Also Read: BrowserStack Introduces Test Companion to Automate IDE-Based Software Testing

Contextualizing the imperative to meet developers inside modern AI-native development environments, David Kårfors, VP Product Management & Product Platform at Sinch, stated: “AI-assisted development tools are becoming a larger part of how software is built. With Agent Tools, we are bringing Sinch into those workflows so developers can build and test applications, access accurate platform information and work with AI-assisted development tools without leaving the environments they already use.” Highlighting the friction-reducing impact of local testing, Kårfors added: “Getting started with a new platform often means creating accounts, configuring credentials and navigating documentation before writing any code. With Simulator Mode, developers can begin testing integrations directly from their development environment, which lowers the barrier to exploring and evaluating Sinch services before even needing to create an account.”

Read More: Sinch launches Agent Tools for developers and AI coding assistants

The post Sinch Unveils Agent Tools to Integrate Communications APIs into AI Coding Workflows appeared first on ITDigest.

Also Read: Resecurity Integrates Native Threat Intelligence with IBM QRadar SIEM

As a combination of both capabilities, the company will have the ability to track all steps, which happened within the environment, and also to monitor agents’ activities in live time across different types of environments: cloud, code repository, and on-premises AI setups. Emphasizing the operational necessity of continuous behavioral verification over static permissioning, Nimrod Vax, Co-Founder and Head of Product at BigID, stated: “Every agent you deploy inherits a level of trust. The real question is whether you can verify that trust is earned continuously, not just granted once at setup.” By grounding governance directly in data sensitivity and real-time intent verification, BigID equips security and compliance teams with the essential controls needed to safely scale autonomous agentic automation while mitigating critical enterprise security risks.

Read More: BigID Defines the Missing Governance Layer for Autonomous AI Agents

The post BigID Introduces Governance Layer to Secure Autonomous AI Agents appeared first on ITDigest.

Conducted across the live infrastructure of a major global institution, the three-day engagement pitched Armadin’s autonomous offensive AI swarm directly against TENEX.ai’s agentic, human-led Security Operations Center (SOC). The exercise wasn’t a simulated, sandboxed proof of concept—it was a real-world, machine-speed clash between autonomous red team AI and agentic blue team defense.

Breakdown of the Record-Breaking Engagement

Operating under zero-knowledge conditions—with no pre-shared credentials, whitelisting, or source code access—Armadin unleashed 26,000 autonomous AI agents across the institution’s external perimeter, internal network, and web applications.

Armadin Autonomous AI Swarm (Offense)

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17M Offensive Actions
26,000 Active Agents
38 Validated Attack Paths

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▼

TENEX.ai Agentic SOC Platform (Defense)

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▼

101,169 Alerts Triaged
231B Raw Events Processed
2,400 Analyst Hours Saved

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Continuous Real-Time Defensive Coverage

Over the course of the campaign, the offensive swarm generated 17 million actions, targeted more than 25,000 services, and mapped 38 validated attack paths yielding 238 security findings.

On the defensive side, TENEX.ai’s platform ingested and triaged 101,169 alerts and reconstructed the full attack chain across 231 billion raw events in real time. Reconstructing an attack of this magnitude manually would traditionally require a five-person analyst team approximately 2,400 hours—or four months—of forensic effort.

Also Read: Forcepoint Launches AI Data Security Platform to Secure the Agentic Enterprise Data

Transformative Impact on the Cybersecurity Industry

This experiment marks an important turning point for the cybersecurity and MDR industry. For years, enterprises have conducted penetration tests and used signature-based vulnerability scanning solutions that were run periodically to test their security posture.

However, given the current use of LLM-based and autonomous tools by threat actors, traditional point-in-time compliance approach will not be enough anymore.

Key Industry Shifts:

1. Continuous Adversarial Validation as the Baseline: The concept of “annual red-teaming” is rapidly becoming obsolete. Cybersecurity vendors must transition toward continuous, live adversarial testing—often termed “Hyperattacks”—to uncover complex, chained vulnerabilities before hostile threat actors exploit them.
2. AI Offense Training AI Defense: The future of Security Operations Centers lies in closed-loop AI cycles where machine-speed offensive probing continuously trains and refines machine-speed defensive detection algorithms.
3. The “Human-in-the-Loop” Evolution: As TENEX.ai demonstrated, AI agents handle the heavy lifting of parsing billions of raw telemetry events, while human operators remain accountable for high-level decision-making, strategic containment, and escalation.

What This Means for Businesses Operating in Today’s Threat Landscape

For business leaders, CISOs, and IT executives, the Armadin–TENEX.ai benchmark provides clear takeaway lessons for risk management and operational readiness:

1. Closing the “Detection vs. Coverage” Gap

Having security tooling (WAFs, EDRs, SIEMs) does not guarantee operational security coverage. Modern attackers exploit ordinary engineering decisions and complex dependency graphs rather than simple unpatched software bugs. Businesses must adopt tools capable of evaluating how configurations interact across hybrid environments in real time.

2. Overcoming SOC Analyst Burnout

Alert fatigue has been a problem for enterprise security teams from time immemorial. With threat actor behavior accounting for only 1 event out of 13,000 telemetry events, it is unfeasible to think that humans can follow up attacks manually in current day and age. By using agentic AI triage, security personnel workload is greatly reduced.

3. Preparing for Machine-Speed Adversaries

Threat actors are already leveraging generative models to create unique, highly adaptive attack chains that bypass static signature models. Enterprises that fail to modernize their defense workflows to operate at machine speed risk finding their security gaps in production—when a breach has already occurred.

The Path Forward

The successful execution of the Armadin and TENEX.ai live engagement proves that effective defense in the AI era requires autonomous offense continuously challenging autonomous defense. As continuous adversarial validation becomes the standard, organizations that integrate machine-speed testing and agentic SOC response today will build the resilience necessary to withstand the next generation of cyber threats.

The post Armadin and TENEX.ai Stage Largest Live AI Cyberattack Test appeared first on ITDigest.

Although CTEM has enjoyed a lot of acceptance in the business world as a strategy for managing cyber risks, many security teams in the enterprise space have had problems executing CTEM due to issues such as workflow disconnections, outdated tools, and manual friction. AVA Agentic OS addresses this gap by orchestrating specialized teams of artificial intelligence agents to autonomously discover, validate, and eliminate threat debt.

“Organizations don’t have a CTEM strategy problem they have a CTEM execution problem,” said Carl Wright, Chief Commercial Officer at AttackIQ. “AVA OS is the operational layer that makes Continuous Threat Exposure Management executable. It coordinates specialized AI agents that continuously perform the work required to discover, validate, and reduce threat debt. The next generation of cybersecurity operations will be built on specialized, mission focused agentic systems.”

Also Read: Harness Integrates Agentic AI Security with Google Cloud Apigee

Unifying Security Operations into Autonomous Missions

Rather than relying on isolated task automation, AVA Agentic OS deploys mission-focused AI agent teams across six core cybersecurity domains:

Cyber Threat Intelligence (CTI): Continuously ingests and analyzes global threat actor techniques to prioritize emerging exposures.

Security Validation: Emulates real-world adversary behavior across production networks to verify defensive control efficacy.

Detection Engineering: Automatically updates and refines security telemetry rules to catch novel threat variants.

Control Optimization: Identifies gaps in firewall, endpoint, and identity coverage to optimize existing tech stack investments.

Threat Debt Reduction: Streamlines remediation pathways to neutralize critical attack paths before exploitation occurs.

AI Security Validation: Evaluates and safeguards enterprise AI infrastructure against prompt injection, data leakage, and adversarial manipulation.

Transforming Security Posture Through Agentic Automation

AVA Agentic OS offers enterprise security teams the potential to completely abandon relying on vulnerability scanning by integrating threat validation, detection engineering, and remediation into smooth-flowing workflows. It is also possible for companies to use the system for continuous monitoring of their highest-value assets thereby being sure that defensive measures adjust themselves to the ever-changing threat environment.

AVA Agentic OS is available immediately for deployment. Enterprise security leads, Chief Information Security Officers (CISOs), and IT operations managers can evaluate platform specifications or request operational demonstrations by visiting the official AttackIQ digital portal.

The post AttackIQ Unveils AVA Agentic OS to Drive Autonomous CTEM Execution appeared first on ITDigest.

In Business Technology news this week…

DXC and ElevenLabs Partner to Scale Conversational Voice AI Across Enterprise Infrastructure
DXC Technology and ElevenLabs have partnered to help enterprises deploy conversational voice AI at scale across business operations. The collaboration combines DXC’s enterprise transformation expertise with ElevenLabs’ advanced voice AI capabilities to enable intelligent customer interactions, automate workflows, and improve operational efficiency. The partnership reflects the increasing adoption of voice-enabled AI across enterprise environments.

In Cloud Computing & Mobility news this week…

Veeam Debuts Data Cloud Vault Archive to Cut Cold Storage Costs
Veeam has introduced Data Cloud Vault Archive, a new solution designed to reduce long-term cloud storage costs while maintaining secure backup and recovery capabilities. The offering enables organizations to archive infrequently accessed data more efficiently without compromising resilience or compliance. As enterprise data volumes continue to grow, cost-effective storage strategies are becoming increasingly important.

In Artificial Intelligence news this week…

Cognizant and Anthropic Expand AI Partnership to Bridge the Enterprise Absorption Gap
Cognizant and Anthropic have expanded their partnership to help enterprises accelerate the adoption of generative AI while overcoming implementation challenges. The collaboration focuses on enabling organizations to integrate AI into business processes through governance, responsible deployment, and scalable transformation strategies. The initiative highlights the growing need to bridge the gap between AI innovation and enterprise execution.

In Quantum Computing news this week…

IBM and Qedma Demonstrate Quantum Advantage to Unlock Next-Gen Materials Discovery
IBM and Qedma have demonstrated a significant quantum computing milestone that could accelerate the discovery of advanced materials. By combining IBM’s quantum hardware with Qedma’s error mitigation technologies, the collaboration showcases how quantum systems can address complex scientific problems beyond the capabilities of classical computing. The achievement represents another step toward practical enterprise applications of quantum technology.

In FinTech news this week…

LTM and Cognition Partner to Reduce Financial Cyber Risk with Devin
LTM and Cognition have partnered to help financial institutions reduce cyber risk by leveraging Devin, an AI-powered software engineering agent. The collaboration aims to improve secure software development, automate security-related tasks, and strengthen resilience against emerging cyber threats. As AI becomes more deeply integrated into financial services, secure development practices are becoming a strategic priority.

In HealthTech news this week…

Wolters Kluwer Integrates Clinical Solutions with Epic for Rural Healthcare
Wolters Kluwer has integrated its clinical decision support solutions with Epic to improve healthcare delivery in rural communities. The integration provides clinicians with seamless access to evidence-based guidance within existing workflows, supporting faster and more informed care decisions. The initiative demonstrates the growing importance of interoperability in expanding access to high-quality healthcare.

In Cybersecurity news this week…

ReSecurity Integrates Native Threat Intelligence with IBM QRadar SIEM
ReSecurity has announced a native integration between its threat intelligence platform and IBM QRadar SIEM. The integration enhances security operations by providing enriched threat intelligence, improving incident detection, and enabling faster response to cyber threats. As organizations face increasingly sophisticated attacks, integrated security intelligence is becoming essential for proactive cyber defense.

Article of the Week

Smart Medical Devices Security: How Healthcare Organizations Can Protect Connected Care in 2026

The rapid adoption of connected medical devices is transforming patient care while introducing new cybersecurity challenges for healthcare providers. From infusion pumps and patient monitors to wearable health technologies, every connected device expands the potential attack surface. Healthcare organizations must implement strong device management, network segmentation, continuous monitoring, identity controls, and proactive threat detection to safeguard clinical environments. A comprehensive security strategy not only protects sensitive patient data but also ensures operational continuity and builds trust in the future of connected healthcare.

The post ITDigest’s Weekly News Roundup Featuring DXC, Veeam, Cognizant, Anthropic, IBM, LTM, Wolters Kluwer, and ReSecurity appeared first on ITDigest.

Also Read: LTM and Anthropic Form Alliance to Drive Enterprise Claude Adoption

“Our expanded partnership with Oracle is designed to make it easier for organizations to use Gemini in the applications and agentic workflows they rely on to automate workflows, accelerate decisions, and drive outcomes.” Reaffirming the importance of choice in enterprise AI deployment, “To achieve the best business outcomes, organizations need the flexibility to choose the AI model best suited to each problem,” said Chris Leone, executive vice president, applications development, Oracle. “By bringing Gemini to Oracle AI Agent Studio for Fusion Applications, we are giving customers and partners greater choice as they build and extend agents and agentic applications that reason through complex, real-world business challenges. Oracle Fusion Applications then turn that reasoning into action through governed workflows, approvals, and transactions.” By embedding Gemini models where they offer optimal price-performance, Oracle and Google Cloud enable enterprise clients to securely execute mission-critical tasks and scale operational AI innovation.

Read More: Oracle to Make Gemini Models Available to Thousands of Enterprise Applications Customers

The post Oracle Expands Google Cloud Partnership to Bring Gemini Models to Enterprise Applications appeared first on ITDigest.

This offering seeks to meet the growing need to deal with an increasing number of autonomous AI applications deployed in various departments of corporations without coordination and supervision. The phenomenon is termed “agentic sprawl” and involves a number of risks for organizations because it can lead to a breach of data privacy, regulatory fines, and unplanned IT infrastructure costs.

Mitigating Risk in an Era of Autonomous AI Sprawl

Although enterprise software providers include proprietary AI functionality in their applications more often nowadays, it remains challenging for companies to impose consistent security policies across multi-vendor infrastructures. In order to manage the agentic sprawl, Rimini Govern for AI creates an independent management layer controlling the activity of AI agents on various platforms, including SAP, Oracle, and Salesforce.

Also Read: Resecurity Integrates Native Threat Intelligence with IBM QRadar SIEM

The service provides enterprise technology leaders with four primary operational safeguards:

Centralized Policy Enforcement: Manages user permissions, data access boundaries, and regulatory compliance protocols from a single dashboard.

Continuous Security and Privacy Guardrails: Shields sensitive corporate data from improper exposure, prevents unauthorized tool usage, and mitigates prompt injection risks.

Unified Auditability: Logs agent decision-making steps, tool calls, and data transactions to maintain compliance-ready records for external regulators.

Cost and Resource Optimization: Sets usage thresholds and monitors API consumption across underlying language models to eliminate unexpected cloud expenditure.

“Enterprises are deploying AI agents at an incredible pace, but without proper governance, this rapid adoption creates significant security, compliance, and financial risks. Rimini Govern for AI gives organizations the visibility and control they need to safely scale AI initiatives while protecting their enterprise data and technology investments.” Seth Ravin, Chairman and CEO of Rimini Street

Strategic Complement to the Rimini Consult Portfolio

Rimini Govern for AI expands the company’s broader consulting and managed services ecosystem. Designed to integrate seamlessly with existing enterprise systems, the solution allows organizations to adopt emerging agentic workflows without undergoing disruptive, capital-intensive platform migrations.

By establishing clear operational boundaries for autonomous software, the service helps chief information officers, chief security officers, and risk directors leverage artificial intelligence while maintaining strict operational control.

The post Rimini Street Launches Rimini Govern for AI to Secure and Control Enterprise AI Agents appeared first on ITDigest.

As organizations rapidly deploy autonomous AI agents and large language model (LLM) applications, applying conventional application security protocols creates operational friction and critical blind spots. According to the findings of The Harness State of AI-Native Application Security Report, 74% of developers view security controls as one of the biggest barriers to innovation when it comes to AI. However, 62% of security professionals note that development teams fail to handle risks associated with AI-native applications. The new integration solves the problem through automation of security processes within developer processes.

“Organizations are innovating with agents at breakneck speed,” said Rahul Sood, GM of Application Security at Harness. “As they innovate and adopt new capabilities, they are forcing security teams to keep pace. This integration allows customers building on Apigee to seamlessly detect and protect agents as they are being deployed so developers can innovate confidently.”

Also Read: Cyberhaven Expands Data and AI Security Platform with ChatGPT and Claude

End-to-End Governance Across the AI Agent Lifecycle

By situating security controls within Apigee which manages traffic between end-users, foundational models, back-end APIs, and agentic tools organizations can secure new AI interaction patterns without building separate infrastructure. The platform delivers three core security layers:

Automated Agent Discovery: Continuously inventories AI assets, MCP servers, and connected tools as they deploy across the network. Agent Security Posture Management (Agent SPM) maps complex asset dependencies and evaluates organizational risks automatically.

Real-Time AI Firewall: Monitors live runtime activity to enforce security policies against prompt injection attempts, tool misuse, unauthorized agent-to-agent communication, and data exfiltration.

Comprehensive Activity Observability (AgentTrace): Maintains a complete audit trail across user prompts, AI reasoning steps, tool calls, and outputs to evaluate non-deterministic system behaviors.

“Securing AI agents and emerging technologies requires a paradigm shift in how we think about enterprise protection,” said Ritika Suri, Managing Director, AI & Data ISV Partnerships, Google Cloud. “Through our collaboration with Harness, we are bringing robust, agent-aware security to our joint customers without compromising on the agility to deliver solutions that help organizations innovate with confidence.”

The post Harness Integrates Agentic AI Security with Google Cloud Apigee appeared first on ITDigest.

Also Read: Sauce Labs Launches AURA to Eliminate the AI Code Verification Gap

The tool natively supports many popular test systems Playwright Selenium Cypress Appium WebdriverIO and TestNG in fact, and makes it easy for teams to run software quality testing on their own devices or from any of their browsers across over 30,000 devices and browsers that our tool has access to via partner cloud. Emphasizing the operational necessity of supporting the entire testing lifecycle rather than just initial script generation, Nakul Aggarwal, CTO and co-founder of BrowserStack, stated: “Fifteen years of building for testing teams taught us that a test is never written and done. The application changes, the test breaks, and someone has to fix it. Any AI that only writes tests solves the easy part. Test Companion owns the full cycle, and that’s the shift.” Now generally available, Test Companion enables over 1,000 early enterprise adopters to author, debug, and maintain complex web and mobile test suites up to four times faster without requiring manual context switching.

Read More: BrowserStack Launches Test Companion, Agentic AI That Brings Complete Test Automation Into the IDE

The post BrowserStack Introduces Test Companion to Automate IDE-Based Software Testing appeared first on ITDigest.

Security alerts flag activity that matches predefined detection rules, helping teams identify known threats and suspicious behavior, but they are only one lens into the environment. Threat hunting looks for everything else. Finding and remediating the emerging risks and coverage gaps that alerts were not designed to surface is a critical part of any security program. The problem: Traditional threat hunting demands specialized expertise, custom queries, and analyst time that most teams simply cannot spare. A single hunt can take 10 to 20 hours of work, so hunting tends to happen rarely, reactively, or not at all. AI Threat Hunter removes these barriers by turning hunting into an achievable, routine part of the SOC, with the team deciding what to hunt and the agent doing the work.

With more than 270 hunt packs mapped to real attacker behavior and MITRE ATT&CK, it doesn’t just query your tools. It investigates like a senior analyst, connecting evidence across your security stack and returning a complete, reasoned finding you can act on immediately. Each pack bundles 5 to 10 hunts that run together, so work that once consumed a team’s week now returns results in about one to two hours, with every step fully transparent and in your control. Unlike conversational hunting assistants or solutions that simply help analysts search data, AI Threat Hunter is a repeatable, scheduled operation that takes threat hunting from a nice-to-have to operationalized.

Also Read: Sumsub Introduces First AI-powered Trust Infrastructure as Compliance Operations Evolve 

AI Threat Hunter is already running federated, hypothesis-driven hunts across Splunk, Microsoft Sentinel, CrowdStrike NG-SIEM, Elastic, and Panther. Beyond active threats, each hunt surfaces posture insights such as visibility gaps, policy violations, and misconfigurations, along with detection opportunities. Teams can export threat reports and summaries in the UI, review hunt history, and rely on context memory that filters out known-benign activity in their environment. Additional capabilities are planned for the second half of 2026, including custom hypothesis-based hunts, more data sources, and tighter integration with Dropzone AI’s AI SOC Analyst to enable response actions.

“Attackers already operate at machine speed. Compute, not skill, is their bottleneck now, and defenders can’t out-hire that gap. AI Threat Hunter lets any team proactively identify undetected intrusions at the same speed, turning hunting from a once-a-year luxury into an operational habit and leveling a field that’s been tilting toward attackers for years. Analysts can now stay focused on the judgment only they can give rather than the mechanics of building and running hunts.” said Edward Wu, Founder and CEO of Dropzone AI.

More than 300 enterprises and MSSPs run the Dropzone AI platform today, and the results are consistent: teams reclaim hours and investigate more of their environment than ever. Zapier cut triage from 10 to 15 minutes to under two, an 85% reduction. UiPath saved 700+ analyst hours and cut false positives by 86%. Assala Energy hit 100% alert investigation and 5x faster response with a lean team. AI Threat Hunter brings that same machine-speed advantage to threat hunting, in beta alone it automated the equivalent of 200 years of hunting work.

“AI Threat Hunter ran this without pulling a single person off their queue, and by the end of it we had a clear, evidence-backed finding we could take straight to leadership. That’s the kind of leverage a security team actually needs,” said Greg Spillman, Cyber Fusion Center Technical Lead.

Source: BusinessWire

The post Dropzone AI Makes AI Threat Hunter Generally Available, Bringing Proactive Threat Hunting to Every SOC appeared first on ITDigest.