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By Kovrr
Cyber risk benchmarking is the practice of measuring an organization's security posture, quantified exposure, and operational metrics against comparable companies in the same sector and size band. Done well, it answers three questions a board expects the CISO to answer. Done poorly, it produces vanity metrics that look impressive in a slide deck and mean nothing when the auditors, regulators, or insurance carriers start asking questions.
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By Kovrr
Shadow AI is the fastest-growing unmanaged risk surface in most organizations. Employees are adopting AI tools through browser extensions, free-tier SaaS accounts, personal logins, and embedded platform features without involving IT, security, or procurement. The result is an expanding footprint of AI systems that process corporate data, generate business outputs, and create compliance exposure while remaining invisible to the governance program responsible for managing those risks.
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By Kovrr
AI agents introduce a category of security risk that traditional application security, identity management, and even standard AI security programs were not designed to handle. Unlike a generative model that only produces text, an agent takes autonomous action against real systems, chains API calls together to accomplish goals, and often holds permissions broad enough to touch data across multiple business systems.
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By Kovrr
Cyber insurance has become a standard line item in enterprise risk management, and for good reason. The financial consequences of a significant cyber event, whether a ransomware attack that halts operations for weeks or a data breach that triggers regulatory scrutiny and third-party liability, can far exceed what any operational budget was sized to absorb. Insurance exists to handle that tail. Most organizations recognize this benefit and carry a policy.
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By Kovrr
Agentic AI and generative AI both build on large language models, but they behave in fundamentally different ways once deployed. Generative AI produces content in response to a specific prompt and then stops. Agentic AI receives a goal, then autonomously plans, decides, and executes multi-step workflows to accomplish that goal, often across systems and tools the enterprise runs. That difference is the difference between an AI that helps a human do work faster and an AI that does the work itself.
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By Kovrr
Cyber risk quantification methodologies translate technical exposure into structured financial estimates using mathematical, statistical, and actuarial techniques instead of ordinal ratings like high, medium, or low. The methodological landscape has matured enough that buyers now face real choices between frameworks that describe how to reason about risk, models that produce the numbers, and automated platforms that combine both.
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By Kovrr
Organizations assess and manage AI-related risks by establishing a cross-functional governance framework, mapping risks based on impact and financial likelihood, and instituting continuous monitoring that connects AI asset discovery to risk quantification, compliance, and enforcement. The most effective programs treat AI risk management not as a one-time assessment but as a continuous, data-driven discipline that evolves alongside the AI systems it governs.
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By Kovrr
AI governance tools are software platforms designed to help organizations manage AI risks, ensure regulatory compliance, and enforce responsible AI use across the machine learning lifecycle. The market has expanded rapidly, and in 2026 it includes tools spanning compliance automation, model observability, data governance, infrastructure security, and integrated risk quantification.
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By Kovrr
Cyber risk quantification tools translate technical exposure into the same financial language a CFO uses for market, credit, and operational risk. The best of them run probabilistic models on real telemetry, produce defensible loss distributions in dollar terms, and connect quantified exposure to the day-to-day workflows security teams already run: risk registers, board reporting, budget prioritization, and cyber insurance decisions. The wrong tool produces a static number no one trusts.
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By Kovrr
Tracking AI use across business units requires a purpose-built approach that combines endpoint monitoring, browser-level telemetry, network security tools, and a centralized AI governance platform. Most organizations rely on some combination of IT asset management, SaaS monitoring, and manual surveys to understand what AI tools employees are using.
live webinar with Aaron Turner, IANS Faculty, who presents findings from his recent IANS research, 7 Steps to Securing Multi-AI Deployments, and explain how security teams can apply proven principles to modern AI systems.
Kovrr’s new AI Risk Governance Suite gives enterprises the visibility, structure, and measurable control needed to manage GenAI responsibly across its full lifecycle. Join us for Office Hours: Part 1, where Or Amir will walk through the first three modules of the suite—showing how enterprises can gain real-time oversight and quantifiable insight into their AI landscape: Discover how these capabilities help enterprises align innovation with accountability—building a defensible foundation for responsible GenAI adoption.
In this session, Or Amir, Product Manager at Kovrr, showcases our new AI Risk Assessment and AI Risk Quantification modules — helping enterprises gain visibility, benchmark maturity, identify shadow AI, and turn exposure into measurable outcomes.
Explore Kovrr’s brand-new CRQ-Powered Cyber Risk Register — a first-of-its-kind solution that’s redefining the way organizations build cyber GRC programs and manage cyber risk. Led by Or Amir, Product Manager at Kovrr, this session will offer a hands-on deep dive into the risk register’s extensive capabilities and show you why moving beyond static, spreadsheet-based registers to a fully quantified, dynamic risk intelligence framework is necessary for achieving resilience in today’s landscape.
On June 15, 2024, half a year after the SEC's cybersecurity regulations were enacted, smaller organizations—those with a public float under $250 million or annual revenue under $100 million—were finally subject to report material cyber events on Form 8-K, Line 1.05. However, as the larger entities have already demonstrated, determining materiality can be complex, requiring stakeholders to consider financial loss, compromised data records, operational impacts, and more.
* Explore some of the top use cases for which our on-demand CRQ platform is utilized, walking through the specific features and how to leverage them for each of the use cases. These use cases include high-level communication and board reporting, insurance optimization, budgeting, and additional resource justification.
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By Kovrr
Join us for a monthly insightful session where each month we will: Walkthrough our CRQ platform Unveil exciting new product features (when applicable)
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By Kovrr
Join us for a monthly insightful session where each month we will: Walkthrough our CRQ platform Unveil exciting new product features (when applicable)
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By Kovrr
Join us for a monthly insightful session where each month we will: Walkthrough our CRQ platform Unveil exciting new product features (when applicable) Conduct Interactive Q&A Session.
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By Kovrr
Join Kovrr and Dmitriy Sokolovskiy, former CISO at Avid, as he shares his experience and provides highlights and Insights on his CRQ Journey. Some of the topics that Dmitriy will discuss.
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By Kovrr
By its nature, cyber risk is dynamic. New events happen and evolve all the time, making it difficult for enterprises to financially quantify their financial exposure to cyber attacks. Around two years ago, for example, distributed denial-of-service (DDoS) attacks were making headlines, and now ransomware has come into heightened focus. It's reasonable to believe that other types of attacks will emerge in another two years and continue to change thereafter.
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By Kovrr
The number of data breaches reported in the first 6 months of 2022 has put this year on track to be the lowest year of reports in the last 5 years for large US corporations. By looking at the rate at which data breach events have been reported so far this year, we predict that the number of events reported is expected to be 15-20% of the number of breaches reported in 2021
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By Kovrr
The 2022 Verizon Data Breach Investigations Report (DBIR), the fifteenth such report in as many years, leads off with a startling statistic: Credentials are the number one overall attack vector hackers use in data breaches. Use of stolen credentials accounts for nearly half the breaches studied by Verizon, far ahead of phishing and exploit vulnerabilities, which account for 19% and 8% of attacks, respectively. Botnets, the fourth most common entry path for hackers, represent a mere 1% of attacks.
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Kovrr financially quantifies cyber risk on demand. Our technology enables decision makers to seamlessly drive actionable cyber risk management decisions.
Kovrr's Quantum Cyber Risk Quantification platform enables decision makers to understand and financially quantify the changing profile of their cyber risk exposure.
Cyber Risk Management Made Easy:
- Communicate Cyber Risk in Financial Terms: Enhance the board and C-Suite’s decision-making process by financially quantifying cyber risk.
- Cybersecurity Investment Optimization: Prioritize and justify cybersecurity investments based on business impacts and risk reduction.
- Measure Cyber Security Programs’ Effectiveness: Assess the ROI of your cybersecurity program and stress test it based on potential risk mitigation actions, thereby supporting better resource allocation.
- 3rd Party Vendors Cyber Risk Exposure Analysis: Financially quantify cyber risk within your supply chain. Gain insights Into 3rd and 4th party exposure.
- Regulatory Compliance and Governance Reporting: Meet increased demands from regulators to continuously quantify and manage cyber risk exposure.
- Cyber Insurance Coverage and Price Optimization: Identify gaps between risk mitigation impact versus risk cyber insurance spending and needed coverage for 1st party and 3rd party.
- Quantitatively Benchmark and Compare your Cyber Risk Exposure: Benchmark to your industry peers and internally compare between different business entities in a consistent, measurable and accurate way.
A cyber risk management platform to quantify custom cyber risk scenarios.