Google backs Exabeam for Unified Security. August 27, 2026 Google named Exabeam a Google Unified Security Recommended partner. Google launched this program in 2025 with three inaugural members: CrowdStrike, Fortinet and Wiz. Since then, Google has reportedly added Palo Alto Networks, with Exabeam now expected to join the list. This designation recognizes the strength of combining Exabeam New-Scale Analytics with Google Security Operations. Google SecOps' cloud-native security operations platform empowers security teams to better detect, investigate, and respond to cybersecurity threats. Exabeam extends Google SecOps with behavioural intelligence, enabling faster insider threat detection, investigation, and response. The Exabeam solution connects directly with Google Security Operations data, enabling users to work within a single integrated view. With Exabeam, users identify patterns and react faster to risks that remain hidden when viewing individual events. Using integrated data sharing, analysts apply Exabeam's behavioural intelligence to a wider dataset. This helps identify actual issues, flag false positives early and saves time on diagnosis. Pete Harteveld, CEO of Exabeam, commented, "Being named a Google Unified Security Recommended partner reflects the strength of our collaboration with Google Cloud and the value we deliver together for customers. "Security teams are struggling with alert overload. What they're missing is insight into the behaviors that represent real risk to their enterprise. Our work with Google Cloud brings this behavioral intelligence directly into Google Security Operations, helping customers identify abnormal activity in the context of behavior across both human users and AI agents." Unified solution. Both platforms run on Google Cloud, allowing security teams to share data without incurring egress charges. This removes the need to move data into a separate analytics environment and reduces operational complexity. The integration offers several additional benefits: * Accelerate TDIR workflows: Exabeam validation testing showed organizations accelerating TDIR workflows by up to 80%. * Detect insider risk earlier: Apply New-Scale Analytics to Google Security Operations data to identify high-risk activity across users, entities, service accounts, and AI agents. * Reduce analytics complexity: Use integrated data sharing to apply Behaviour Intelligence to data already in Google Security Operations without maintaining a separate analytics environment. * Available on Google Cloud Marketplace: Procure Exabeam New-Scale Analytics through Google Cloud Marketplace, where eligible purchases can apply toward existing Google Cloud spend commitments. * Secure both users and agents: Extend coverage to AI agents by analysing Gemini Enterprise Agent Platform and Model Armor activity alongside user behaviour, behavioural analytics, dynamic risk scoring, and agent-powered TDIR workflows to detect risky human and non-human identity activity. Securing AI agents is more important than ever. AI agents can now work across apps, tools, data and business processes. That makes them useful, but it also makes them harder to monitor. Google describes Google Unified Security as an AI-infused approach. It uses Gemini and threat intelligence to support security workflows at scale. While individual agent actions often resemble human behaviour and appear low-risk, significant concerns remain. Chen et al, in How Your Credentials Are Leaked by LLM Agent Skills: An Empirical Study (June 2026), found several examples. The study identified a cumulative risk: 73.5% of vulnerabilities stemmed from debug logging. Individually, a log statement is benign. However, when an agent executes 100+ tool invocations, and each logs a token, the cumulative exposure becomes a data exfiltration channel. It also identified that 89.6% of the affected agent skills were exploitable during routine execution without elevated privileges. Thus, proving that "normal" behaviour can still leak credentials when viewed as a sequence. Addressing the agentic challenge. Exabeam states its New-Scale Analytics adds behavioural analytics, dynamic risk scoring, and AI-powered investigations to Google Security Operations. The Exabeam solution integrates with Gemini Enterprise Agent Platform and Model Armor to mitigate this risk. * Gemini Enterprise Agent Platform helps organisations build, manage and govern enterprise AI agents. In this context, it provides activity signals that can be reviewed alongside other security data. * Model Armor gives teams more information about large language model activity, including prompts and responses, so that this activity can be assessed as part of security monitoring. Those signals can help security teams see how agents behave, which systems they use and where unusual activity may appear. Exabeam analyses this activity in New-Scale Fusion alongside user behaviour. It designed its New-Scale Analytics product to learn normal activity, apply risk scores, and highlight activity that needs investigation. Exabeam also says its Nova cybersecurity agents can support threat detection, investigation and response workflows by adding behavioural context and helping analysts prioritise work. Dr. Andre Alfred, Sr. Director, Cloud Security Threat Operations, Google Cloud, stated, "As organizations shift toward AI-driven security, operations and autonomous agents, open interoperability across the technology stack is vital. "The Google Unified Security Recommended program creates deep technical collaboration with market-leading security vendors to minimize integration overhead, enabling security teams to focus on outcomes rather than complexity. We're excited to welcome Exabeam to the Google Unified Security Recommended program to help customers strengthen their defenses with unified, AI-driven protection." Enterprise times: what does this mean. Using Exabeam's new scale analytics, security teams can better leverage its behavioural intelligence to spot anomalous patterns from both humans and agents. With agents now capable of performing many more tasks than humans, it is critical that organisations have the ability to track, monitor and analyse events faster than ever before. Using Exabeam and Google SecOps, teams can benchmark normal behaviour and better detect and identify anomalies. No matter how small, that signal compromised accounts, malicious insiders, or risky AI agent behaviour. Security teams can now better identify evolving trends and patterns through the platform. They can react faster and mitigate risks as they emerge. Google Security Operations customers can access Exabeam New-Scale Analytics through Google Cloud Marketplace, where eligible purchases count toward existing Google Cloud spend commitments.

Exabeam vs. Splunk: which approach improves security operations outcomes? * Jul 23, 2026 * Heidi Willbanks * 3 minutes to read Table of Contents Not every SIEM solution is built for modern security operations. While Splunk is widely used for log management, many teams face unpredictable pricing, complex tuning, and slow investigations as environments scale. New-Scale Fusion takes a different approach, It combines behavioral analytics, dynamic risk scoring, and coordinated AI agents to help teams detect risk earlier and move investigations forward faster. Here are six ways Exabeam improves outcomes compared to Splunk. 1. Predictable costs and clear value. Splunk cloud workload pricing model is complex and often unpredictable. Costs scale based on ingestion, storage, compute, and add-ons, which can lead to overages and rising spend as environments grow. Exabeam includes analytics, automation, and threat intelligence within New-Scale Fusion. As data volume increases, you gain more detection coverage and automation without layering on additional modules. Outcome: More predictable cost structure with increasing value over time. 2. Less tuning and operational overhead. Splunk requires continuous tuning. Analysts must maintain Splunk Search Processing Language (SPL) queries, build correlations, and reduce false positives through manual adjustments. Behavioral analytics capabilities are bundled into higher-tier offerings, increasing cost and complexity. Migration paths between legacy and newer capabilities can introduce additional operational risk. Exabeam reduces this overhead with: * Prebuilt detection coverage * Behavioral analytics for users, entities, and agents * Contextual correlation and automated workflows Analysts move from detection to investigation in a single interface without custom scripting. Outcome: Faster time to value and less reliance on engineering resources. 3. Strong behavioral visibility across humans, devices, and agents. Most modern attacks involve credential misuse or lateral movement. Rules alone are not enough to detect these patterns. Splunk provides behavior-based detection, but it often requires extensive tuning and operates outside a unified investigation workflow. Exabeam applies: ABA extends behavioral analytics to AI agents and non-human identities. It correlates activity across users, devices, and agents into a single investigation flow so analysts can understand how behaviors interact within an attack sequence. While Splunk can monitor agent activity and assign risk scores, it approaches this from an observability perspective. Exabeam integrates agent behavior directly into the investigation workflow, so all related activity is analyzed together. Outcome: Faster identification of high-risk behavior with unified investigation context. 4. Cloud-Native architecture built for scale. Splunk Cloud is a managed version of an architecture originally designed for on-premises deployments. Scaling often requires planning for storage, compute, and performance constraints. New-Scale Fusion is cloud native. It: * Processes high event volumes at scale * Unifies ingestion, parsing, analytics, and detection * Provides real-time visibility into service health and consumption OpenAPI Standard (OAS) support enables integration with broader security and IT ecosystems. Outcome: Consistent performance and visibility as data and complexity grow. 5. AI agents that drive investigation and detection outcomes. Splunk AI Assistant focuses on generating SPL queries and summaries. Its use is limited and often dependent on specific configurations. Exabeam Nova is a coordinated system of seven AI agents embedded into the detection, investigation, and response workflow: * Advisor Agent: Provides posture insights, MITRE ATT&CK(R) alignment, and prioritized recommendations through Outcomes Navigator * Search Agent: Converts natural language into Exabeam Query Language (EQL) aligned to the Common Information Model (CIM) * Visualization Agent: Build dashboards and charts from search results * Threat Scoring Agent: Applies adaptive learning to prioritize activity with dynamic risk scores * Investigation Agent: Generates summaries and recommends next steps * Analyst Assistant Agent: Surfaces evidence and guides investigators in real time * Rule Creator Agent: Translates natural language and observed attack patterns into correlation rules aligned to CIM and ATT&CK to accelerate detection coverage These agents work together within a unified workflow, reducing manual effort and improving investigation consistency. Outcome: Faster investigations, improved prioritization, and reduced analyst workload. 6. Measurable detection coverage with Outcomes Navigator. Security teams often lack visibility into whether their SIEM is detecting meaningful threats and how gaps translate to business risk. Splunk Security Essentials (SSE) is a content library that helps teams implement security use cases and map detections to frameworks like ATT&CK. While it highlights detection gaps, it provides limited visibility into exposure and only indirect insight into business risk. Outcomes Navigator delivers: * Detection coverage mapped to ATT&CK * Visibility into gaps and exposure * Prioritized recommendations aligned to business outcomes It continuously tracks detection performance and program maturity without requiring custom dashboards. Outcome: Clear visibility into detection coverage and next steps to reduce risk. Conclusion. Log search alone can't meet the demands of modern security operations. Exabeam combines behavioral analytics, dynamic risk scoring, automated timelines, and AI agents to detect hidden risk in human, device, and agent activity. You gain a unified investigation workflow, faster response times, and measurable improvements in your security program without needing to rebuild your entire stack. Download the full comparison guide to see how to reduce cost, improve detection coverage, and accelerate investigations. Heidi Willbanks. Heidi Willbanks | Senior Product Marketing Manager, Content | Exabeam | Heidi Willbanks leads content strategy and go-to-market execution at Exabeam, focusing on product launches, cybersecurity solutions marketing, and technical alliances. She has 20+ years of marketing experience, including over a decade in information security and data privacy, and holds a Level IV certification from Pragmatic Institute. Heidi specializes in creating clear, technically accurate content for security practitioners and decision-makers. Learn about the Exabeam platform and expand your knowledge of information security with its collection of white papers, podcasts, webinars, and more.

AI is helping security teams, but agents are emerging as a top cybersecurity concern, Exabeam survey finds. * Jul 08, 2026 * 2 minutes to read Survey of cybersecurity professionals attending Infosecurity Europe finds AI is improving security team productivity while changing the insider threat landscape. MAIDENHEAD, England - July 8, 2026 - Exabeam, the leader in Behavior Intelligence for the agentic enterprise, today shared findings from a survey of cybersecurity professionals attending Infosecurity Europe 2026, offering a snapshot of how practitioners view AI's growing impact on security operations. Among the 134 cybersecurity professionals surveyed when visiting the Exabeam booth, 88% said AI has improved their security team's productivity. At the same time, one in four identified AI agents and autonomous systems as the single greatest cybersecurity threat facing their organisation, reflecting the dual role AI now plays in helping defenders while introducing new insider risks. "As organisations deploy AI across the business, they're introducing a new class of trusted identities," said Findlay Whitelaw, Field CISO at Exabeam. "AI agents can access systems, process sensitive information and make decisions autonomously using legitimate credentials. Security teams aren't just protecting people anymore. They're securing trusted identities, whether they're human or AI." While external threat actors were the most frequently cited cybersecurity threat (40%), AI agents and autonomous systems ranked similarly to compromised insiders, ahead of malicious insiders (9%). Unlike traditional attackers, AI agents increasingly operate with authorised access and trusted workflows, making risky behaviour more difficult to distinguish from normal business activity. The survey also found that insider threats remain a persistent concern. Nearly half (46%) of respondents said insider threats have increased over the past 12 months, while 43% said they have remained the same. Only 4% believe insider threats have decreased. At the same time, nearly three-quarters (72%) believe executive leadership underestimates insider threat risk, suggesting many organisations have yet to fully appreciate how insider risk is evolving as AI becomes part of the workforce. "Insider risk hasn't disappeared, it has evolved," Whitelaw said. "The challenge is no longer limited to monitoring employees or compromised accounts. Organisations also need to understand how AI agents behave, and identify abnormalities before they become business risk. Understanding behaviour across both human and AI identities is essential to protecting the modern enterprise." Survey methodology. Exabeam surveyed 134 cybersecurity professionals attending the Exabeam Booth at Infosecurity Europe in London during the event in June 2026. Approximately 78% of respondents were based in the UK and Ireland. The findings represent a snapshot of the views of cyber security professionals who engaged with Exabeam at Infosecurity Europe 2026, and are intended to reflect participant sentiment. About Exabeam Exabeam is the leader in Behavior Intelligence for the agentic enterprise. As organizations deploy digital workers and confront machine-speed adversaries, Exabeam applies agent-powered analytics to understand and govern the behavior of both human and non-human insiders. With integrated Exabeam Nova cybersecurity agents, Exabeam delivers flexible, industry-proven solutions for insider threat coverage of humans and agents and faster, more accurate threat detection, investigation, and response (TDIR). As the pioneer of user and entity behavior analytics (UEBA) and the innovator behind Agent Behavior Analytics (ABA), Exabeam is trusted by more than 3,000 enterprises worldwide to reduce risk, secure the digital workforce, and accelerate security operations. Learn more at www.exabeam.com. Exabeam: Stop Insider Threats. Human or AI. Recent press releases. Learn about the Exabeam platform and expand your knowledge of information security with its collection of white papers, podcasts, webinars, and more. * Blog Why Rules Can't Detect Insider Threat Sequences Read Now * White Paper Agent Behavior Analytics: Securing the Autonomous Enterprise Read Now * Data Sheet Exabeam Academy Course Catalog 2026 Read Now * Guide Exabeam vs. CrowdStrike: Five Ways to Compare and Evaluate Read Now * Show More