—often suffer from fragmented logging and monitoring, creating blind spots for security teams.

Solution:

Centralize logs using SIEM/SOAR platforms.

Deploy cloud-native monitoring tools (e.g., AWS CloudTrail, Azure Monitor).

Enable real-time alerting with correlation rules and ML-based anomaly detection.

Final Thoughts

Cloud security in 2025 demands a proactive, layered, and automated approach. It’s no longer about protecting the perimeter—because in the cloud, the perimeter is dynamic, ephemeral, and everywhere.

Security leaders must focus on:

Automation and continuous compliance

Identity-first security

Unified monitoring and response

Secure software development lifecycle (SSDLC)

Ready to Secure Your Cloud Future?

Partner with cloud-native security platforms, invest in team education, and make security a shared responsibility across development, operations, and governance teams.

[industrynewsupdates]

Key Drivers Fueling Growth in the Application Security Market

According to a new report released by Grand View Research, Inc., the global application security market is projected to reach a valuation of USD 25.10 billion by the year 2030. This growth reflects a strong compound annual growth rate (CAGR) of 18.7% over the forecast period from 2024 to 2030. The increasing severity and frequency of cybersecurity threats across the digital landscape are key factors driving the expansion of the global application security industry. As organizations become more dependent on web and mobile applications for day-to-day operations, these platforms have become increasingly vulnerable and attractive targets for cyberattacks. In response to the evolving threat landscape and the rising sophistication of cybercriminals, enterprises are prioritizing the implementation of robust application security solutions to protect sensitive and confidential data.

A notable trend shaping the future of application security is the integration of artificial intelligence (AI) into existing cybersecurity frameworks. The application of AI technologies, including subsets such as machine learning (ML) and expert systems, is expected to significantly enhance the effectiveness of application security solutions. These AI-driven systems are being employed to anticipate potential security threats, detect existing vulnerabilities, and recommend appropriate code-level remediation strategies by leveraging predictive analytics and inference capabilities.

In particular, AI’s ability to learn and adapt makes it highly valuable in the development of advanced tools such as User and Entity Behavior Analytics (UEBA). These tools can analyze patterns in user behavior across servers and endpoints to detect anomalies that may signal a potential cyberattack—often even before the vulnerability is officially recognized or addressed by developers. By enabling proactive threat detection and faster incident response, the integration of AI and ML technologies is expected to substantially boost the demand for application security solutions during the forecast period.

Furthermore, the growing emphasis on data privacy and regulatory compliance is also driving the market forward. Regulatory frameworks such as the General Data Protection Regulation (GDPR) in Europe, the Health Insurance Portability and Accountability Act (HIPAA) in the United States, and mandates from India’s Central Consumer Protection Authority, among others, are pushing organizations to implement stringent security measures. These regulations require businesses to uphold strict data protection standards and implement adequate safeguards to prevent data breaches and misuse. Failure to comply can result in substantial financial penalties and reputational damage, making application security tools a critical component of organizational risk management strategies.

Consequently, the rising need to adhere to complex regulatory requirements is compelling companies across diverse sectors to adopt advanced application security solutions. These tools help organizations not only meet compliance demands but also enhance overall security posture, thereby contributing to the steady expansion of the application security market.

Curious about the Application Security Market? Get a FREE sample copy of the full report and gain valuable insights.

The FAQs about the Application Security Market highlight its size, growth rate, key players, and technological segments.

1. How big is the application security market?

The global application security market size was estimated at USD 7.57 billion in 2023 and is expected to reach USD 8.98 billion in 2024.

2. What is the application security market growth?

The global application security market is expected to grow at a compound annual growth rate of 18.7% from 2024 to 2030 to reach USD 25.10 billion by 2030.

3. Which segment accounted for the largest application security market share?

Solution offering led the market and accounted for more than 67.0% of the global revenue in 2023. Application security solutions identify and manages open source and third-party component risks in the development and production of application security platforms. Additionally, application security solutions identify and concentrate on the highest-priority issues by aggregating risk scores based on software composition, static, and dynamic analysis when users filter across multiple security tests.

4. Who are the key players in application security market?

Some key players operating in the application security market include Capgemini, CAST Software, Checkmarx, Cisco Systems, Inc., and F5, Inc., GitLab, HCL Technologies Ltd , International Business Machines Corporation, MicroFocus, Onapsis, Rapid7, Synopsys, Inc., Veracode, VMware, and WhiteHat Security.

5. What are the factors driving the application security market?

The growing cybersecurity threats are one of the main factors propelling the global application security market. In addition, due to the increasing reliance on the internet and digital technology, applications are now a prime target for cyberattacks. Thus, driving the market demand of the application security market.

Order a free sample PDF of the Application Security Market Intelligence Study, published by Grand View Research.

[basheeransari]

The Role of Managed IT Services in Cybersecurity & Cloud-Managed IT Services

Let’s be honest—cyber threats aren’t just the stuff of action movies. Your business isn't fighting off rogue hackers in hoodies from dimly lit basements (or maybe it is, who knows?). In reality, cyber threats are stealthier, smarter, and more relentless than ever.

Enter Managed IT Services—your digital bodyguards, working behind the scenes to keep your data safe. And when it comes to cloud-managed IT? It’s like giving your business a VIP pass to efficiency, scalability, and airtight security.

Let’s break it down—with the technical muscle to back it up.

1. The Role of Managed IT Services in Cybersecurity: Protecting Your Digital Assets

Cyber threats like ransomware, phishing, and insider attacks are relentless. Managed IT Services act as your 24/7 security command center, blending cutting-edge tools and frameworks to outsmart threats.

1.1 Advanced Security Operations Center (SOC): The Nerve Center

SIEM (Security Information and Event Management): Aggregates logs from firewalls, cloud apps, and endpoints to detect anomalies in real time. For example, SIEM tools like Splunk or LogRhythm correlate login attempts across systems to flag brute-force attacks.

SOAR (Security Orchestration, Automation, and Response): Automates threat containment, slashing response times. Imagine automatically isolating a compromised server before ransomware spreads.

XDR (Extended Detection and Response): Unified visibility across networks, endpoints, and cloud environments. XDR platforms like CrowdStrike Falcon uncover hidden threats in multi-cloud setups.

Threat Intelligence Feeds: Constantly updated feeds track new malware variants, vulnerabilities, and cybercrime tactics, allowing preemptive defense strategies.

1.2 Zero Trust Architecture (ZTA): No More Blind Trust

Micro-Segmentation: Limits lateral movement by isolating network segments. For instance, separating finance data from general employee access.

MFA & IAM: Multi-factor authentication and role-based access ensure only verified users get in. Tools like Okta enforce least-privilege access.

EDR (Endpoint Detection and Response): Monitors endpoints for behavioral anomalies, such as unusual file encryption patterns signaling ransomware.

Continuous Authentication: AI-driven authentication models assess user behavior dynamically, reducing risks of credential-based attacks.

1.3 AI-Driven Threat Detection: Outsmarting Attackers

UEBA (User and Entity Behavior Analytics): Uses machine learning to flag suspicious activity (e.g., Dave in accounting suddenly accessing sensitive files at 3 AM).

Predictive Analytics: Anticipates attack vectors using historical data. For example, identifying phishing campaigns targeting your industry.

Deep Learning-Based Malware Detection: Identifies previously unknown threats by analyzing patterns and behaviors rather than signatures.

1.4 Compliance Frameworks: Building a Regulatory Fortress

Managed IT Services align with frameworks like:

NIST Cybersecurity Framework (CSF): Risk-based strategies for identifying, protecting, and recovering from threats.

MITRE ATT&CK: Simulates real-world attacks to harden defenses. Red team exercises mimic APT groups like Lazarus.

CIS Controls: Automates audits for critical safeguards like data encryption and access controls.

ISO 27001 & GDPR Compliance: Ensures global security standards are met.

Case Study: A healthcare client reduced HIPAA violation risks by 80% through encrypted EHR systems and quarterly audits.

2. Cloud-Managed IT Services: Efficiency Meets Enterprise-Grade Security

Imagine an IT team that never sleeps, scales on demand, and cuts costs—all while securing your data. That’s cloud-managed IT.

2.1 Cloud Security Posture Management (CSPM)

Scans for misconfigured storage buckets (e.g., exposed AWS S3 instances). Tools like Palo Alto Prisma Cloud auto-remediate gaps.

Monitors IAM permissions to prevent overprivileged access. For example, revoking admin rights for temporary contractors.

Automated Compliance Audits: Ensures cloud environments align with regulatory policies.

2.2 Secure Access Service Edge (SASE)

Integrates Zero Trust with cloud-delivered security:

CASB (Cloud Access Security Broker): Secures SaaS apps like Office 365.

SWG (Secure Web Gateway): Blocks malicious URLs in real time.

FWaaS (Firewall as a Service): Replaces legacy hardware with scalable cloud firewalls.

ZTNA (Zero Trust Network Access): Prevents unauthorized access through software-defined perimeters.

2.3 Disaster Recovery as a Service (DRaaS)

Immutable Backups: Unalterable backups ensure data integrity. Veeam and Rubrik prevent ransomware from corrupting backups.

Multi-Region Failover: Keeps businesses running during outages. A retail client maintained uptime during an AWS outage by failing over to Azure.

Automated Recovery Testing: Regular tests ensure recovery strategies remain effective.

2.4 Cost Savings & Flexibility

Pay-as-you-go: Only pay for the cloud resources you use. Startups save 40% compared to on-premise setups.

Infrastructure as Code (IaC): Automates deployments using Terraform or AWS CloudFormation, reducing human error.

Statistic: Gartner predicts 60% of enterprises will use cloud-managed services by 2025 for cost and agility benefits.

Resource Optimization Strategies: AI-driven cloud cost optimization minimizes wasteful spending.

3. Incident Response and Disaster Recovery: When Seconds Matter

3.1 Automated Incident Response

Prebuilt Playbooks: For ransomware, isolate infected devices and trigger backups. For DDoS, reroute traffic via CDNs like Cloudflare.

Threat Containment: Automated network isolation of compromised assets. A financial firm contained a breach in 12 minutes vs. 4 hours manually.

AI-Based Incident Prediction: Uses past incidents to anticipate and mitigate future threats proactively.

3.2 Next-Gen Firewalls (NGFW)

Deep Packet Inspection (DPI): Uncovers hidden malware in encrypted traffic.

Behavioral Analytics: Detects zero-day exploits by analyzing traffic patterns.

Deception Technology: Uses decoy systems to detect attackers before they reach critical systems.

3.3 Digital Forensics and Threat Hunting

Malware Analysis: Reverse-engineers ransomware to identify kill switches.

Proactive Hunting: Combines AI alerts with human expertise. One MSP uncovered a dormant APT group during a routine hunt.

Blockchain-Based Security Logging: Ensures forensic logs remain immutable and tamper-proof.

4. Choosing the Right Managed IT Service Provider

4.1 Key Evaluation Criteria

Expertise in Frameworks: Look for NIST, ISO 27001, or CIS certifications.

24/7 Support: Ensure SOC teams operate in shifts for round-the-clock coverage.

Industry Experience: Healthcare providers need HIPAA experts; fintechs require PCI DSS mastery.

Customization Capabilities: Managed IT should be tailored to unique business needs.

4.2 In-House vs. Managed Services: A Cost Comparison

Mid-Sized Business Example:

In-House: $200k/year for salaries, tools, and training.

Managed Services: $90k/year with predictable pricing and no overhead.

5. Conclusion: Future-Proof Your Business

Cyber threats evolve, but so do Managed IT Services. With AI, Zero Trust, and cloud agility, businesses can stay ahead of attackers.

At Hardwin Software Solutions, we merge 24/7 SOC vigilance, compliance expertise, and scalable cloud solutions to shield your business.

📞 Contact us today—because cybercriminals don’t wait, and neither should you.

FAQs : 

1. How long does it take to onboard Managed IT Services, and when will we see results?

Onboarding: Typically 2–4 weeks, depending on infrastructure complexity. This includes risk assessments, tool integration (e.g., SIEM, XDR), and policy alignment.

Results: Proactive threat detection begins immediately, but full optimization (e.g., AI-driven threat modeling, Zero Trust implementation) takes 60–90 days.

2. Can Managed IT Services integrate with our legacy systems, or do we need a full infrastructure overhaul?

Yes! Managed IT providers use hybrid frameworks to secure legacy systems:

API-based integrations for outdated software.

Network segmentation to isolate legacy systems from modern attack surfaces.

Virtual patching to shield unpatched legacy apps from exploits.

3. How do you defend against AI-powered cyberattacks, like deepfake phishing or adaptive malware?

We counter AI-driven threats with:

Behavioral AI models: Detect anomalies in communication patterns (e.g., deepfake voice calls).

Adversarial Machine Learning: Trains defense systems to recognize AI-generated attack patterns.

Threat Hunting Teams: Human experts validate AI alerts to avoid false positives.

4. Do you offer industry-specific compliance solutions beyond HIPAA and GDPR (e.g., CMMC for defense contractors)?

Absolutely. We tailor compliance to your sector:

CMMC for defense contractors.

PCI DSS for payment processors.

FERPA for education.

Custom audits and controls to meet frameworks like NERC CIP (energy) or ISO 27701 (privacy).

5. How do you measure the ROI of Managed IT Services for stakeholders?

We quantify ROI through:

MTTD/MTTR Reductions: Track mean time to detect/respond to incidents (e.g., 30% faster threat neutralization).

Downtime Costs: Calculate savings from preventing outages (e.g., $10K/minute saved for e-commerce).

Compliance Penalty Avoidance: Estimate fines dodged via audit-ready systems.

Productivity Metrics: Reduced IT ticket volume (e.g., 50% fewer disruptions).

[jcmarchi]

Saryu Nayyar, CEO and Founder of Gurucul – Interview Series

New Post has been published on https://thedigitalinsider.com/saryu-nayyar-ceo-and-founder-of-gurucul-interview-series/

Saryu Nayyar, CEO and Founder of Gurucul – Interview Series

Saryu Nayyar is an internationally recognized cybersecurity expert, author, speaker and member of the Forbes Technology Council. She has more than 15 years of experience in the information security, identity and access management, IT risk and compliance, and security risk management sectors.

She was named EY Entrepreneurial Winning Women in 2017. She has held leadership roles in security products and services strategy at Oracle, Simeio, Sun Microsystems, Vaau (acquired by Sun) and Disney. Saryu also spent several years in senior positions at the technology security and risk management practice of Ernst & Young.

Gurucul is a cybersecurity company that specializes in behavior-based security and risk analytics. Its platform leverages machine learning, AI, and big data to detect insider threats, account compromise, and advanced attacks across hybrid environments. Gurucul is known for its Unified Security and Risk Analytics Platform, which integrates SIEM, UEBA (User and Entity Behavior Analytics), XDR, and identity analytics to provide real-time threat detection and response. The company serves enterprises, governments, and MSSPs, aiming to reduce false positives and accelerate threat remediation through intelligent automation.

What inspired you to start Gurucul in 2010, and what problem were you aiming to solve in the cybersecurity landscape?

Gurucul was founded to help Security Operations and Insider Risk Management teams obtain clarity into the most critical cyber risks impacting their business. Since 2010 we’ve taken a behavioral and predictive analytics approach, rather than rules-based, which has generated over 4,000+ machine learning models that put user and entity anomalies into context across a variety of different attack and risk scenarios. We’ve built upon this as our foundation, moving from helping large Fortune 50 companies solve Insider Risk challenges, to helping companies gain radical clarity into ALL cyber risk. This is the promise of REVEAL, our unified and AI-Driven Data and Security Analytics platform. Now we’re building on our AI mission with a vision to deliver a Self-Driving Security Analytics platform, using Machine Learning as our foundation but now layering on Generative and Agentic AI capabilities across the entire threat lifecycle. The goal is for analysts and engineers to spend less time in the myriad in complexity and more time focused on meaningful work. Allowing machines to amplify the definition of their day-to-day activities.

Having worked in leadership roles at Oracle, Sun Microsystems, and Ernst & Young, what key lessons did you bring from those experiences into founding Gurucul?

My leadership experience at Oracle, Sun Microsystems, and Ernst & Young strengthened my ability to solve complex security challenges and provided me with an understanding of the challenges that Fortune 100 CEOs and CISOs face. Collectively, it allowed me to gain a front-row seat the technological and business challenges most security leaders face and inspired me to build solutions to bridge those gaps.

How does Gurucul’s REVEAL platform differentiate itself from traditional SIEM (Security Information and Event Management) solutions?

Legacy SIEM solutions depend on static, rule-based approaches that lead to excessive false positives, increased costs, and delayed detection and response. Our REVEAL platform is fully cloud-native and AI-driven, utilizing advanced machine learning, behavioral analytics, and dynamic risk scoring to detect and respond to threats in real time. Unlike traditional platforms, REVEAL continuously adapts to evolving threats and integrates across on-premises, cloud, and hybrid environments for comprehensive security coverage. Recognized as the ‘Most Visionary’ SIEM solution in Gartner’s Magic Quadrant for three consecutive years, REVEAL redefines AI-driven SIEM with unmatched precision, speed, and visibility. Furthermore, SIEMs struggle with a data overload problem. They are too expensive to ingest everything needed for complete visibility and even if they do it just adds to the false positive problem. Gurucul understands this problem and it’s why we have a native and AI-driven Data Pipeline Management solution that filters non-critical data to low-cost storage, saving money, while retaining the ability to run federated search across all data. Analytics systems are a “garbage in, garbage out��� situation. If the data coming in is bloated, unnecessary or incomplete then the output will not be accurate, actionable or ultimately trusted.

Can you explain how machine learning and behavioral analytics are used to detect threats in real time?

Our platform leverages over 4,000 machine learning models to continuously analyze all relevant datasets and identify anomalies and suspicious behaviors in real time. Unlike legacy security systems that rely on static rules, REVEAL uncovers threats as they emerge. The platform also utilizes User and Entity Behavior Analytics (UEBA) to establish baselines of normal user and entity behavior, detecting deviations that could indicate insider threats, compromised accounts, or malicious activity. This behavior is further contextualized by a big data engine that correlates, enriches and links security, network, IT, IoT, cloud, identity, business application data and both internal and external sourced threat intelligence. This informs a dynamic risk scoring engine that assigns real-time risk scores that help prioritize responses to critical threats. Together, these capabilities provide a comprehensive, AI-driven approach to real-time threat detection and response that set REVEAL apart from conventional security solutions.

How does Gurucul’s AI-driven approach help reduce false positives compared to conventional cybersecurity systems?

The REVEAL platform reduces false positives by leveraging AI-driven contextual analysis, behavioral insights, and machine learning to distinguish legitimate user activity from actual threats. Unlike conventional solutions, REVEAL refines its detection capabilities over time, improving accuracy while minimizing noise. Its UEBA detects deviations from baseline activity with high accuracy, allowing security teams to focus on legitimate security risks rather than being overwhelmed by false alarms. While Machine Learning is a foundational aspect, generative and agentic AI play a significant role in further appending context in natural language to help analysts understand exactly what is happening around an alert and even automate the response to said alerts.

What role does adversarial AI play in modern cybersecurity threats, and how does Gurucul combat these evolving risks?

First all we’re already seeing adversarial AI being applied to the lowest hanging fruit, the human vector and identity-based threats. This is why behavioral, and identity analytics are critical to being able to identify anomalous behaviors, put them into context and predict malicious behavior before it proliferates further. Furthermore, adversarial AI is the nail in the coffin for signature-based detection methods. Adversaries are using AI to evade these TTP defined detection rules, but again they can’t evade the behavioral based detections in the same way. SOC teams are not resourced adequately to continue to write rules to keep pace and will require a modern approach to threat detection, investigation and response. Behavior and context are the key ingredients.  Finally, platforms like REVEAL depend on a continuous feedback loop and we’re constantly applying AI to help us refine our detection models, recommend new models and inform new threat intelligence our entire ecosystem of customers can benefit from.

How does Gurucul’s risk-based scoring system improve security teams’ ability to prioritize threats?

Our platform’s dynamic risk scoring system assigns real-time risk scores to users, entities, and actions based on observed behaviors and contextual insights. This enables security teams to prioritize critical threats, reducing response times and optimizing resources. By quantifying risk on a 0–100 scale, REVEAL ensures that organizations focus on the most pressing incidents rather than being overwhelmed by low-priority alerts. With a unified risk score spanning all enterprise data sources, security teams gain greater visibility and control, leading to faster, more informed decision-making.

In an age of increasing data breaches, how can AI-driven security solutions help organizations prevent insider threats?

Insider threats are an especially challenging security risk due to their subtle nature and the access that employees possess. REVEAL’s UEBA detects deviations from established behavioral baselines, identifying risky activities such as unauthorized data access, unusual login times, and privilege misuse. Dynamic risk scoring also continuously assesses behaviors in real time, assigning risk levels to prioritize the most pressing insider risks. These AI-driven capabilities enable security teams to proactively detect and mitigate insider threats before they escalate into breaches. Given the predictive nature of behavioral analytics Insider Risk Management is race against the clock. Insider Risk Management teams need to be able to respond and collaborate quickly, with privacy top-of-mind. Context again is critical here and appending behavioral deviations with context from identity systems, HR applications and all other relevant data sources gives these teams the ammunition to quickly build and defend a case of evidence so the business can respond and remediate before data exfiltration occurs.

How does Gurucul’s identity analytics solution enhance security compared to traditional IAM (identity and access management) tools?

Traditional IAM solutions focus on access control and authentication but lack the intelligence and visibility to detect compromised accounts or privilege abuse in real time. REVEAL goes beyond these limitations by leveraging AI-powered behavioral analytics to continuously assess user risk, dynamically adjust risk scores, and enforce adaptive access entitlements, minimizing misuse and illegitimate privileges. By integrating with existing IAM frameworks and enforcing least-privilege access, our solution enhances identity security and reduces the attack surface. The problem with IAM governance is identity system sprawl and the lack of interconnectedness between different identity systems. Gurucul gives teams a 360° view of their identity risks across all identity infrastructure. Now they can stop rubber stamping access but rather take risk-oriented approach to access policies. Furthermore, they can expedite the compliance aspect of IAM and demonstrate a continuous monitoring and fully holistic approach to access controls across the organization.

What are the key cybersecurity threats you foresee in the next five years, and how can AI help mitigate them?

Identity-based threats will continue to proliferate, because they have worked. Adversaries are going to double-down on gaining access by logging in either via compromising insiders or attacking identity infrastructure. Naturally insider threats will continue to be a key risk vector for many businesses, especially as shadow IT continues. Whether malicious or negligent, companies will increasingly need visibility into insider risk. Furthermore, AI will accelerate the variations of conventional TTPs, because adversaries know that is how they will be able to evade detections by doing so and it will be low cost for them to creative adaptive tactics, technics and protocols. Hence again why focusing on behavior in context and having detection systems capable of adapting just as fast will be crucial for the foreseeable future.

Thank you for the great interview, readers who wish to learn more should visit Gurucul. 

[deployvector]

Enhancing IT Security with Vector’s Threat Detection

In an era where cyber threats are more sophisticated than ever, the need for early threat detection for businesses has become more important. Cyberattacks are no longer a matter of "if" but "when." To combat these evolving threats, organizations must employ advanced security measures that ensure real-time protection. Vector offers a comprehensive suite of security tools designed to enhance cybersecurity, including advanced threat detection and proactive response mechanisms. With its cutting-edge AI-driven capabilities, Vector delivers unmatched security solutions that identify and mitigate risks before they escalate.

AI-Driven Threat Detection: The Future of IT Security

The cornerstone of Vector’s security is its AI-driven threat detection capabilities. By leveraging artificial intelligence (AI) and behavioral analytics, Vector can predict and detect anomalies across systems, identifying potential threats before they cause damage. Unlike traditional security methods, threat detection is not reactive but predictive, offering real-time analysis of activities and deviations from normal behavior patterns.

This proactive approach helps companies minimize the mean time to detect (MTTD) threats, enabling them to respond faster and more efficiently. With Vector, organizations can maximize true positives while reducing false positives, ensuring that security teams can focus on genuine risks rather than wasting time on irrelevant alerts.

Advanced Threat Detection and Response

Vector’s Security and Compliance Monitoring (SCM) module goes beyond basic detection with its advanced threat detection and response capabilities. Through User and Entity Behavior Analytics (UEBA), the system tracks the behavior of users and entities within the network, learning from past activities to identify suspicious behavior that may signal a breach. By continuously analyzing patterns and data, the system offers a dynamic and adaptable defense strategy against evolving cyber threats.

Security Orchestration, Automation, and Response (SOAR) further enhances Vector’s capabilities by automating the response process. This automation reduces the mean time to respond (MTTR) by offering guided response recommendations, ensuring swift action when a threat is identified. Automated playbooks allow for a quick and effective resolution to incidents, minimizing damage and disruption to business operations.

Ensuring Compliance and Secure Operations

In addition to threat detection, Vector also emphasizes compliance monitoring and reporting. Companies must maintain compliance with security standards such as ISO 27001 and SOC 2, and Vector ensures that these standards are met by continuously monitoring for any deviations. This proactive approach not only keeps businesses compliant but also identifies areas for improvement, ensuring that security operations are always aligned with best practices.

Vector's SCM module helps manage these compliance requirements by providing automated reports and alerts when potential compliance risks arise. By integrating compliance and security management, organizations can streamline their auditing processes and minimize the risk of penalties due to non-compliance.

Robust Data Protection

With data protection becoming a top priority, Vector provides multiple layers of security to safeguard sensitive information. Data encryption, both at rest and in transit, ensures that confidential information is protected from unauthorized access. Furthermore, access controls, including Role-based Access Control (RBAC) and Multi-factor Authentication (MFA), restrict who can access data, ensuring only authorized personnel have the necessary permissions.

To comply with privacy regulations like GDPR and CCPA, Vector incorporates advanced techniques such as data anonymization and pseudonymization, adding another layer of protection. This comprehensive data security strategy ensures that businesses can maintain confidentiality while adhering to global privacy standards.

Enhancing Network Security

Vector also excels in network security, utilizing robust firewall protocols, intrusion detection systems, and secure transmission methods to protect the network from unauthorized access and attacks. Regular vulnerability assessments ensure that potential weaknesses are identified and rectified before they can be exploited.

With continuous 24/7 monitoring and automated alerts, Vector ensures that organizations can quickly detect and respond to security incidents. Integration with Security Information and Event Management (SIEM) tools enhances its ability to manage incidents and investigate threats, keeping networks safe from malicious activity.

Conclusion

In an era where cyberattacks are a constant threat, leveraging advanced technologies like AI-driven threat detection is essential for safeguarding critical systems and data. Vector, with its SCM module, delivers an all-encompassing security solution that includes advanced threat detection, compliance monitoring, and automated incident response. By integrating AI and behavioral analytics, Vector empowers businesses to stay ahead of threats and maintain a secure digital environment.

From network security to data protection and compliance, Vector’s robust security architecture ensures that organizations are not only protected but also prepared to face the ever-evolving cyber landscape. 

Click here to learn more about Vector’s AI-driven threat detection and how it can protect your business from potential threats.

[roamnook]

"Varonis: #1 Data Security Platform delivering automated outcomes with deep data visibility, classification capabilities, and automated remediation for data access. Rated #1 overall in three Gartner Peer Insights markets."

Polarizing Facts: Unveiling the Power of Data Security - RoamNook

Polarizing Facts: Unveiling the Power of Data Security

Welcome to our blog post where we delve into the world of data security, bringing you hard facts, key information, and concrete data. In this informative content, we will explore the importance of data security and how it impacts individuals and organizations alike. Get ready to be amazed by the sheer power of data security solutions in protecting critical information from threats and cyberattacks.

The #1 Data Security Platform - Varonis

When it comes to data security, one name reigns supreme - Varonis. As the leading provider of data security solutions, Varonis offers an all-in-one SaaS platform that automatically identifies critical data, remediates exposure, and stops threats in the cloud and on-premises.

Automating Data Security Posture with DSPM

Data security posture plays a crucial role in safeguarding sensitive information. Varonis' Data Security Posture Management (DSPM) solution takes data security to the next level by improving your organization's data security posture automatically. Through advanced algorithms and machine learning, DSPM identifies vulnerabilities, enforces access controls, and detects and responds to threats in real-time.

Enhanced Security with AI

In the digital age, threats evolve rapidly, which is why Varonis has developed AI Security solutions. With secure AI copilots and LLMs (Limited License Members), Varonis leverages the power of artificial intelligence to detect abnormal activity from APTs (Advanced Persistent Threats) and insider threats. This ensures that organizations stay one step ahead of potential cyberattacks.

Discover, Classify, and Label Sensitive Data

Accurately discovering, classifying, and labeling sensitive data is paramount to data security. Varonis' Data Discovery & Classification solution utilizes advanced algorithms and machine learning to accurately identify sensitive data, enabling organizations to take the necessary steps to protect it effectively.

Monitor Cloud Data Activity and Prevent Exfiltration with Cloud DLP

As more data is stored in the cloud, protecting it becomes increasingly important. Varonis' Cloud Data Loss Prevention (DLP) solution monitors cloud data activity and prevents exfiltration. By continuously analyzing data access and usage patterns, Cloud DLP detects and alerts organizations to potential data breaches, enabling swift action to be taken.

Automate Compliance Regulations with Policy Automation

Compliance with regulations and frameworks is a critical element of data security. Varonis' Policy Automation solution ensures organizations achieve and maintain compliance by automating the enforcement of least privilege, labels, and secure settings. This not only streamlines the compliance process but also enhances overall data security.

Uncover Abnormal Activity with UEBA

Abnormal activity can often be an indication of a cyber threat. Varonis' User and Entity Behavior Analytics (UEBA) solution leverages advanced analytics and machine learning techniques to detect abnormal activity from APTs and insider threats. By analyzing user behavior patterns, UEBA helps organizations identify and respond to potential threats quickly.

24x7x365 Data Detection & Response with MDDR

Varonis' Managed Data Detection and Response (MDDR) solution provides round-the-clock data detection and response with a guaranteed SLA (Service Level Agreement). MDDR performs continuous monitoring, proactively identifying and responding to potential threats, and minimizing the impact of data breaches on organizations.

Fix Critical SaaS Misconfigurations with SSPM

Software as a Service (SaaS) applications are a common target for cyber threats. Varonis' SaaS Security Posture Management (SSPM) solution fixes critical SaaS misconfigurations and third-party app risks, helping organizations enhance their overall SaaS security posture and mitigate potential vulnerabilities.

Automate Compliance Regulations with Compliance Management

Compliance management is an essential aspect of data security. Varonis' Compliance Management solution automates compliance regulations and frameworks, making it easier for organizations to achieve and maintain compliance. With Varonis, compliance becomes streamlined and more efficient.

Lock Down Sensitive Mailboxes with Email Security

Email is a common attack vector for cybercriminals. Varonis' Email Security solution locks down sensitive mailboxes and prevents exfiltration. By monitoring email activity and analyzing attachments and content, Varonis detects and alerts organizations to potential email-based threats, safeguarding critical information.

Detect Attacks on AD, Entra ID, and Okta with Identity Security

Active Directory (AD), Entra ID, and Okta are essential components of an organization's identity infrastructure. Varonis' Identity Security solution detects attacks on these systems, helping organizations identify and respond to potential security breaches. By leveraging advanced analytics and threat intelligence, Identity Security helps keep identities secure.

Athena AI - Your AI SOC Analyst and Search Assistant

Varonis' Athena AI is a game-changer in the world of cybersecurity. By using advanced artificial intelligence algorithms, Athena AI offers AI-enabled security operations center (SOC) analytics and natural language search capabilities. This innovative solution empowers organizations to quickly detect and respond to the most complex cyber threats.

Platform Overview - Powering Digital Growth with Varonis

At RoamNook, we are proud to partner with Varonis to offer cutting-edge IT consultation, custom software development, and digital marketing solutions. As an innovative technology company, our main goal is to fuel digital growth. Varonis' powerful platform provides the foundation for organizations to achieve their digital transformation goals, with data security at the forefront.

Unveiling the Real-World Applications and Importance of Data Security

Data security is of paramount importance in today's digital landscape. By leveraging Varonis' advanced data security solutions, organizations can protect critical data from cyber threats, ensure compliance with regulations, and enhance overall data security posture. With automated processes, AI-driven insights, and continuous monitoring, Varonis empowers organizations to stay one step ahead of potential threats.

Conclusion: Reflecting on the Power of Data Security

As we conclude this insightful blog post, we invite you to reflect on the power of data security and its impact on individuals and organizations. How does data security affect your daily life? What steps can you take to enhance your own data security posture? Varonis provides the tools and expertise needed to navigate the complex world of data security. Reach out to us at RoamNook to learn more about how we can help you unlock the full potential of data security.

Source: https://www.varonis.com/blog/azure-virtual-network&sa=U&ved=2ahUKEwi_kM-g4smGAxWZEmIAHV0tAL4QFnoECAEQAw&usg=AOvVaw3TM0wDtIXWRhwp3902OGfN

[leotechnosblog]

Innovative UEBA Solution Changing the Game for Cybersecurity

Know UEBA  Security

In the ever-evolving landscape of cybersecurity, companies are constantly searching for the latest and most effective tools to protect their data and networks. Enter ueba (User and Entity Behavior Analytics), a revolutionary solution that is making waves in the industry.

One company leading the charge with their cutting-edge ueba product is CyberGuard Technologies. Their innovative software utilizes artificial intelligence and machine learning to analyze user behavior and detect anomalies that could indicate a potential threat.

UEBA Solution

"We saw a gap in the market for a more proactive approach to cybersecurity," says CEO John Smith. "Traditional solutions are reactive, but with ueba, we can identify and mitigate risks before they escalate."

This proactive approach has garnered attention from companies across industries, with many praising the effectiveness of CyberGuard's ueba solution. "Since implementing CyberGuard's product, we've seen a significant decrease in security incidents," says a satisfied customer.

With cyber threats becoming more sophisticated and prevalent, the need for advanced security solutions like ueba is greater than ever. Companies like CyberGuard Technologies are paving the way for a more secure digital future, one behavior analysis at a time.

[xaltius]

The Silent Intruder: How to Detect Identity Breaches?

In the complex tapestry of modern cybersecurity, headlines often blare about ransomware attacks and network intrusions. Yet, a more insidious and equally devastating threat often operates in the shadows: the identity breach. It's not always about a system being locked down; sometimes, it's about someone else quietly becoming you in the digital realm.

An identity breach occurs when an unauthorized party gains access to your personal information or credentials, allowing them to impersonate you for various malicious purposes – from financial fraud and account takeovers to tax fraud and even accessing medical services. The impact can be severe, affecting your finances, reputation, and peace of mind.

The key to mitigating damage from an identity breach is early detection. Here’s how individuals and organizations can spot the tell-tale signs.

Signs You (As an Individual) Might Be Compromised

Your personal identity is a prime target. Vigilance is your first line of defense:

Unexpected Account Lockouts or Password Reset Notifications: If you receive alerts about password changes or account lockouts that you didn't initiate, someone is likely trying to access your accounts.

Unusual Activity on Your Accounts: Spotting transactions you didn't make on bank or credit card statements, strange emails or social media posts coming from your accounts, or changes to your profile you didn't approve.

Strange Login Alerts: Receiving notifications about logins from unfamiliar locations, devices, or at odd hours. Many services offer these alerts – enable them!

Credit Report Anomalies: Discovering new accounts opened in your name, hard inquiries you didn't authorize, or unexpected dips in your credit score. Regularly check your credit reports from all three major bureaus.

Unexplained Medical Bills or Insurance Claims: If you receive bills for medical services you didn't receive, or your health insurance benefits are maxed out without explanation, it could indicate medical identity theft.

Tax Return Rejection or IRS Notices: If your tax return is rejected because one has already been filed in your name, or you receive an IRS notice about income from an unknown employer, your Social Security Number might be compromised.

Calls from Debt Collectors for Unfamiliar Debts: If collection agencies contact you about debts you don't recognize, it's a strong indicator of fraudulent accounts opened in your name.

Your Information on the Dark Web: If you subscribe to an identity theft protection service, they might alert you if your email, password, or other PII appears on breach data dumps on the dark web.

How Organizations Can Detect Identity Breaches (Proactive Measures)

For businesses, identity breaches often manifest as compromised employee or customer accounts, leading to data exfiltration, financial fraud, or further network penetration. Proactive monitoring is essential:

Centralized Identity and Access Management (IAM) Monitoring:

Anomalous Login Patterns: Monitoring for logins from unusual geographical locations, at odd hours, from unfamiliar devices, or multiple failed login attempts on a single account.

Privilege Escalation Attempts: Alerting on users attempting to gain higher access rights than their usual role.

Access to Unusual Resources: Flagging when a user accesses files, applications, or servers they normally wouldn't.

Tools: Security Information and Event Management (SIEM) systems and User and Entity Behavior Analytics (UEBA) platforms are crucial here.

Dark Web and Credential Monitoring Services:

Compromised Credentials: Subscribing to services that actively scan the dark web for leaked company credentials (usernames, email addresses, passwords) that could lead to account takeovers.

Brand Impersonation: Monitoring for fraudulent websites or social media accounts impersonating your brand, which could be used for phishing attacks targeting your employees or customers.

Endpoint Detection and Response (EDR) Alerts:

Suspicious Process Execution: Identifying unauthorized software installations, suspicious scripts, or processes running on employee endpoints that might indicate credential harvesting malware.

Unauthorized Data Access: Detecting attempts to access sensitive files or move data to unusual locations from an endpoint.

Network Traffic Analysis (NTA):

Unusual Data Exfiltration: Monitoring for large volumes of data leaving your network, especially from non-standard ports or to unusual external destinations.

Communication with Known Malicious Infrastructure: Detecting connections to known command-and-control (C2) servers or other malicious IPs.

Unauthorized Internal Lateral Movement: Identifying suspicious internal network activity that suggests an attacker is moving between systems after an initial compromise.

User Behavior Analytics (UBA/UEBA):

Establishing Baselines: UEBA tools learn the normal behavior patterns of individual users and groups.

Detecting Deviations: They flag significant deviations from these baselines – for example, an employee logging in from a country they've never visited, downloading an unprecedented amount of data, or attempting to access sensitive systems outside their role.

Regular Log Review and Correlation:

Aggregating Logs: Centralizing logs from all systems (authentication, firewall, application, cloud platforms) into a SIEM allows for correlation of seemingly disparate events.

Identifying Suspicious Event Sequences: A single failed login might be nothing, but a thousand failed logins followed by a successful login from a new IP is a clear red flag.

Steps to Take After Detection (Briefly)

Detecting an identity breach is just the first step. Rapid response is critical:

Isolate: Disconnect affected systems or accounts to prevent further damage.

Investigate: Determine the scope, source, and method of the breach.

Contain: Implement measures to stop the breach from spreading.

Eradicate: Remove the root cause of the breach and any malicious artifacts.

Recover: Restore systems and data from secure backups.

Communicate: Notify affected individuals and regulatory bodies as legally required.

Improve: Implement lessons learned to prevent future occurrences.

Prevention is Always Key

While detection is vital, a strong defensive posture reduces the likelihood of a breach in the first place:

Strong, Unique Passwords and Multi-Factor Authentication (MFA): The simplest yet most effective defense.

Employee Security Awareness Training: Educate staff on phishing, social engineering, and best security practices.

Regular Security Audits and Penetration Testing: Proactively find and fix vulnerabilities.

Patch Management: Keep all systems and software updated.

Data Minimization: Only collect and store the data you truly need.

In an age where identities are the new perimeter, understanding how to detect a breach – both personally and organizationally – is non-negotiable. By combining proactive monitoring with swift response, we can better protect ourselves and our valuable digital identities.

[brigitapvtltd]

What Is Cloud Infrastructure Entitlement Management (CIEM)?

Managing identities and privileges in cloud environments is known as cloud infrastructure entitlement management, or CIEEM. Understanding which access entitlements are present in cloud and multi cloud systems is the first step in CIEM's mission. Next, it aims to detect and reduce risks associated with entitlements that give users more access than is appropriate.  Security teams can control cloud identities and entitlements and implement the least-privileged access principle to cloud infrastructure and resources by using CIEM solutions. Businesses can lower their cloud attack surface and minimize access risks caused by granting too many permissions with the use of CIEM solutions. 

Why Is CIEM Important to Your Cloud Security Strategy?

Static self-hosted or on-premises infrastructure is subject to access controls thanks to traditional identity and access management (IAM) solutions. The cloud infrastructure, services, and apps that businesses use are becoming more dynamic and transient than their on-premises counterparts as more businesses shift to the cloud. 

To assist enterprises in enforcing granular IAM policies, cloud service providers Amazon Web Services (AWS), Microsoft Azure, and Google Cloud offer distinctive, native, cloud-based controls. Companies using a multicloud strategy may find it difficult to manage entitlements for each cloud environment because different cloud environments don't naturally integrate. Cloud security teams can manage all entitlements across multicloud settings and comprehend access risk with the aid of a CIEM solution. 

Security and risk management experts can find information on implementing technologies that facilitate the efficient administration of cloud infrastructure entitlements in the Managing Privileged Access in Cloud Infrastructure publication. The publications illustrate how security teams should utilize CIEM to detect and prioritize issues related to access control across public clouds and other infrastructure resources. Together, they define the fundamental meaning of CIEM.

What Are the Components of CIEM?

The four primary pillars of CIEM are advanced analytics, entitlement visibility, rightsizing permissions, and compliance. Knowing whether entitlements are present in your environment is the first step towards managing entitlements and reducing entitlement risks. To do this, CIEM tools automatically examine configurations, rules, and policies related to access control in order to ascertain:

Which rights are in place.

What each user, human or machine, is entitled to do in light of those rights.

Depending on their rights, which machine and human users can access whatever cloud resource.

CIEM tools identify entitlements and then evaluate them to see if the access capabilities they grant are the least essential to accomplishing the goal of the workload. Administrators can manually remedy the issue if CIEM tools inform them when an entitlement grants excessive access. Additionally, the technologies have the ability to automatically modify entitlements, enabling teams to function effectively in expansive settings. 

The entitlement evaluations carried out by CIEM tools rely on sophisticated analytics driven by machine learning in addition to user and entity behavior analytics (UEBA), as opposed to generic rules and conditions. Although CIEM is not just focused on compliance, its tools may automatically determine whether entitlements meet compliance criteria, allowing entitlements to be aligned with compliance requirements. Additionally, they are able to identify cases of "drift," in which configuration changes cause entitlements that were previously compliant to no longer be compliant. Having a more secure platform to enforce least-privileged access credentials across cloud providers and resources is the ultimate goal. 

How Is CIEM Used?

With the use of cutting-edge methods like machine learning, CIEM enables enterprises to suggest the least privileges for a specific type of activity.  For instance, a user might ask to access a production computer via SSH in order to examine an environment variable or confirm a configuration setting. To complete the task, the user might ask for temporary access to an SSH key pair. The user's request is approved by the security team, who then advises them to obtain the keys through an SSO provider. The user's access to the resources is revoked when they complete the necessary tasks, and they are unable to use those keys to access the computer ever again. 

How Does CIEM Improves Cloud Security?

According to the least privilege concept, entitlements are made up of effective permissions that are assigned by the cloud provider (IAM policies) to users, workloads, and data so they can carry out essential operations. Permissions can be readily overallocated to users or workloads in the absence of adequate entitlement monitoring and security enforcement.

Conclusion

Security teams may control cloud identities and entitlements and apply the least-privileged access concept to cloud infrastructure and services by employing CIEM solutions. By employing CIEM solutions, Brigita Business Solutions could assist you.

[maximizegn1]

In a groundbreaking revelation, the global User and Entity Behavior Analytics (UEBA) market is poised for an exceptional growth trajectory, anticipating a staggering 35.7% surge, propelling it to a substantial worth of nearly US$ 8.58 Billion by 2029. 

[esytes-encyclopedia]

AI and Cybersecurity: Battling Cyber Threats with Intelligent Solutions

AI and cybersecurity have become deeply interconnected, with artificial intelligence playing a pivotal role in battling cyber threats. The evolving nature of cyber threats, including sophisticated attacks and rapidly changing attack vectors, necessitates intelligent solutions that can adapt and respond in real time. Here's how AI is being used to enhance cybersecurity measures: 1. Threat Detection and Prevention: - Anomaly Detection: AI algorithms can analyze vast amounts of data to identify patterns and anomalies, helping in the early detection of potential threats. - Behavioural Analysis: AI can learn and understand normal user and system behaviour. Deviations from the norm can indicate a potential security breach. - Predictive Analysis: Machine learning algorithms can predict potential threats based on historical data and emerging trends. 2. Vulnerability Management: - Automated Vulnerability Assessment: AI can automate vulnerability scanning and prioritize vulnerabilities based on the level of risk, enabling organizations to focus on critical issues first. - Patch Management: artificial intelligence in security can assist in identifying the most suitable patches for specific vulnerabilities, speeding up the patching process. 3. Incident Response: - Automated Incident Triage: AI-powered systems can automatically categorize and prioritize incidents, allowing security teams to focus on the most critical issues first. - Playbook Automation: AI can execute predefined incident response playbooks, ensuring a rapid and consistent response to security incidents. 4. Phishing and Fraud Prevention: - Email Filtering: AI algorithms can analyze email content, sender behaviour, and context to identify phishing attempts and malicious emails. - Deep Learning for Fraud Detection: Deep learning techniques can identify fraudulent patterns in financial transactions and online activities. 5. User and Entity Behavior Analytics (UEBA): - Profile User Behavior: AI systems can create user profiles and detect deviations in real time, helping to identify compromised accounts. - Insider Threat Detection: AI can analyze user behaviour to detect potential insider threats, such as employees accessing sensitive data without authorization. 6. Network Security: - AI-Driven Firewalls: Firewalls powered by AI can dynamically adapt to changing network conditions and learn from cyber threats in real time. - Network Traffic Analysis: AI algorithms can analyze network traffic patterns to detect unusual activities and potential intrusions. 7. Cybersecurity Training and Awareness: - Simulated Phishing Attacks: AI-driven simulations can help organizations conduct realistic phishing attack simulations to train employees and raise awareness about cyber threats. - Interactive Training Modules: AI-powered interactive modules can provide personalized cybersecurity training based on individual learning needs and knowledge gaps. Challenges and Considerations: - Adversarial Attacks: Hackers can use AI to create sophisticated attacks, leading to the development of AI systems that can detect and defend against adversarial attacks. - Data Privacy: Ensuring that AI systems adhere to data privacy regulations and ethical standards is crucial to maintaining user trust. - Human Expertise: While AI can automate many tasks, human expertise is essential for interpreting AI-generated insights and making strategic decisions. Conclusion on AI and Cybersecurity The integration of AI vs cybersecurity is transforming the way organizations defend against cyber threats. By leveraging intelligent solutions, businesses can stay ahead of cybercriminals and respond effectively to the ever-changing cybersecurity landscape. However, it's important to continuously update the role of AI in cyber security systems, collaborate with cybersecurity experts, and stay informed about emerging threats to maintain a robust defence against cyber attacks. Read the full article

[exito123654]

Challenges of Implementing Cybersecurity Solutions for Remote & Hybrid work

Implementing cybersecurity solutions for remote and hybrid work environments presents several unique challenges due to the increased complexity and expanded attack surface. Here are some of the key challenges organizations face:

Expanded Attack Surface: With employees working from various locations and devices, the attack surface has significantly expanded. Cybersecurity teams must now secure not only the corporate network but also a multitude of home networks, public Wi-Fi, and personal devices.

Endpoint Security: Securing remote endpoints (laptops, smartphones, tablets) can be challenging. Ensuring that these devices are up to date with patches, have updated antivirus software, and are configured securely is crucial.

Data Protection: Protecting sensitive data becomes more complex when it's accessed from multiple locations. Ensuring that data is encrypted both in transit and at rest is essential, as is implementing access controls and data loss prevention measures.

Identity and Access Management (IAM): Managing user identities and ensuring appropriate access is a significant challenge. Implementing multi-factor authentication (MFA) is crucial, but it can be challenging to enforce, especially on personal devices.

Secure Remote Access: Providing secure remote access to corporate resources is vital. VPNs, secure tunnels, or zero-trust network access (ZTNA) solutions need to be implemented and maintained. These solutions must be both user-friendly and secure.

User Awareness and Training: Users working remotely may not have the same level of cybersecurity awareness and training as they would in the office. Cybersecurity education and training programs need to be adapted for remote workers.

Phishing and Social Engineering: Phishing attacks are on the rise, and remote workers may be more susceptible to them. Remote and hybrid workforces require robust email security solutions, as well as education on identifying and reporting phishing attempts.

Monitoring and Detection: Monitoring network and endpoint activity can be more challenging in remote environments. Security Information and Event Management (SIEM) systems and User and Entity Behavior Analytics (UEBA) tools can help, but they need to be configured to account for remote work patterns.

Compliance and Legal Issues: Remote work can introduce compliance and legal issues, especially when it comes to data privacy and international regulations. Ensuring that remote work practices align with relevant laws is essential.

Third-Party Risks: Many remote workers use third-party applications and services to perform their jobs. These third-party tools can introduce additional security risks. Organizations need to assess and monitor the security of these tools.

Resource Scalability: Handling a sudden increase in remote workers, such as during a crisis, can strain an organization's IT resources. Scalability and disaster recovery planning are essential.

Balancing Security and User Experience: Implementing stringent security measures can sometimes hinder user productivity and experience. Striking the right balance between security and user convenience is an ongoing challenge.

Patch and Update Management: Ensuring that all remote devices are kept up to date with security patches can be challenging, especially if devices are geographically dispersed.

Budget Constraints: Cybersecurity solutions often require significant financial investments. Remote work arrangements may force organizations to allocate additional resources to cybersecurity, which may not always be feasible.

Employee Privacy: Balancing cybersecurity with employee privacy can be challenging. Monitoring employee activities without infringing on their privacy rights is a delicate balance.

To address these challenges, organizations should adopt a comprehensive cybersecurity strategy that includes a combination of technology, policies, and user education. Additionally, regular risk assessments and threat intelligence updates are crucial for staying ahead of emerging cybersecurity threats in the remote and hybrid work landscape.

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