For enterprises, this tipping point reveals a critical infrastructure vulnerability. Legacy defense mechanisms—specifically traditional, static CAPTCHAs—have become dangerously obsolete. While a modern, generative AI-powered bot can easily solve a one-time visual challenge or simulate a single endpoint action to slip through the front door, replicating an entire human user journey across a session remains a massive engineering hurdle.

Addressing this gap between static checkpoints and continuous exposure, connectivity cloud giant Cloudflare announced the general availability of Precursor, a next-generation, continuous behavioral validation engine for bot management.

By deploying continuous, client-side behavioral telemetry directly at Cloudflare’s edge network, Precursor eliminates the “black box” space that exists between entry gates and checkout windows. For the Cybersecurity, Cloud Infrastructure, and Digital Fraud Prevention industry, this launch establishes a new operational paradigm shifting bot mitigation away from disruptive, point-in-time gatekeeping and entering an era of invisible, session-long verification.

Also Read: KKR Launches Allyntra to Meet the Rising Demand for MedTech Precision Manufacturing

Technical Performance: Session-Long Telemetry Without Code Disruption

The core architectural breakthrough driving Precursor is its ability to track browsing integrity without degrading the end-user experience or introducing application development friction. Instead of forcing web engineering teams to rewrite internal application logic or hardcode event listeners into forms, the platform operates as an automated network overlay.

The system evaluates interaction trails in real time across several sophisticated parameters:

Zero-Code, One-Click Activation: Enabled instantly via the Cloudflare dashboard, the network automatically injects a compact, dynamic JavaScript bundle into outgoing HTML responses. The obfuscated script functions natively across web and single-page applications (SPAs) without interfering with existing page logic.

Continuous Browser Telemetry: Rather than relying on a static checkpoint, Precursor captures ongoing, real-time client interaction data. It monitors cursor trajectories, scrolling rhythms, typing cadences, clipboard activity, and page visibility durations to build a compounding behavioral profile.

Privacy-Led Aggregation: Built with a strict privacy-first architecture, the engine does not track or log specific user inputs. Keyboard activity, for instance, is recorded strictly as mathematical timing intervals and typing rhythms—ensuring actual characters and personally identifiable information (PII) are never captured.

Edge-Driven Behavioral Validation: Cloudflare’s edge nodes process the streaming telemetry instantly, cross-referencing behavioral patterns to catch anomalies (e.g., typing events occurring without active text-field focus, or mouse movements registering while a page hidden state is active). This continuously updates a session’s Bot Score in the background.

Transforming the Cybersecurity and Digital Fraud Industry

The introduction of an automated, session-wide behavioral validation framework creates permanent structural shifts across the online security landscape.

The Obsolescence of the Friction-Heavy CAPTCHA Era
For over a decade, the digital fraud prevention market relied heavily on visual challenges to prove human intent. However, as advanced multi-modal AI models grew capable of solving these puzzles faster and more accurately than actual humans, vendors responded by making the challenges increasingly complex. This resulted in extreme user friction, driving down shopping cart conversions and frustrating legitimate traffic.

Precursor highlights the strategic failure of point-in-time challenges. By analyzing the organic complexity of a full user journey invisibly, the technology allows cybersecurity teams to dramatically reduce human interruptions while increasing true detection accuracy, spelling the end for intrusive, standalone gateway challenges.

Eliminating Evasion via Session Resets
Historically, bot developers bypassed basic endpoint protections by executing their malicious automated tasks in short bursts and frequently clearing cookies or refreshing pages to reset their risk score.

Precursor systematically shuts down this defensive blindspot. Because the validation engine evaluates behavior seamlessly across the entire application session, an automated script cannot clean its signature simply by reloading the site. This radically alters the economics of cyberattacks, forcing malicious actors to expend immense engineering resources simulating complex human browsing traits over prolonged timelines just to remain unblocked.

Broad Operational Impact on Enterprise Businesses

For e-commerce networks, financial platforms, and SaaS enterprises looking to shield their digital assets from hyper-automated automated abuse without expanding their technical debt, adopting a continuous edge defense yields distinct commercial advantages.

Insulating Corporate Margins from Infrastructure and Inventory Exploitation
When an enterprise leaves its session-level traffic unmonitored, it risks severe operational distortions. Malicious AI agents can scrape proprietary pricing data continuously, while scalper bots can flood checkout lines to lock up high-demand inventory, denying access to real customers and falsifying demand metrics.

Furthermore, processing vast streams of automated non-human requests introduces a massive unvouched tax on cloud data center overhead. Transitioning to an invisible, session-wide behavioral analyzer ensures that bad actors are silently neutralized the moment their programmatic signature deviates from human patterns—protecting inventory availability and shielding corporate balance sheets from ballooning infrastructure bills.

Reclaiming Engineering Capacity for Strategic Security Architecture
Corporate application security (AppSec) teams routinely waste immense internal capacity playing a continuous game of whack-a-mole manually writing custom firewall rules, tuning regex patterns, and reviewing traffic spikes to stop highly evasive bots.

Offloading routine web-traffic validation onto a secure, edge-native behavioral engine allows internal IT organizations to recover valuable bandwidth. Cyber professionals can step away from manual entry analysis and focus their full attention on high-value, strategic priorities such as threat modeling core business logic, hardening API integrations, and refining localized data access frameworks turning defensive risk management into a confident engine of enterprise scaling and competitive advantage.

The post Cloudflare Launches Precursor to Counter Evasive AI Bots at the Edge appeared first on ITDigest.

Also Read: FusionAuth Launches Intelligent MFA to Maximize Infrastructure Control 

This platform expansion also builds on Tidal Cyber’s strategy of separating MITRE ATT&CK® cyber threat intelligence (CTI) from its proprietary threat streams, providing security teams with procedural precision and absolute transparency across active defense environments. Highlighting the necessity of shifting to an execution-based risk model, Rick Gordon, Co-founder and CEO of Tidal Cyber, stated: “Most security platforms still prioritize based on severity scores, inventory counts, or generalized risk models. But adversaries don’t attack environments based on CVSS scores or asset databases. They exploit the path of least resistance. Threat-Led Defense changes the model entirely by aligning defenses to the assets, vulnerabilities, and procedures attackers actually use to execute attacks.” Concluding on the operational philosophy driving the platform upgrades, Frank Duff, Co-founder and Chief Innovation Officer of Tidal Cyber, noted: “Threat-Led Defense starts with a simple principle: you cannot reduce residual risk unless you understand how adversaries actually execute attacks and how that execution impacts your defensive environment.”

Read More: Tidal Cyber Advances Threat-Led Defense to Transform Asset Visibility and Vulnerability Prioritization

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Today’s cybersecurity practices regularly face significant friction in the workflow. With increased speed and frequency of automatic malicious exploits, SOC teams experience an overwhelming amount of low-quality logs coming from their telemetry sources. Security analysts find it challenging to identify essential vulnerabilities of the system because of disconnected security software consoles and too many false alerts. By unifying deep network visibility with an autonomous security operations platform, this enterprise-grade service addresses these challenges, mitigating tool sprawl and accelerating protective response cycles.

“Cyber defense is a speed game, and the network is where threats often show up first,” said Lumen’s Chief Technology and Product Officer, Jim Fowler. “With Palo Alto Networks, we’re again raising the bar for security by expanding access to our high-value network threat intelligence and putting it to work through modern, automated operations. As we bring Lumen Defender AMDR to more partners and platforms, more customers can quickly thwart bad actors.”

Also Read: Keeper Security Introduces Agentic AI Governance for Endpoint Privilege Manager

Neutralizing Pre-Compromise Exploits via Network Intelligence

The core architectural breakthrough of the platform lies in the deep integration of the Lumen Defender℠ Threat Feed, backed by Lumen’s elite threat research division, Black Lotus Labs®. Unlike legacy security monitoring solutions that rely strictly on endpoint telemetry or localized device logs, this specialized threat intelligence stream monitors real-time traffic behaviors directly across the global Lumen network backbone.

This network-level visibility delivers distinct advantages across several threat vectors:

Early Adversary Infrastructure Tracking: Maps outbound malicious staging zones and command-and-control centers before data payloads impact internal corporate domains.

Proactive Reconnaissance Interception: Identifies early-stage unauthorized network scanning and system probing prior to active infiltration attempts.

Autonomous Incident Triage: Reduces overall operational fatigue by transforming raw signal noise into contextualized, high-confidence security alerts.

Agentic Workspace Automation: Minimizes administrative maintenance by leveraging automated playbooks to streamline daily evidence-based investigations.

“Securing the modern enterprise means eliminating complexity and accelerating time-to-resolution,” said Simone Gammeri, Chief Partnership Officer at Palo Alto Networks. “Combining Lumen’s network-level threat intelligence with Cortex XSIAM empowers organizations to proactively defend against sophisticated threats at machine-speed and scale their security operations.”

Flexible SOC Deployment and Ecosystem Connectivity

The platform architecture supports both fully co-managed and completely managed SOC engagement models, enabling enterprise networks to rapidly upgrade their cyber posture without replacing existing security personnel. The unified interface aggregates core security workflows—including Extended Detection and Response (XDR), Security Orchestration, Automation, and Response (SOAR), Attack Surface Management (ASM), and Security Information and Event Management (SIEM) into a centralized dashboard, eliminating console switching.

This integration forms part of Lumen‘s broader ecosystem strategy, which links its global fiber footprint and cloud-native control plane with leading enterprise software applications to deliver scalable data transit, AI acceleration, and infrastructure protection.

The Lumen Defender℠ AMDR platform for Palo Alto Networks Cortex XSIAM is live and available immediately for worldwide enterprise onboarding. Chief information security officers, cloud architects, and risk management executives can explore technical deployment documentation, evaluate platform architecture frameworks, and schedule a custom environment validation by visiting Lumen’s official digital technology interface.

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Studies show that most people don’t know if what they see on the Internet is real anymore. A 2026 RBC poll found that 83% of people now assume any online message is a scam or fraud unless proven otherwise. The FBI reported $20.9B in cybercrime losses in 2025 (a 26% jump in one year) and, for the first time, added AI crime as a category, with over 22,000 AI-related complaints. New AI models like Anthropic’s Claude Mythos have made these problems even more dangerous.

“The Internet is not safe, and is getting less safe every day because of AI,” said Shuman Ghosemajumder, Reken CEO, who previously founded Google’s Trust & Safety product group and was Head of AI at F5. “Traditional cybersecurity has failed to solve these problems, and increasing scams, fraud, and cybercriminal use of AI have accelerated this erosion of trust. We need a new architecture to prevent our critical online channels from becoming overwhelmed.”

Breakthrough architecture: the Reken Private Core and the Reken Network

To solve this, Reken was founded and raised $10M in 2024, and spent two years in stealth R&D to design and build a new technology platform to address these persistent issues. The result is the Reken Private Core, a breakthrough on-device AI security system introduced today.

Also Read: Claroty and Frenos Partner to Reduce Downtime Risk for Industrial Environments

The Reken Private Core protects communications sent to and from each device, account, and user. Products built on the Reken Private Core use high-performance, proprietary AI models to identify incoming threats, as well as next-generation telemetry sensors to detect AI bots and automation on compromised channels, while keeping all communication data private and on-device. These technologies are able to protect against advanced attacks that no other system can detect, while dealing with traditional attacks more effectively. The Reken Private Core is designed to work on commodity hardware without GPUs and with no additional AI token costs.

Products built on the Reken Private Core platform self-assemble into the Reken Network, an advanced trust layer for the Internet. Organizations within the Reken Network can communicate with greater security and confidence, and incoming communications from outside the network are automatically analyzed for malicious behavior and deceptive content.

“There is nothing like this available to CISOs,” said Jim Routh, the former Chief Information Security Officer of American Express, DTCC, Aetna/CVS Health and MassMutual. “This will enable companies and their supply chains to significantly improve the level of safety they can expect in their communications.”

The first product: Reken Northstar, just-in-time AI to eliminate the need for phishing training

The first product built on the Reken Private Core platform is Northstar, a pro-worker AI application that helps employees by removing the burden of constantly looking for security threats like social engineering, deepfakes, business email compromise, and other AI-enabled fraud.

“Companies spend millions of human hours per day and billions of dollars on security training that simply doesn’t work,” said Ghosemajumder. “We shouldn’t be forcing employees to become forensic digital investigators. We need just-in-time AI that detects the threats the human eye cannot see. That’s what Northstar does.”

Source: PRNewswire

The post Reken Launches From Stealth, to Build an Internet Safe for Humans appeared first on ITDigest.

Also Read: ThreatModeler Debuts Nexus Platform for Agentic Security Design 

Crucially, the feature runs natively within any environment an organization selects whether hosted via dedicated FusionAuth Cloud, on-premises, or air-gapped infrastructure allowing enterprise buyers to scale security without forfeiting architectural control or data visibility. The product rollout addresses a massive industry shift highlighted in the firm’s 2026 State of AI and Identity Report, which revealed that organizations relying on shared multi-tenant identity infrastructure suffered security breaches at more than double the rate of those utilizing self-hosted platforms. Highlighting how this transparent architecture helps security and compliance teams successfully manage increasing regulatory scrutiny, Brian Bell, CEO of FusionAuth, stated: “Security teams do not just need stronger authentication. They need authentication they can explain. When an auditor, board member, customer, or regulator asks why a user was challenged, ‘the model said so’ is not a satisfying answer. Intelligent MFA gives teams a clear policy, clear signals, and a clear record of what happened.”

Read More: FusionAuth Launches Intelligent MFA in Latest Release as Demand Surges for Identity Infrastructure Customers can Control

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Security teams face increasing pressure to prove their business value and demonstrate that they are achieving true risk reduction with tangible results. At the same time, AI-enabled threats have hyper-accelerated the threat lifecycle, leaving teams outmatched in their ability to react at the same pace. Organizations must meet these challenges head-on with AI-native tools purpose-built for complex CPS environments that deliver trustworthy insights with swift, deterministic, scalable actions.

Key benefits of the Claroty and Frenos joint solution include:

• Threat-Informed Vulnerability Prioritization: Frenos ingests Claroty’s deep asset intelligence to build environment-specific digital twins and the Frenos AI adversary agent, SAIRA, analyzes which vulnerabilities are actually exploitable and then provides specific remediation options.
• Continuous Validation of Segmentation and Firewall Policy Effectiveness: Claroty provides the necessary visibility into network communications and device connections, which Frenos uses to model and simulate attacks, allowing security teams to validate that segmentation designs successfully protect high-value OT targets.
• Threat Actor Emulation and Exposure Assessment: Claroty provides the detection layer and environmental context, while Frenos replicates the attack sequence to determine if a threat can lead to production disruption, transforming abstract warnings into concrete defensive assessments.

Also Read: Barracuda Acquires Evo Security to Deliver Complete Identity Resilience

“Asset intelligence is the bedrock of every organization’s CPS risk management program,” said Grant Geyer, Chief Strategy Officer at Claroty. “By gaining full visibility into the industrial environment with the ability to stress test their exposures, organizations that leverage Claroty and Frenos are in the best position to protect against operational downtime and to reduce overall risk.”

“Knowing your assets is the starting point; knowing which exposures an adversary can actually exploit is what drives action,” said Brian Proctor, CEO of Frenos. “By building environment-specific digital twins from Claroty’s deep asset intelligence, our AI adversary agent shows teams exactly which vulnerabilities are reachable, what an attacker could do with them, and where to remediate first. Together, Claroty and Frenos give industrial organizations the confidence to move from reactive defense to proactive risk reduction”

The AI-powered Claroty Platform combines deep asset visibility, threat detection, exposure management, and network protection to reduce CPS risk while offering the world’s fastest time-to-value at a lower total cost of ownership. Having just announced Claroty Claire, a first-of-its-kind, CPS-native AI security agent, the company is leading the market in organizations’ ability to ensure safety, uptime, and availability in an AI-driven world.

The Frenos platform empowers security professionals to scale assessments across OT environments at a fraction of the time. By combining a digital twin with an AI reasoning agent, Frenos identifies the most probable adversary tactics, techniques, and procedures (TTPs), so organizations can prioritize their mitigation activities to stay ahead of today’s threats. This intelligence-driven approach enables security teams to shift from reactive to proactive defense, delivering comprehensive assessments without any operational impact.

Source: PRNewswire

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For years, organizations have recognized the value of segmentation for securing their most important assets but have struggled to put it into practice. Traditional approaches demand complex network redesigns and risky infrastructure changes in environments where downtime is not an option. As a consequence, many industrial organizations deferred segmentation, settling instead on detection-and-response practices to protect their environments.

But that reactive model is no longer sufficient. As the attack surface expands with AI-enabled threats accelerating attacks and operations becoming increasingly connected organizations need to contain threats before they can spread laterally. Segmentation has become essential to protecting operational continuity.

Also Read: Endace and Artiza Networks Partner to Deliver Cybersecurity and Defense Solutions to the Japanese Market 

Cyolo understands critical infrastructure environments, where uptime is non-negotiable, legacy systems are common, implementation resources are limited, and security controls cannot come at the cost of operational disruption. Designed specifically for these realities, Cyolo CPS Segmentation delivers practical, risk-based microsegmentation that fits the way industrial organizations operate.

Built on Cyolo’s proven true Zero Trust architecture, which keeps all sensitive data under customer governance, CPS Segmentation supports the full microsegmentation lifecycle from discovering assets and communication flows to creating, validating, and enforcing policies. With capabilities that include shadow-access discovery, visual flow mapping, blast-radius analysis, intelligent grouping, policy recommendations, and pre-enforcement simulation, organizations can identify connectivity risks, validate changes with confidence, and limit lateral movement without disruptive redesigns, lengthy implementation projects, or added complexity.

“We’ve pursued a single goal since Cyolo was founded to help the organizations that keep our world running control every connection across their critical infrastructure,” said Almog Apirion, CEO and co-founder at Cyolo. “We started with human-to-machine access, and now we’re bringing the same OT-native security principles to machine-to-machine communication control. As AI helps attackers move faster and farther, the ability to stop lateral movement and reduce blast radius has never been more crucial. We built Cyolo CPS Segmentation to solve that challenge.”

Cyolo CPS Segmentation is the latest addition to the broader Cyolo platform, which brings together remote privileged access, identity security, malware detection, secure web access, endpoint security, and a broad ecosystem of security integrations. Together, these capabilities provide critical infrastructure and industrial organizations with a unified foundation for protecting the people, processes, assets, data, and AI-driven systems that power critical operations.

Source: PRNewswire

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While AI code-generation tools have dramatically accelerated development cycles, they have also hyper-automated the adversarial perimeter. Malicious actors are now using frontier AI models to discover, generate, and execute software exploits at machine speed, completely breaking traditional manual patch management frameworks.

For large-scale corporate entities, managing this massive influx of software vulnerabilities has become an operational crisis. Forcing development teams to execute sweeping upstream software upgrades simply to patch a single nested vulnerability often triggers complex system errors, requiring weeks of slow, expensive testing that paralyzes internal roadmaps.

Addressing this high-stakes deadlock, technology giants IBM and Red Hat announced the commercial launch of Lightwell.

Building on a massive $5 billion corporate investment, the platform leverages advanced, agentic AI models backed by a global force of 20,000 engineers to identify, validate, and patch open-source vulnerabilities. By backporting verified security patches directly to the specific, pinned software versions companies already run in production, Lightwell establishes a major shift in the Cybersecurity, Enterprise Software Governance, and Secure Supply Chain Architecture industry.

The News: Automated, Target-Version Patching at Machine Speed

The primary technical advancement delivered by the launch of Lightwell is its ability to separate open-source vulnerability remediation from disruptive major upgrade cycles. Instead of forcing an enterprise to rebuild an entire software stack to resolve a flaw, Lightwell injects production-ready, target-version fixes straight into active developer pipelines via two primary commercial offerings:

Lightwell Network: Generally available immediately, this self-service model grants enterprise teams access to a launch catalog of more than 6,500 remediated, digitally signed, and certified application-layer dependencies across dominant ecosystems like Java and Python. The service automatically delivers clean code and complete Software Bills of Materials (SBOMs) straight into existing workflows.

Lightwell Clearinghouse Premier: Entering a limited-availability phase initially focused on the heavily regulated financial services sector, this solution acts as a secure, trusted intermediary. Member organizations can coordinate under a patch embargo framework, safely sharing threat intelligence and requesting custom fixes for company-specific dependency versions before flaws are publicly exposed.

Also Read: Accenture Edge and Google Cloud Launch Agentic AI Solutions for the Mid-Market

Transforming the Cybersecurity and Software Governance Industry

The introduction of an automated, backported patch infrastructure creates massive ripple effects across the technical governance and cybersecurity landscape.

The Death of Vulnerability Identification Without Remediation
For years, the application security market was dominated by detection utilities—such as static and dynamic application security testing (SAST/DAST) and software composition analysis (SCA) platforms. These tools made their margins by scanning code and outputting massive lists of vulnerabilities, effectively passing the administrative burden of writing patches onto overworked corporate teams.

Lightwell completely flips this business model. By moving the bar from passive detection to automated, guaranteed remediation, IBM and Red Hat are forcing the entire security tech sector to evolve. Niche scanning tools will quickly lose market viability unless they tightly link their diagnostic dashboards to active, certified code delivery engines.

Overhauling the Technical Debt Paradigm in Systems Integration
Historically, global systems integrators and premium IT consultancies generated highly predictable revenue streams by managing complex application modernization and legacy code refactoring projects.

By applying automated, agentic AI to handle the tedious mechanics of dependency patch backporting, Lightwell heavily commoditizes a significant friction point in software maintenance. This operational shift frees up massive capacity for technology consulting partners like Deloitte, Accenture, and Infosys. Systems engineers can move away from routine patch testing and focus entirely on high-level system architecture, custom monetization strategy, and advanced data modeling.

Broad Operational Impact on Enterprise Businesses

For enterprise corporations looking to maintain rapid software innovation cycles without introducing existential operational vulnerabilities, deploying an automated remediation fabric provides clear commercial advantages.

Insulating Corporate Infrastructures from Automated Software Supply Chain Attacks
Because modern applications rely on deeply nested trees of open-source libraries, a security vulnerability in a minor, forgotten sub-dependency can easily expose a massive multinational enterprise to remote code execution or data theft. Relying on slow, manual internal review boards to patch these vectors is no longer effective when adversaries are using AI to exploit zero-day flaws within hours of discovery.

Securing continuous, real-time access to a validated registry of hardened open-source binaries shields corporate assets from devastating brand damage, expensive regulatory penalties, and unexpected operational downtime.

Recovering Administrative Engineering Hours for Core Innovation
When an enterprise development group is forced to constantly halt its core product roadmap to execute forced upstream framework upgrades, its time-to-market dramatically slows down.

Offloading the burden of manual bug triage and regression testing onto a secure, automated global clearinghouse recovers vital internal capacity. Software developers are liberated from routine administrative bottlenecks and can redirect their full attention toward building high-margin digital features, optimizing customer experiences, and accelerating strategic business velocity.

The post IBM and Red Hat Launch Lightwell to Neutralize Open-Source AI Threat Vector appeared first on ITDigest.

“Artiza is exactly the partner we have been looking for to satisfy demand in Japan, with the right balance of expertise, and market reach,” said Stuart Wilson, CEO of Endace.

Through this partnership, Artiza will offer Endace’s packet capture, network recording, and packet forensics solutions to customers in Japan, including telecommunications operators, enterprises, government agencies, defense organizations, and critical infrastructure providers.

Endace’s EndaceProbe Analytics Platform provides highly scalable, always-on packet capture and recording capabilities across a wide range of network environments, including enterprise networks, data centers, telecommunications networks, on-premises infrastructures, hybrid cloud environments, and public cloud deployments. The platform enables Security Operations Center (SOC) and Network Operations Center (NOC) teams to investigate cybersecurity incidents, network performance issues, and operational anomalies by providing access to complete packet-level evidence.

Also Read: Barracuda Acquires Evo Security to Deliver Complete Identity Resilience

Endace solutions integrate with a broad range of cybersecurity and network monitoring platforms, providing direct access to definitive packet evidence required for incident investigation, threat hunting, and root-cause analysis.

By making complete packet-level evidence available to security and operations teams, Endace helps organizations improve the effectiveness of cybersecurity investigations and network performance analysis.

In addition, Endace solutions have achieved important security certifications and approvals, including NIST FIPS 140-3 validation, Common Criteria / NIAP certification, and inclusion on the U.S. Department of Defense Information Network Approved Products List (DoDIN APL). These achievements demonstrate compliance with some of the world’s most demanding cybersecurity requirements for government, defense, and critical infrastructure environments.

By combining Endace‘s advanced packet visibility and packet forensics technologies with Artiza‘s strong presence in the Japanese telecommunications and technology markets, the two companies will work together to support organizations seeking enhanced cybersecurity, operational resilience, and network assurance capabilities.

Source: BusinessWire

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The software update addresses a rapidly evolving threat vector within enterprise network architecture. As coding assistants and autonomous AI applications proliferate across workforce workstations, they routinely execute tasks, make system calls, and seek administrative clearance outside the visibility of legacy privilege management software. Keeper Endpoint Privilege Manager mitigates this visibility gap by intercepting and governing agent activity in real time, regardless of whether the system interacts through a direct API, Model Context Protocol (MCP), or local automation scripts.

“AI agents are not assistants; they are principals,” said Darren Guccione, CEO and Co-founder of Keeper Security. “Every agent running on an endpoint has an identity, requests access and takes actions on behalf of your organization. If you are not governing them with the same rigor you apply to your human workforce, you have blind spots that adversaries will find before you do. Keeper closes that gap today.”

Also Read: SEALSQ Corp Advances Post-Quantum Cybersecurity Infrastructure 

Enforcing Local Control via OS-Level Process Observation

Instead of routing security evaluations through external network proxies, Keeper handles policy management from the existing endpoint software agent tasked with regulating human privilege requests. Operating natively at the operating system level, Keeper monitors the exact machine environment where the artificial intelligence executes to manage five specific local vectors:

• Child Process Spawning: Prevents unauthorized background executables or cascading sub-routines from initiating without administrative consent.

• Direct Filesystem Adjustments: Regulates the writing, modification, or deletion of sensitive information blocks across restricted system volumes.

• Local Shell Invocations: Blocks autonomous systems from opening terminal prompts or executing unverified, low-level operational commands.

• Privilege Elevation Paths: Restricts AI applications from modifying local operating system permissions or obtaining persistent root access.

• Sensitive File Ingestion: Safeguards corporate intellectual property by controlling which database paths or directories an agent can read.

Because every action undergoes evaluation against a unified policy engine, the platform produces a single, cohesive audit trail that matches the compliance rigor applied to human operators.

Combining Machine Learning Diagnostics with Human Review

To simplify administrative overhead, the platform calculates a real-time risk index ranging from 0 to 100 for every application active on a managed workstation. Any system crossing a preconfigured compliance threshold automatically triggers agentic AI protective policies at runtime, eliminating the need for manual file tagging or signature updates.

“This update stops the emerging threat of autonomous AI in its tracks, allowing enterprises to adopt cutting-edge AI agents without opening the floodgates to catastrophic risk.”

The agentic governance matrix introduces three dedicated policy models built on existing Endpoint Privilege Manager configurations, alongside a human-in-the-loop review interface:

• Agentic AI Policy: Manages user permissions to determine which specific personnel are authorized to launch automated agents on local hardware.

• Agentic Access Policy: Controls what data, executables, and background terminal commands a running agent can access on a user’s behalf.

• Agentic Privilege Elevation Policy: Regulates the mechanism by which an active agent can request temporary or permanent administrative clearance from the OS.

The expanded toolkit provides the necessary controls to help enterprises satisfy the National Institute of Standards and Technology (NIST) AI Risk Management Framework directly at the workstation layer. The release also debuts a redesigned management console complete with automated agent version control, unique workload monitoring screens, and dedicated visibility dashboards.

The agentic security features are globally available today, offered as a standalone endpoint solution or fully integrated into the cloud-native KeeperPAM® platform. Corporate security directors, risk compliance managers, and enterprise cloud architects can examine deployment blueprints, review identity verification frameworks, and analyze cryptographic structures by visiting Keeper’s official digital platform.

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