Nov 19 2025

Understanding Your AI System’s Risk Level: A Guide to EU AI Act Compliance

Category: AI,AI Governance,AI Governance Tools,AI Guardrails,Risk Assessment — disc7 @ 9:46 am

A Guide to EU AI Act Compliance

The European Union’s Artificial Intelligence Act represents the world’s first comprehensive regulatory framework for artificial intelligence. As organizations worldwide prepare for compliance, one of the most critical first steps is understanding exactly where your AI system falls within the EU’s risk-based classification structure.

At DeuraInfoSec, we’ve developed a streamlined EU AI Act Risk Calculator to help organizations quickly assess their compliance obligations.🔻 But beyond the tool itself, understanding the framework is essential for any organization deploying AI systems that touch EU markets or citizens.

eu-ai-act-classifier

The EU AI Act’s Risk-Based Approach

The EU AI Act takes a pragmatic, risk-based approach to regulation. Rather than treating all AI systems equally, it categorizes them into four distinct risk levels, each with different compliance requirements:

1. Unacceptable Risk (Prohibited Systems)

These AI systems pose such fundamental threats to human rights and safety that they are completely banned in the EU. This category includes:

  • Social scoring by public authorities that evaluates or classifies people based on behavior, socioeconomic status, or personal characteristics
  • Real-time remote biometric identification in publicly accessible spaces (with narrow exceptions for law enforcement in specific serious crimes)
  • Systems that manipulate human behavior to circumvent free will and cause harm
  • Systems that exploit vulnerabilities of specific groups due to age, disability, or socioeconomic circumstances

If your AI system falls into this category, deployment in the EU is simply not an option. Alternative approaches must be found.

2. High-Risk AI Systems

High-risk systems are those that could significantly impact health, safety, fundamental rights, or access to essential services. The EU AI Act identifies high-risk AI in two ways:

Safety Components: AI systems used as safety components in products covered by existing EU safety legislation (medical devices, aviation, automotive, etc.)

Specific Use Cases: AI systems used in eight critical domains:

  • Biometric identification and categorization
  • Critical infrastructure management
  • Education and vocational training
  • Employment, worker management, and self-employment access
  • Access to essential private and public services
  • Law enforcement
  • Migration, asylum, and border control management
  • Administration of justice and democratic processes

High-risk AI systems face the most stringent compliance requirements, including conformity assessments, risk management systems, data governance, technical documentation, transparency measures, human oversight, and ongoing monitoring.

3. Limited Risk (Transparency Obligations)

Limited-risk AI systems must meet specific transparency requirements to ensure users know they’re interacting with AI:

  • Chatbots and conversational AI must clearly inform users they’re communicating with a machine
  • Emotion recognition systems require disclosure to users
  • Biometric categorization systems must inform individuals
  • Deepfakes and synthetic content must be labeled as AI-generated

While these requirements are less burdensome than high-risk obligations, they’re still legally binding and require thoughtful implementation.

4. Minimal Risk

The vast majority of AI systems fall into this category: spam filters, AI-enabled video games, inventory management systems, and recommendation engines. These systems face no specific obligations under the EU AI Act, though voluntary codes of conduct are encouraged, and other regulations like GDPR still apply.

Why Classification Matters Now

Many organizations are adopting a “wait and see” approach to EU AI Act compliance, assuming they have time before enforcement begins. This is a costly mistake for several reasons:

Timeline is Shorter Than You Think: While full enforcement doesn’t begin until 2026, high-risk AI systems will need to begin compliance work immediately to meet conformity assessment requirements. Building robust AI governance frameworks takes time.

Competitive Advantage: Early movers who achieve compliance will have significant advantages in EU markets. Organizations that can demonstrate EU AI Act compliance will win contracts, partnerships, and customer trust.

Foundation for Global Compliance: The EU AI Act is setting the standard that other jurisdictions are likely to follow. Building compliance infrastructure now prepares you for a global regulatory landscape.

Risk Mitigation: Even if your AI system isn’t currently deployed in the EU, supply chain exposure, data processing locations, or future market expansion could bring you into scope.

Using the Risk Calculator Effectively

Our EU AI Act Risk Calculator is designed to give you a rapid initial assessment, but it’s important to understand what it can and cannot do.

What It Does:

  • Provides a preliminary risk classification based on key regulatory criteria
  • Identifies your primary compliance obligations
  • Helps you understand the scope of work ahead
  • Serves as a conversation starter for more detailed compliance planning

What It Doesn’t Replace:

  • Detailed legal analysis of your specific use case
  • Comprehensive gap assessments against all requirements
  • Technical conformity assessments
  • Ongoing compliance monitoring

Think of the calculator as your starting point, not your destination. If your system classifies as high-risk or even limited-risk, the next step should be a comprehensive compliance assessment.

Common Classification Challenges

In our work helping organizations navigate EU AI Act compliance, we’ve encountered several common classification challenges:

Boundary Cases: Some systems straddle multiple categories. A chatbot used in customer service might seem like limited risk, but if it makes decisions about loan approvals or insurance claims, it becomes high-risk.

Component vs. System: An AI component embedded in a larger system may inherit the risk classification of that system. Understanding these relationships is critical.

Intended Purpose vs. Actual Use: The EU AI Act evaluates AI systems based on their intended purpose, but organizations must also consider reasonably foreseeable misuse.

Evolution Over Time: AI systems evolve. A minimal-risk system today might become high-risk tomorrow if its use case changes or new features are added.

The Path Forward

Whether your AI system is high-risk or minimal-risk, the EU AI Act represents a fundamental shift in how organizations must think about AI governance. The most successful organizations will be those who view compliance not as a checkbox exercise but as an opportunity to build more trustworthy, robust, and valuable AI systems.

At DeuraInfoSec, we specialize in helping organizations navigate this complexity. Our approach combines deep technical expertise with practical implementation experience. As both practitioners (implementing ISO 42001 for our own AI systems at ShareVault) and consultants (helping organizations across industries achieve compliance), we understand both the regulatory requirements and the operational realities of compliance.

Take Action Today

Start with our free EU AI Act Risk Calculator to understand your baseline risk classification. Then, regardless of your risk level, consider these next steps:

  1. Conduct a comprehensive AI inventory across your organization
  2. Perform detailed risk assessments for each AI system
  3. Develop AI governance frameworks aligned with ISO 42001
  4. Implement technical and organizational measures appropriate to your risk level
  5. Establish ongoing monitoring and documentation processes

The EU AI Act isn’t just another compliance burden. It’s an opportunity to build AI systems that are more transparent, more reliable, and more aligned with fundamental human values. Organizations that embrace this challenge will be better positioned for success in an increasingly regulated AI landscape.

Ready to assess your AI system’s risk level? Try our free EU AI Act Risk Calculator now.

Need expert guidance on compliance? Contact DeuraInfoSec.com today for a comprehensive assessment.

Email: info@deurainfosec.com
Phone: (707) 998-5164

DeuraInfoSec specializes in AI governance, ISO 42001 implementation, and EU AI Act compliance for B2B SaaS and financial services organizations. We’re not just consultants—we’re practitioners who have implemented these frameworks in production environments.

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Tags: AI System, EU AI Act

Nov 18 2025

Building an Effective AI Risk Assessment Process

Category: AI,AI Governance,AI Governance Tools,Risk Assessment — disc7 @ 10:32 am

Building an Effective AI Risk Assessment Process: A Practical Guide

As organizations rapidly adopt artificial intelligence, the need for structured AI risk assessment has never been more critical. With regulations like the EU AI Act and standards like ISO 42001 reshaping the compliance landscape, companies must develop systematic approaches to evaluate and manage AI-related risks.

Why AI Risk Assessment Matters

Traditional IT risk frameworks weren’t designed for AI systems. Unlike conventional software, AI systems learn from data, evolve over time, and can produce unpredictable outcomes. This creates unique challenges:

  • Regulatory Complexity: The EU AI Act classifies systems by risk level, with severe penalties for non-compliance
  • Operational Uncertainty: AI decisions can be opaque, making risk identification difficult
  • Rapid Evolution: AI capabilities and risks change as models are retrained
  • Multi-stakeholder Impact: AI affects customers, employees, and society differently

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The Four-Stage Assessment Framework

An effective AI risk assessment follows a structured progression from basic information gathering to actionable insights.

Stage 1: Organizational Context

Understanding your organization’s AI footprint begins with foundational questions:

Company Profile

  • Size and revenue (risk tolerance varies significantly)
  • Industry sector (different regulatory scrutiny levels)
  • Geographic presence (jurisdiction-specific requirements)

Stakeholder Identification

  • Who owns AI procurement decisions?
  • Who bears accountability for AI outcomes?
  • Where does AI governance live organizationally?

This baseline helps calibrate the assessment to your organization’s specific context and risk appetite.

Stage 2: AI System Inventory

The second stage maps your actual AI implementations. Many organizations underestimate their AI exposure by focusing only on custom-built systems while overlooking:

  • Customer-Facing Systems: Chatbots, recommendation engines, virtual assistants
  • Operational Systems: Fraud detection, predictive analytics, content moderation
  • HR Systems: Resume screening, performance prediction, workforce optimization
  • Financial Systems: Credit scoring, loan decisioning, insurance pricing
  • Security Systems: Biometric identification, behavioral analysis, threat detection

Each system type carries different risk profiles. For example, biometric identification and emotion recognition trigger higher scrutiny under the EU AI Act, while predictive analytics may have lower inherent risk but broader organizational impact.

Stage 3: Regulatory Risk Classification

This critical stage determines your compliance obligations, particularly under the EU AI Act which uses a risk-based approach:

High-Risk Categories Systems that fall into these areas require extensive documentation, testing, and oversight:

  • Employment decisions (hiring, firing, promotion, task allocation)
  • Credit and lending decisions
  • Insurance pricing and claims processing
  • Educational access or grading
  • Law enforcement applications
  • Critical infrastructure management (energy, transportation, water)

Risk Multipliers Certain factors elevate risk regardless of system type:

  • Direct interaction with EU consumers or residents
  • Use of biometric data or emotion recognition
  • Impact on vulnerable populations
  • Deployment in regulated sectors (healthcare, finance, education)

Risk Scoring Methodology A quantitative approach helps prioritize remediation:

  • Assign base scores to high-risk categories (3-4 points each)
  • Add points for EU consumer exposure (+2 points)
  • Add points for sensitive technologies like biometrics (+3 points)
  • Calculate total risk score to determine classification

Example thresholds:

  • HIGH RISK: Score ≥5 (immediate compliance required)
  • MEDIUM RISK: Score 2-4 (enhanced governance needed)
  • LOW RISK: Score <2 (standard controls sufficient)

Stage 4: ISO 42001 Control Gap Analysis

The final stage evaluates your AI management system maturity against international standards. ISO 42001 provides a comprehensive framework covering:

A.4 – AI Policy Framework

  • Are AI policies documented, approved, and maintained?
  • Do policies cover ethical use, data handling, and accountability?
  • Are policies communicated to relevant stakeholders?

Gap Impact: Without policy foundation, you lack governance structure and face regulatory penalties.

A.6 – Data Governance

  • Do you track AI training data sources systematically?
  • Is data quality, bias, and lineage documented?
  • Can you prove data provenance during audits?

Gap Impact: Poor data tracking creates audit failures and enables undetected bias propagation.

A.8 – AI Incident Management

  • Are AI incident response procedures documented and tested?
  • Do procedures cover detection, containment, and recovery?
  • Are escalation paths and communication protocols defined?

Gap Impact: Without incident procedures, AI failures cause business disruption and regulatory violations.

A.5 – AI Impact Assessment

  • Do you conduct regular impact assessments?
  • Are assessments comprehensive (fairness, safety, privacy, security)?
  • Is assessment frequency appropriate to system criticality?

Gap Impact: Infrequent assessments allow risks to accumulate undetected over time.

A.9 – Transparency & Explainability

  • Can you explain AI decision-making to stakeholders?
  • Is documentation appropriate for technical and non-technical audiences?
  • Are explanation mechanisms built into systems, not retrofitted?

Gap Impact: Inability to explain decisions violates transparency requirements and damages stakeholder trust.

Implementing the Assessment Process

Technical Implementation Considerations

When building an assessment tool – key design principles include:

Progressive Disclosure

  • Break assessment into digestible sections with clear progress indicators
  • Use branching logic to show only relevant questions
  • Validate each section before allowing progression

User Experience

  • Visual feedback for risk levels (color-coded: red/high, yellow/medium, green/low)
  • Clear section descriptions explaining “why” questions matter
  • Mobile-responsive design for completion flexibility

Data Collection Strategy

  • Mix question types: multiple choice for consistency, checkboxes for comprehensive coverage
  • Require critical fields while making others optional
  • Save progress to prevent data loss

Scoring Algorithm Transparency

  • Document risk scoring methodology clearly
  • Explain how answers translate to risk levels
  • Provide immediate feedback on assessment completion

Automated Report Generation

Effective assessments produce actionable outputs:

Risk Level Summary

  • Clear classification (HIGH/MEDIUM/LOW)
  • Plain language explanation of implications
  • Regulatory context (EU AI Act, ISO 42001)

Gap Analysis

  • Specific control deficiencies identified
  • Business impact of each gap explained
  • Prioritized remediation recommendations

Next Steps

  • Concrete action items with timelines
  • Resources needed for implementation
  • Quick wins vs. long-term initiatives

From Assessment to Action

The assessment is just the beginning. Converting insights into compliance requires:

Immediate Actions (0-30 days)

  • Address critical HIGH RISK findings
  • Document current AI inventory
  • Establish incident response contacts

Short-term Actions (1-3 months)

  • Develop missing policy documentation
  • Implement data governance framework
  • Create impact assessment templates

Medium-term Actions (3-6 months)

  • Deploy monitoring and logging
  • Conduct comprehensive impact assessments
  • Train staff on AI governance

Long-term Actions (6-12 months)

  • Pursue ISO 42001 certification
  • Build continuous compliance monitoring
  • Mature AI governance program

Measuring Success

Track these metrics to gauge program maturity:

  • Coverage: Percentage of AI systems assessed
  • Remediation Velocity: Average time to close gaps
  • Incident Rate: AI-related incidents per quarter
  • Audit Readiness: Time needed to produce compliance documentation
  • Stakeholder Confidence: Survey results from users, customers, regulators

Conclusion

AI risk assessment isn’t a one-time checkbox exercise. It’s an ongoing process that must evolve with your AI capabilities, regulatory landscape, and organizational maturity. By implementing a structured four-stage approach—organizational context, system inventory, regulatory classification, and control gap analysis—you create a foundation for responsible AI deployment.

The assessment tool we’ve built demonstrates that compliance doesn’t have to be overwhelming. With clear frameworks, automated scoring, and actionable insights, organizations of any size can begin their AI governance journey today.

Ready to assess your AI risk? Start with our free assessment tool or schedule a consultation to discuss your specific compliance needs.

About DeuraInfoSec: We specialize in AI governance, ISO 42001 implementation, and information security compliance for B2B SaaS and financial services companies. Our practical, outcome-focused approach helps organizations navigate complex regulatory requirements while maintaining business agility.

Free AI Risk Assessment: Discover Your EU AI Act Classification & ISO 42001 Gaps in 15 Minutes

A progressive 4-stage web form that collects company info, AI system inventory, EU AI Act risk factors, and ISO 42001 readiness, then calculates a risk score (HIGH/MEDIUM/LOW), identifies control gaps across 5 key ISO 42001 areas. Built with vanilla JavaScript, uses visual progress tracking, color-coded results display, and includes a CTA for Calendly booking, with all scoring logic and gap analysis happening client-side before submission. Concise, tailored high-level risk snapshot of your AI system.

What’s Included:

✅ 4-section progressive flow (15 min completion time) ✅ Smart risk calculation based on EU AI Act criteria ✅ Automatic gap identification for ISO 42001 controls ✅ PDF generation with 3-page professional report ✅ Dual email delivery (to you AND the prospect) ✅ Mobile responsive design ✅ Progress tracking visual feedback

Click below 👇 to launch your AI Risk Assessment.

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CISO MindMap 2025 by Rafeeq Rehman

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Tags: AI risk assessment

Nov 13 2025

Closing the Loop: Turning Risk Logs into Actionable Insights

Category: Risk Assessment,Security Risk Assessment — disc7 @ 3:06 pm

Your Risk Program Is Only as Strong as Its Feedback Loop

Many organizations are excellent at identifying risks, but far fewer are effective at closing them. Logging risks in a register without follow-up is not true risk management—it’s merely risk archiving.

A robust risk program follows a complete cycle: identify risks, assess their impact and likelihood, assign ownership, implement mitigation, verify effectiveness, and feed lessons learned back into the system. Skipping verification and learning steps turns risk management into a task list, not a strategic control process.

Without a proper feedback loop, the same issues recur across departments, “closed” risks resurface during audits, teams lose confidence in the process, and leadership sees reports rather than meaningful results.

Building an Effective Feedback Loop:

  • Make verification mandatory: every mitigation must be validated through control testing or monitoring.
  • Track lessons learned: use post-mortems to refine controls and frameworks.
  • Automate follow-ups: trigger reviews for risks not revisited within set intervals.
  • Share outcomes: communicate mitigation results to teams to strengthen ownership and accountability.

Pro Tips:

  1. Measure risk elimination, not just identification.
  2. Highlight a “risk of the month” internally to maintain awareness.
  3. Link the risk register to performance metrics to align incentives with action.

The most effective GRC programs don’t just record risks—they learn from them. Every feedback loop strengthens organizational intelligence and security.

Many organizations excel at identifying risks but fail to close them, turning risk management into mere record-keeping. A strong program not only identifies, assesses, and mitigates risks but also verifies effectiveness and feeds lessons learned back into the system. Without this feedback loop, issues recur, audits fail, and teams lose trust. Mandating verification, tracking lessons, automating follow-ups, and sharing outcomes ensures risks are truly managed, not just logged—making your organization smarter, safer, and more accountable.

Risk Maturity Models: How to Assess Risk Management Effectiveness

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Tags: Risk Assessment, risk logs

Oct 15 2025

The Rising Risk: Are AI and Crypto Fueling the Next Financial Collapse?

Category: AI Guardrails,Crypto,Risk Assessment — disc7 @ 10:35 am

The Robert Reich article highlights the dangers of massive financial inflows into poorly understood and unregulated industries — specifically artificial intelligence (AI) and cryptocurrency. Historically, when investors pour money into speculative assets driven by hype rather than fundamentals, bubbles form. These bubbles eventually burst, often dragging the broader economy down with them. Examples from history — like the dot-com crash, the 2008 housing collapse, and even tulip mania — show the recurring nature of such cycles.

AI, the author argues, has become the latest speculative bubble. Despite immense enthusiasm and skyrocketing valuations for major players like OpenAI, Nvidia, Microsoft, and Google, the majority of companies using AI aren’t generating real profits. Public subsidies and tax incentives for data centers are further inflating this market. Meanwhile, traditional sectors like manufacturing are slowing, and jobs are being lost. Billionaires at the top — such as Larry Ellison and Jensen Huang — are seeing massive wealth gains, but this prosperity is not trickling down to the average worker. The article warns that excessive debt, overvaluation, and speculative frenzy could soon trigger a painful correction.

Crypto, the author’s second major concern, mirrors the same speculative dynamics. It consumes vast energy, creates little tangible value, and is driven largely by investor psychology and hype. The recent volatility in cryptocurrency markets — including a $19 billion selloff following political uncertainty — underscores how fragile and over-leveraged the system has become. The fusion of AI and crypto speculation has temporarily buoyed U.S. markets, creating the illusion of economic strength despite broader weaknesses.

The author also warns that deregulation and politically motivated policies — such as funneling pension funds and 401(k)s into high-risk ventures — amplify systemic risk. The concern isn’t just about billionaires losing wealth but about everyday Americans whose jobs, savings, and retirements could evaporate when the bubbles burst.

Opinion:
This warning is timely and grounded in historical precedent. The parallels between the current AI and crypto boom and previous economic bubbles are clear. While innovation in AI offers transformative potential, unchecked speculation and deregulation risk turning it into another economic disaster. The prudent approach is to balance enthusiasm for technological advancement with strong oversight, realistic valuations, and diversification of investments. The writer’s call for individuals to move some savings into safer, low-risk assets is wise — not out of panic, but as a rational hedge against an increasingly overheated and unstable financial environment.

Ai’S Rising Threat: A Beginner’S Guide To Navigating Risks

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“AI is already the single largest uncontrolled channel for corporate data exfiltration—bigger than shadow SaaS or unmanaged file sharing.”

Click the ISO 42001 Awareness Quiz — it will open in your browser in full-screen mode

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Check out our earlier posts on AI-related topics: AI topic

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Tags: AI Risk, Crypto Risk

Aug 05 2025

EU AI Act concerning Risk Management Systems for High-Risk AI

Category: AI,Risk Assessment — disc7 @ 11:10 am

  1. Lifecycle Risk Management
    Under the EU AI Act, providers of high-risk AI systems are obligated to establish a formal risk management system that spans the entire lifecycle of the AI system—from design and development to deployment and ongoing use.
  2. Continuous Implementation
    This system must be established, implemented, documented, and maintained over time, ensuring that risks are continuously monitored and managed as the AI system evolves.
  3. Risk Identification
    The first core step is to identify and analyze all reasonably foreseeable risks the AI system may pose. This includes threats to health, safety, and fundamental rights when used as intended.
  4. Misuse Considerations
    Next, providers must assess the risks associated with misuse of the AI system—those that are not intended but are reasonably predictable in real-world contexts.
  5. Post-Market Data Analysis
    The system must include regular evaluation of new risks identified through the post-market monitoring process, ensuring real-time adaptability to emerging concerns.
  6. Targeted Risk Measures
    Following risk identification, providers must adopt targeted mitigation measures tailored to reduce or eliminate the risks revealed through prior assessments.
  7. Residual Risk Management
    If certain risks cannot be fully eliminated, the system must ensure these residual risks are acceptable, using mitigation strategies that bring them to a tolerable level.
  8. System Testing Requirements
    High-risk AI systems must undergo extensive testing to verify that the risk management measures are effective and that the system performs reliably and safely in all foreseeable scenarios.
  9. Special Consideration for Vulnerable Groups
    The risk management system must account for potential impacts on vulnerable populations, particularly minors (under 18), ensuring their rights and safety are adequately protected.
  10. Ongoing Review and Adjustment
    The entire risk management process should be dynamic, regularly reviewed and updated based on feedback from real-world use, incident reports, and changing societal or regulatory expectations.

🔐 Main Requirement Summary:

Providers of high-risk AI systems must implement a comprehensive, documented, and dynamic risk management system that addresses foreseeable and emerging risks throughout the AI lifecycle—ensuring safety, fundamental rights protection, and consideration for vulnerable groups.

The EU AI Act: Answers to Frequently Asked Questions 

EU AI ACT 2024

EU publishes General-Purpose AI Code of Practice: Compliance Obligations Begin August 2025

ISO 42001 Readiness: A 10-Step Guide to Responsible AI Governance

Aligning with ISO 42001:2023 and/or the EU Artificial Intelligence (AI) Act

The Strategic Synergy: ISO 27001 and ISO 42001 – A New Era in Governance

Clause 4 of ISO 42001: Understanding an Organization and Its Context and Why It Is Crucial to Get It Right.

Think Before You Share: The Hidden Privacy Costs of AI Convenience

The AI Readiness Gap: High Usage, Low Security

Mitigate and adapt with AICM (AI Controls Matrix)

DISC InfoSec’s earlier posts on the AI topic

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Tags: EU AI Act, Risk management

Aug 04 2025

Cyber Risk in Context: Why Boards Must See the Full Picture

Category: Cyber Strategy,Risk Assessment — disc7 @ 9:22 am

Cybersecurity is critical — but it’s not the only thing on a board’s mind. Executive leaders must make strategic decisions across the entire business, often with limited capital. So when CISOs ask for budget based solely on rising threats, without showing how it stacks up against other priorities, it becomes difficult to justify the spend.

Let’s consider a real-world scenario.

A company has $15 million in capital budget for the upcoming fiscal year. Multiple departments bring urgent and well-supported requests:

  • The CISO presents a cyber risk analysis using the FAIR model, showing that threat levels have surged due to automated AI-driven attacks. There’s now a 12% chance of a $15 million breach, and a 6% chance of a loss exceeding $35 million. A $6 million investment could reduce both the likelihood and potential impact by half.
  • The Chief Compliance Officer flags a looming regulatory risk. Without a $4 million compliance program upgrade, the company could face sanctions under new data transfer rules, risking both fines and disrupted global operations.
  • The Chief Marketing Officer argues that $5 million is needed to counter a competitor’s aggressive campaign launch. Without it, brand visibility may drop significantly, leading to an estimated $25 million decline in annual revenue.
  • The Strategy Lead proposes a $5 million acquisition of a startup with a product that complements their core offering. Early analysis projects a 30% return on investment within the first 12 months.
  • The Head of Workplace Safety requests $3 million to modernize outdated safety equipment and procedures. Incident reports are rising, and the potential cost of a serious injury — not to mention reputational damage — could be far greater.
  • The CIO outlines a $4 million plan to implement AI across customer service and logistics. The projected first-year impact: $2 million in savings and $6 million in additional revenue.

Each proposal has merit. But only $15 million is available. Should cybersecurity receive funding without evaluating how it compares to these other strategic needs?

Absolutely not.

Boards don’t decide based on fear — they decide based on business value. For cybersecurity to compete, it must be communicated in business terms: risk-adjusted ROI, financial exposure, and alignment with strategic goals. The days of saying “this is a critical vulnerability” without quantifying business impact are over.

Cyber risk is business risk — and it must be treated that way.

So here’s the real question: Are you making the case for cybersecurity in isolation? Or are you enabling informed, enterprise-level decisions?

How to be a Chief Risk Officer: A handbook for the modern CRO

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Tags: Boards Must See the Full Picture, CRO

Aug 04 2025

Stop Evaluating Cyber Risk in a Vacuum: Align Security with Business Objectives

Category: Risk Assessment — disc7 @ 8:01 am

Despite years of progress in the cybersecurity industry, one flawed mindset still lingers: assessing cyber risk as if it exists in a silo. Far too many organizations continue to focus on the “risk to information assets” — systems, servers, and data — while ignoring the larger picture: how those risks threaten the achievement of strategic business objectives.

This technical-first approach is understandable, especially for teams deeply embedded in IT or security operations. After all, threats like ransomware, phishing, and vulnerabilities in software systems are concrete, measurable, and urgent. But when cyber risk is framed solely in terms of what systems are vulnerable or which data might be exposed, the conversation never leaves the server room. It doesn’t reach the boardroom — or if it does, it’s lost in translation.

Why the Disconnect Matters

Business leaders don’t make decisions based on firewalls or patch levels. They prioritize growth, revenue, brand trust, customer retention, and regulatory compliance. If cyber risk isn’t explicitly tied to those business outcomes, it’s deprioritized — not because leadership doesn’t care, but because it hasn’t been made relevant.

Consider two ways of reporting the same issue:

  • Traditional framing: “Critical vulnerability in our ERP system could lead to data loss.”
  • Business-aligned framing: “If exploited, this vulnerability could halt our ability to process $8M in monthly sales orders, delaying shipments and damaging customer relationships during peak season.”

Which one gets budget approved faster?

The Real Risk Is to Business Continuity and Competitive Position

Data is an asset, yes — but only because it powers business functions. A compromise isn’t just a “security incident,” it’s a disruption to revenue streams, operational continuity, or brand reputation. If a phishing attack leads to credential theft, the real risk isn’t “loss of credentials” — it’s potential wire fraud, regulatory penalties, or a hit to investor confidence.

To manage cyber risk effectively, organizations must shift from asking “What’s the risk to this system?” to “What’s the risk to our ability to execute this critical business process?”

What Needs to Change?

  1. Map technical risks to business outcomes.
    Every asset, system, and data flow should be tied to a business function. Don’t just classify systems by “sensitivity level”; classify them by their impact on revenue, operations, or customer experience.
  2. Involve finance and operations early.
    Risk quantification must include input from finance, not just IT. If you want to talk about “impact,” use language CFOs understand: financial exposure, downtime cost, productivity loss, and potential liabilities.
  3. Use scenarios, not scores.
    Risk scores (like CVSS) are useful for prioritizing technical work, but they don’t capture business context. A CVSS 9.8 on a dev server may matter less than a CVSS 5 on a production payment system. Scenario-based risk assessments, tailored to your business, provide more actionable insights.
  4. Educate your board with what matters to them.
    Boards don’t need to understand encryption algorithms — they need to understand if a cyber risk could delay a product launch, spark a PR crisis, or violate a regulation that leads to fines.

The Bottom Line

Treating cyber risk as separate from business risk is not just outdated — it’s dangerous. In today’s digital economy, the two are inseparable. The organizations that thrive will be those that break down the silos between IT and the business, and assess cyber threats through the lens of what truly matters: achieving strategic objectives.

Your firewall isn’t just protecting data. It’s protecting the future of your business.

The Complete Guide to Business Risk Management

Secure Your Business. Simplify Compliance. Gain Peace of Mind

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Tags: Cyber risk, cyber risk quantification, with Business Objectives

Jul 22 2025

Understanding the EU AI Act: A Risk-Based Framework for Trustworthy AI – Implications for U.S. Organizations

Category: AI,Risk Assessment — disc7 @ 10:49 am

EU AI Act: A Risk-Based Approach to Managing AI Compliance

1. Objective and Scope
The EU AI Act aims to ensure that AI systems placed on the EU market are safe, respect fundamental rights, and encourage trustworthy innovation. It applies to both public and private actors who provide or use AI in the EU, regardless of whether they are based in the EU or not. The Act follows a risk-based approach, categorizing AI systems into four levels of risk: unacceptable, high, limited, and minimal.

2. Prohibited AI Practices
Certain AI applications are completely banned because they violate fundamental rights. These include systems that manipulate human behavior, exploit vulnerabilities of specific groups, enable social scoring by governments, or use real-time remote biometric identification in public spaces (with narrow exceptions such as law enforcement).

3. High-Risk AI Systems
AI systems used in critical sectors—like biometric identification, infrastructure, education, employment, access to public services, and law enforcement—are considered high-risk. These systems must undergo strict compliance procedures, including risk assessments, data governance checks, documentation, human oversight, and post-market monitoring.

4. Obligations for High-Risk AI Providers
Providers of high-risk AI must implement and document a quality management system, ensure datasets are relevant and free from bias, establish transparency and traceability mechanisms, and maintain detailed technical documentation. They must also register their AI system in a publicly accessible EU database before placing it on the market.

5. Roles and Responsibilities
The Act defines clear responsibilities for all actors in the AI supply chain—providers, importers, distributors, and deployers. Each has specific obligations based on their role. For instance, deployers of high-risk AI systems must ensure proper human oversight and inform individuals impacted by the system.

6. Limited and Minimal Risk AI
For AI systems with limited risk (like chatbots), providers must meet transparency requirements, such as informing users that they are interacting with AI. Minimal-risk systems (e.g., spam filters or AI in video games) are largely unregulated, though developers are encouraged to voluntarily follow codes of conduct and ethical guidelines.

7. General Purpose AI Models
General-purpose AI (GPAI) models, including foundation models like GPT, are subject to specific transparency obligations. Developers must provide technical documentation, summaries of training data, and usage instructions. Advanced GPAIs with systemic risks face additional requirements, including risk management and cybersecurity obligations.

8. Enforcement, Governance, and Sanctions
Each Member State will designate a national supervisory authority, while the EU will establish a European AI Office to oversee coordination and enforcement. Non-compliance can result in fines of up to €35 million or 7% of annual global turnover, depending on the severity of the violation.

9. Timeline and Compliance Strategy
The AI Act will come into effect in stages after formal adoption. Prohibited practices will be banned within six months; GPAI rules will apply after 12 months; and the core high-risk system obligations will become enforceable in 24 months. Businesses should begin gap assessments, build internal governance structures, and prepare for conformity assessments to ensure timely compliance.

EU AI ACT 2024

EU publishes General-Purpose AI Code of Practice: Compliance Obligations Begin August 2025

For U.S. organizations operating in or targeting the EU market, preparation involves mapping AI use cases against the Act’s risk tiers, enhancing risk management practices, and implementing robust documentation and accountability frameworks. By aligning with the EU AI Act’s principles, U.S. firms can not only ensure compliance but also demonstrate leadership in trustworthy AI on a global scale.

A compliance readiness checklist for U.S. organizations preparing for the EU AI Act:

👉 EU AI Act Compliance Checklist for U.S. Organizations

The EU Artificial Intelligence (AI) Act: A Commentary

What are the benefits of AI certification Like AICP by EXIN

The New Role of the Chief Artificial Intelligence Risk Officer (CAIRO)

InfoSec services | InfoSec books | Follow our blog | DISC llc is listed on The vCISO Directory | ISO 27k Chat bot | Comprehensive vCISO Services | ISMS Services | Security Risk Assessment Services

Tags: EU AI Act, Framework for Trustworthy

Jul 08 2025

Stop Managing Risks—Start Enabling Better Decisions

Category: Information Security,Risk Assessment,Security Risk Assessment — disc7 @ 2:22 pm

Most risk assessments fail to support real decisions. Learn how to turn risk management into a strategic advantage, not just a compliance task.

1.
In many organizations, risk assessments are treated as checklist exercises—completed to meet compliance requirements, not to drive action. They often lack relevance to current business decisions and serve more as formalities than strategic tools.

2.
When no real decision is being considered, a risk assessment becomes little more than paperwork. It consumes time, effort, and even credibility without providing meaningful value to the business. In such cases, risk teams risk becoming disconnected from the core priorities of the organization.

3.
This disconnect is reflected in recent research. According to PwC’s 2023 Global Risk Survey, while 73% of executives agree that risk management is critical to strategic decisions, only 22% believe it is effectively influencing those decisions. Gartner’s 2023 survey also found that over half of organizations see risk functions as too siloed to support enterprise-wide decisions.

4.
Even more concerning is the finding from NC State’s ERM Initiative: over 60% of risk assessments are performed without a clear decision-making context. This means that most risk work happens in a vacuum, far removed from the actual choices business leaders are making.

5.
Risk management should not be a separate track from business—it should be a core driver of decision-making under uncertainty. Its value lies in making trade-offs explicit, identifying blind spots, and empowering leaders to act with clarity and confidence.

6.
Before launching into a new risk register update or a 100 plus page report, organizations should ask a sharper business related question: What business decision are we trying to support with this assessment? When risk is framed this way, it becomes a strategic advantage, not an overhead cost.

7.
By shifting focus from managing risks to enabling better decisions, risk management becomes a force multiplier for strategy, innovation, and resilience. It helps business leaders act not just with caution—but with confidence.

Conclusion
A well-executed risk assessment helps businesses prioritize what matters, allocate resources wisely, and protect value while pursuing growth. To be effective, risk assessments must be decision-driven, timely, and integrated into business conversations. Don’t treat them as routine reports—use them as decision tools that connect uncertainty to action.

Fundamentals of Risk Management: Understanding, Evaluating and Implementing Effective Enterprise Risk Management

Secure Your Business. Simplify Compliance. Gain Peace of Mind

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Tags: Business Enabler, Enabling Better Decisions

Jun 30 2025

Why AI agents could be the next insider threat

Category: AI,Risk Assessment,Security Risk Assessment — disc7 @ 5:11 pm

1. Invisible, Over‑Privileged Agents
Help Net Security highlights how AI agents—autonomous software acting on behalf of users—are increasingly embedded in enterprise systems without proper oversight. They often receive excessive permissions, operate unnoticed, and remain outside traditional identity governance controls

2. Critical Risks in Healthcare
Arun Shrestha from BeyondID emphasizes the healthcare sector’s vulnerability. AI agents there handle Protected Health Information (PHI) and system access, increasing risks to patient privacy, safety, and regulatory compliance (e.g., HIPAA)

3. Identity Blind Spots
Research shows many firms lack clarity about which AI agents have access to critical systems. AI agents can impersonate users or take unauthorized actions—yet these “non‑human identities” are seldom treated as significant security threats.

4. Growing Threat from Impersonation
TechRepublic’s data indicates only roughly 30% of US organizations map AI agent access, and 37% express concern over agents posing as users. In healthcare, up to 61% report experiencing attacks involving AI agents

5. Five Mitigation Steps
Shrestha outlines five key defenses: (1) inventory AI agents, (2) enforce least privilege, (3) monitor their actions, (4) integrate them into identity governance processes, and (5) establish human oversight—ensuring no agent operates unchecked.

6. Broader Context
This video builds on earlier insights about securing agentic AI, such as monitoring, prompt‑injection protection, and privilege scoping. The core call: treat AI agents like any high-risk insider.

📝 Feedback (7th paragraph):
This adeptly brings attention to a critical and often overlooked risk: AI agents as non‑human insiders. The healthcare case strengthens the urgency, yet adding quantitative data—such as what percentage of enterprises currently enforce least privilege on agents—would provide stronger impact. Explaining how to align these steps with existing frameworks like ISO 27001 or NIST would add practical value. Overall, it raises awareness and offers actionable controls, but would benefit from deeper technical guidance and benchmarks to empower concrete implementation.

Source Help Net security: Why AI agents could be the next insider threat

Agentic AI: Navigating Risks and Security Challenges

Artificial Intelligence: The Next Battlefield in Cybersecurity

AI and The Future of Cybersecurity: Navigating the New Digital Battlefield

“Whether you’re a technology professional, policymaker, academic, or simply a curious reader, this book will arm you with the knowledge to navigate the complex intersection of AI, security, and society.”

AI Governance Is a Boardroom Imperative—The SEC Just Raised the Stakes on AI Hype

How AI Is Transforming the Cybersecurity Leadership Playbook

Previous AI posts

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AI in the Workplace: Replacing Tasks, Not People

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Interpretation of Ethical AI Deployment under the EU AI Act

AI Governance: Applying AI Policy and Ethics through Principles and Assessments

ISO/IEC 42001:2023, First Edition: Information technology – Artificial intelligence – Management system

ISO 42001 Artificial Intelligence Management Systems (AIMS) Implementation Guide: AIMS Framework | AI Security Standards

Businesses leveraging AI should prepare now for a future of increasing regulation.

Digital Ethics in the Age of AI 

DISC InfoSec’s earlier posts on the AI topic

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Tags: AI Agents, Insider Threat

Jun 28 2025

Vineyard and Wineries may be at Risk

Category: cyber security,Information Security,M&A,Risk Assessment — disc7 @ 2:58 pm

1. Vineyard and Wineries are increasingly at Risk

Many winery owners and executives—particularly those operating small to mid-sized, family-run estates—underestimate their exposure to cyber threats. Yet with the rise of direct-to-consumer channels like POS systems, wine clubs, and ecommerce platforms, these businesses now collect and store sensitive customer and employee data, including payment details, birthdates, and Social Security numbers. This makes them attractive targets for cybercriminals.

The Emerging Threat of Cyber-Physical Attacks

Wineries increasingly rely on automated production systems and IoT sensors to manage fermentation, temperature control, and chemical dosing. These digital tools can be manipulated by hackers to:

  • Disrupt production by altering temperature or chemical settings.
  • Spoil inventory through false sensor data or remote tampering.
  • Undermine trust by threatening product safety and quality.

A Cautionary Tale

While there are no public reports of terrorist attacks on the wine industry’s supply chain, the 1985 Austrian wine scandal is a stark reminder of what can happen when integrity is compromised. In that case, wine was adulterated with antifreeze (diethylene glycol) to manipulate taste—resulting in global recalls, destroyed reputations, and public health risks.

The lesson is clear: cyber and physical safety in the winery business are now deeply intertwined.

2. Why Vineyards and Wineries Are at Risk

  • High-value data: Personal and financial details stored in club databases or POS systems can be exploited and sold on the dark web.
  • Legacy systems & limited expertise: Many wineries rely on outdated IT infrastructure and lack in-house cybersecurity staff.
  • Regulatory complexity: Compliance with data privacy regulations like CCPA/CPRA adds to the burden, and gaps can lead to penalties.
  • Charming targets: Boutique and estate brands, which often emphasize hospitality and trust, can be unexpectedly appealing to attackers seeking vulnerable entry points.

3. Why It Matters

  • Reputation risk: A breach can shatter consumer trust—especially among affluent wine club customers who expect discretion and reliability.
  • Financial & legal exposure: Incidents may invite steep fines, ransomware costs, and lawsuits under privacy laws.
  • Operational disruption: Outages or ransomware can cripple point-of-sale and club systems, causing revenue loss and logistical headaches.
  • Competitive advantage: Secure operations can boost customer confidence, support audit and M&A readiness, and unlock better insurance or investor opportunities.

4. What You Can Do About It

  • Risk & compliance assessment: Discover vulnerabilities in systems, Wi‑Fi, and employee habits. Score your risk with a 10-page report for stakeholders.
  • Privacy compliance support: Navigate CCPA/CPRA (and PCI/GDPR as needed) to keep your winery legally sound.
  • Defense against phishing & ransomware: Conduct employee training, simulations, and implement defenses.
  • Security maturity roadmap: Prioritize improvements—like endpoint protection, firewalls, 2FA setups—and phase them according to your brand and budget.
  • Fractional vCISO support: Access quarterly executive consultations to align compliance and tech strategy without hiring full-time experts.
  • Optional services: Pen testing, PCI-DSS support, vendor reviews, and business continuity planning for deeper security.

DISC WinerySecure™ offers a tailored roadmap to safeguard your winery:

You don’t need to face this alone. We offer Free checklist + consultation.

DISC InfoSec
Virtual CISO | Wine Industry Security & Compliance

 Info@deurainfosec.com | https://www.deurainfosec.com/ | (707) 998-5164 | Contact us

Investing in a proactive security strategy isn’t just about avoiding threats—it’s about protecting your brand, securing compliance, and empowering growth. Contact DISC WinerySecure™ today for a free consultation.

In addition to winery protection, DISC specializes in securing data during mergers and acquisitions.

DISC WinerySecure™: Cybersecurity & Compliance Services for California Wineries


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Next Steps: Let us prepare a customized scorecard or walk you through a free 15-minute discovery call.

Contact: info@discinfosec.com | www.discinfosec.com

Tags: Vineyard, Wineries at Risk

Apr 29 2025

ISO 27001:2022 Risk Management Steps

Category: Information Security,ISO 27k,Risk Assessment,Security Risk Assessment — disc7 @ 11:08 am

​The document “Step-by-Step Explanation of ISO 27001/ISO 27005 Risk Management” by Advisera Expert Solutions offers a comprehensive guide to implementing effective information security risk management in alignment with ISO 27001 and ISO 27005 standards. It aims to demystify the process, providing practical steps for organizations to identify, assess, and treat information security risks efficiently.​ Advisera

1. Introduction to Risk Management

Risk management is essential for organizations to maintain competitiveness and achieve objectives. It involves identifying, evaluating, and treating risks, particularly those related to information security. The document emphasizes that while risk management can be complex, it doesn’t have to be unnecessarily complicated. By adopting structured methodologies, organizations can manage risks effectively without excessive complexity.​

2. Six Basic Steps of ISO 27001 Risk Assessment and Treatment

The risk management process is broken down into six fundamental steps:​

  1. Risk Assessment Methodology: Establishing consistent rules for conducting risk assessments across the organization.
  2. Risk Assessment Implementation: Identifying potential problems, analyzing, and evaluating risks to determine which need treatment.
  3. Risk Treatment Implementation: Developing cost-effective strategies to mitigate identified risks.
  4. ISMS Risk Assessment Report: Documenting all activities undertaken during the risk assessment process.
  5. Statement of Applicability: Summarizing the results of risk treatment and serving as a key document for auditors.
  6. Risk Treatment Plan: Outlining the implementation of controls, including responsibilities, timelines, and budgets.​

Management approval is crucial for the Risk Treatment Plan to ensure the necessary resources and commitment for implementation.​

3. Crafting the Risk Assessment Methodology

Developing a clear risk assessment methodology is vital. This involves defining how risks will be identified, analyzed, and evaluated. The methodology should ensure consistency and objectivity, allowing for repeatable and comparable assessments. It should also align with the organization’s context, considering its specific needs and risk appetite.​

4. Identifying Risks: Assets, Threats, and Vulnerabilities

Effective risk identification requires understanding the organization’s assets, potential threats, and vulnerabilities. This step involves creating an inventory of information assets and analyzing how they could be compromised. By mapping threats and vulnerabilities to assets, organizations can pinpoint specific risks that need to be addressed.​

5. Assessing Consequences and Likelihood

Once risks are identified, assessing their potential impact and the likelihood of occurrence is essential. This evaluation helps prioritize risks based on their severity and probability, guiding the organization in focusing its resources on the most significant threats. Both qualitative and quantitative methods can be employed to assess risks effectively.​

6. Implementing Risk Treatment Strategies

After assessing risks, organizations must decide on appropriate treatment strategies. Options include avoiding, transferring, mitigating, or accepting risks. Selecting suitable controls from ISO 27001 Annex A and integrating them into the Risk Treatment Plan ensures that identified risks are managed appropriately. The plan should detail the implementation process, including responsible parties and timelines.​

7. Importance of Documentation and Continuous Improvement

Documentation plays a critical role in the risk management process. The ISMS Risk Assessment Report and Statement of Applicability provide evidence of the organization’s risk management activities and decisions. These documents are essential for audits and ongoing monitoring. Furthermore, risk management should be a continuous process, with regular reviews and updates to adapt to changing threats and organizational contexts.​

By following these structured steps, organizations can establish a robust risk management framework that aligns with ISO 27001 and ISO 27005 standards, enhancing their information security posture and resilience.

Information Security Risk Management for ISO 27001/ISO 27002

How to Continuously Enhance Your ISO 27001 ISMS (Clause 10 Explained)

Continual improvement doesn’t necessarily entail significant expenses. Many enhancements can be achieved through regular internal audits, management reviews, and staff engagement. By fostering a culture of continuous improvement, organizations can maintain an ISMS that effectively addresses current and emerging information security risks, ensuring resilience and compliance with ISO 27001 standards.

ISO 27001 Compliance and Certification

ISMS and ISO 27k training

Security Risk Assessment and ISO 27001 Gap Assessment

At DISC InfoSec, we streamline the entire process—guiding you confidently through complex frameworks such as ISO 27001, and SOC 2.

Here’s how we help:

  • Conduct gap assessments to identify compliance challenges and control maturity
  • Deliver straightforward, practical steps for remediation with assigned responsibility
  • Ensure ongoing guidance to support continued compliance with standard
  • Confirm your security posture through risk assessments and penetration testing

Let’s set up a quick call to explore how we can make your cybersecurity compliance process easier.

Feel free to get in touch if you have any questions about the ISO 27001 Internal audit or certification process.

Successfully completing your ISO 27001 audit confirms that your Information Security Management System (ISMS) meets the required standards and assures your customers of your commitment to security.

Get in touch with us to begin your ISO 27001 audit today.

ISO 27001:2022 Annex A Controls Explained

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Many companies perceive ISO 27001 as just another compliance expense?

ISO 27001: Guide & key Ingredients for Certification

DISC InfoSec Previous posts on ISO27k

ISO certification training courses.

ISMS and ISO 27k training

Difference Between Internal and External Audit

InfoSec services | InfoSec books | Follow our blog | DISC llc is listed on The vCISO Directory | ISO 27k Chat bot | Comprehensive vCISO Services | ISMS Services | Security Risk Assessment Services

Tags: iso 27001, iso 27005, Risk Assessment, Risk management

Mar 26 2025

How to Begin with Cybersecurity Risk Management

Category: Information Security,Risk Assessment,Security program,Security Risk Assessment — disc7 @ 3:13 pm

Cyber security risk management is a critical aspect of data security, underpinning various frameworks and regulations such as GDPR, NIST CSF, and ISO 27001. The process begins by establishing a common vocabulary to ensure clear communication across the organization. Risk in this context typically refers to potential negative outcomes for the organization, with the goal of identifying and mitigating these risks while considering time and cost implications.

When assessing risks, two key factors are considered: likelihood and impact. These need to be clearly defined and quantified to ensure consistent interpretation throughout the organization. Risk levels are often categorized as low, medium, or high, with corresponding color-coding for easy visualization. A low risk might be something the organization can tolerate, while a high risk could have catastrophic consequences requiring immediate action.

Impact categories can include financial, strategic, customer-related, employee-related, regulatory, operational, and reputational aspects. Not all categories apply to every organization, and some may overlap. Defining the values for these categories is crucial for establishing a common language and meeting ISO 27001 requirements for consistent risk assessments.

Financial impact is typically the easiest to define, using currency figures or percentages of annual turnover. Non-financial impacts, such as operational or reputational, require more nuanced definitions. For example, operational impact might be measured by the duration of business disruption, while reputational impact could be assessed based on the level of media interest.

Likelihood categories are usually defined on a scale from “very unlikely” to “very likely,” with clear descriptions of what each category means. These can be based on expected frequency of occurrence, such as annually, monthly, weekly, or daily. Estimating likelihood can be based on past experiences within the organization or industry-wide occurrences.

Using multiple impact categories is important because security is everyone’s responsibility, and different departments may need to assess impact in different terms. For instance, a chemical manufacturer might need to define impact levels in terms of employee health and safety, while other departments might focus on financial or operational impacts.

A risk heat map, which combines likelihood and impact levels, is a useful tool for visualizing risk severity. The highest risk area (typically colored red) represents what would be catastrophic for the organization, regardless of the specific impact category. This approach allows for a comprehensive view of risks across different aspects of the business, enabling more effective risk management strategies.

DISC InfoSec offer free initial high level assessment – Based on your needs DISC InfoSec offer ongoing compliance management or vCISO retainer.

The best approach for SMBs to start the cybersecurity risk management process involves the following steps:

Understand Your Risks:

  • Conduct a basic risk assessment to identify critical assets, potential threats, and vulnerabilities.
  • Prioritize risks based on their potential impact and likelihood.

Set Clear Goals:

  • Define your cybersecurity objectives, such as protecting customer data, complying with regulations, or avoiding downtime.

Develop a Security Policy:

  • Create a simple, easy-to-follow cybersecurity policy that outlines acceptable use, password management, and data handling practices.

Start with the Basics:

  • Implement basic cybersecurity measures like using firewalls, antivirus software, and regular system updates.
  • Use strong passwords and enable multi-factor authentication (MFA).

Train Your Employees:

  • Provide ongoing security awareness training to help employees recognize phishing, social engineering, and other threats.

Back Up Your Data:

  • Regularly back up critical data and store it in a secure, offsite location.
  • Test your backup and recovery process to ensure it works effectively.

Monitor and Respond:

  • Set up basic monitoring to detect suspicious activity (e.g., failed login attempts).
  • Establish an incident response plan to know what to do in case of an attack.

Leverage External Resources:

  • Work with a trusted Managed Security Service Provider (MSSP) or consultant to cover any expertise gaps.
  • Consider using frameworks like NIST Cybersecurity Framework (CSF) or CIS Controls for guidance.

Start Small and Scale Up:

  • Focus on quick wins that provide maximum risk reduction with minimal effort.
  • Gradually invest in more advanced tools and processes as your cybersecurity maturity grows.

Regularly Review and Update:

  • Reassess risks, policies, and controls periodically to stay ahead of evolving threats.

This structured approach helps SMBs build a solid foundation without overwhelming resources or budgets.

Cybersecurity Risk Management for Small Businesses

Building a Cyber Risk Management Program: Evolving Security for the Digital Age

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Tags: Building a Cyber Risk Management Program, Cybersecurity Risk Management

Mar 26 2025

You can’t eliminate risk entirely, but you can minimize it

Category: Information Security,Risk Assessment,Security Incident,Security Risk Assessment — disc7 @ 10:03 am

You can’t eliminate risk entirely, but you can minimize it. If a cyberattack occurs, here are three key steps to take:

  1. Plan Ahead:
    Create a detailed incident response plan now, involving all key departments (e.g., technical, legal, financial, marketing). Practice it through tabletop exercises to prepare for unexpected scenarios. The better your preparation, the less chaos you’ll face during an attack.
  2. Contact Your Cyber Insurance Company:
    Reach out to your cyber insurance provider immediately. They can coordinate response teams, provide legal and regulatory support, handle public relations, negotiate ransoms, assist with technical recovery, and help strengthen security post-incident. Follow their guidance to avoid unnecessary expenses.
  3. Return to Normal Operations:
    Once the active threat is contained, declare the incident over and shift your team back to regular duties. Fix vulnerabilities and train staff but avoid staying in “response mode” indefinitely, as it can lead to burnout, distraction, and reduced productivity.

Preparation and thoughtful responses are key to minimizing damage and ensuring a smoother recovery from cyber incidents.

Additional steps to help minimize information security risks:

1. Conduct Regular Risk Assessments

  • Identify vulnerabilities in your systems, applications, and processes.
  • Prioritize risks based on their likelihood and potential impact.
  • Address gaps with appropriate controls or mitigations.

2. Implement Strong Access Controls

  • Use multi-factor authentication (MFA) for all critical systems and applications.
  • Follow the principle of least privilege (grant access only to those who truly need it).
  • Regularly review and revoke unused or outdated access permissions.

3. Keep Systems and Software Up-to-Date

  • Patch operating systems, software, and firmware as soon as updates are released.
  • Use automated tools to manage and deploy patches consistently.

4. Train Employees on Security Best Practices

  • Conduct regular security awareness training, covering topics like phishing, password hygiene, and recognizing suspicious activity.
  • Simulate phishing attacks to test and improve employee vigilance.

5. Use Endpoint Detection and Response (EDR) Solutions

  • Deploy advanced tools to monitor, detect, and respond to threats on all devices.
  • Set up alerts for abnormal behavior or unauthorized access attempts.

6. Encrypt Sensitive Data

  • Use strong encryption protocols for data at rest and in transit.
  • Ensure proper key management practices are followed.

7. Establish Network Segmentation

  • Separate critical systems and sensitive data from less critical networks.
  • Limit lateral movement in case of a breach.

8. Implement Robust Backup Strategies

  • Maintain regular, secure backups of all critical data.
  • Store backups offline or in isolated environments to protect against ransomware.
  • Test recovery processes to ensure backups are functional and up-to-date.

9. Monitor Systems Continuously

  • Use Security Information and Event Management (SIEM) tools for real-time monitoring and alerts.
  • Proactively look for signs of intrusion or anomalies.

10. Develop an Incident Reporting Culture

  • Encourage employees to report security issues or suspicious activities immediately.
  • Avoid a blame culture so employees feel safe coming forward.

11. Engage in Threat Intelligence Sharing

  • Join industry groups or forums to stay informed about new threats and vulnerabilities.
  • Leverage shared intelligence to strengthen your defenses.

12. Test Your Defenses Regularly

  • Conduct regular penetration testing to identify and fix exploitable weaknesses.
  • Perform red team exercises to simulate real-world attacks and refine your response capabilities.

By integrating these steps into your cybersecurity strategy, you’ll strengthen your defenses and reduce the likelihood of an incident.

Feel free to reach out if you have any additional questions or feedback.

DISC InfoSec offer free initial high level assessment – Based on your needs DISC InfoSec offer ongoing compliance management or vCISO retainer.

The #1 Risk to Small Businesses: …And How to Minimize it

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Tags: eliminate risk, minimize risk

Mar 19 2025

ISO 27001 Risk Assessment Process – Summary

Category: ISO 27k,Risk Assessment,Security Risk Assessment — disc7 @ 8:51 am

The summary covers information security risk assessment, leveraging ISO 27001 for compliance and competitive advantage.

ISO 27001 Risk Management

  1. Risk Assessment Process
    • Identify assets and analyze risks.
    • Assign risk value and assess controls.
    • Implement monitoring, review, and risk mitigation strategies.
  2. Risk Concepts
    • Asset-Based vs. Scenario-Based Risks: Evaluating risk based on critical assets and potential attack scenarios.
    • Threats & Vulnerabilities: Identifying security weaknesses and potential risks (e.g., unauthorized access, data breaches, human error).
  3. Risk Impact & Likelihood
    • Risks are measured based on financial, operational, reputational, and compliance impacts.
    • Likelihood is classified from Highly Unlikely to Highly Likely based on past occurrences.
  4. Risk Treatment Options
    • Tolerate (Accept): Accepting the risk if the cost of mitigation is higher than the impact.
    • Treat (Mitigate): Reducing the risk by implementing controls.
    • Transfer (Share): Outsourcing risk through insurance or third-party agreements.
    • Terminate (Avoid): Eliminating the source of risk.

Risk assessment process details:

The risk assessment process follows a structured approach to identifying, analyzing, and mitigating security risks. The key steps include:

  1. Risk Identification
    • Identify information assets (e.g., customer data, financial systems, hardware).
    • Determine potential threats (e.g., cyberattacks, insider threats, physical damage).
    • Identify vulnerabilities (e.g., weak access controls, outdated software, lack of employee training).
  2. Risk Analysis & Valuation
    • Assess the likelihood of a threat exploiting a vulnerability (rated from Highly Unlikely to Highly Likely).
    • Evaluate the impact on financial, operational, reputational, and compliance aspects (from Minimal to Catastrophic).
    • Calculate the risk level based on the combination of likelihood and impact.
  3. Risk Mitigation & Decision Making
    • Assign a risk owner responsible for managing each identified risk.
    • Select appropriate controls (e.g., firewalls, encryption, staff training).
    • Compute the residual risk (risk left after implementing controls).
    • Decide on the risk treatment approach (Accept, Mitigate, Transfer, or Avoid).
  4. Risk Monitoring & Review
    • Establish a reporting frequency to reassess risks periodically.
    • Continuously monitor changes in the threat landscape and update controls as needed.
    • Communicate risk status and treatment effectiveness to stakeholders.

This structured approach ensures organizations can proactively manage risks, comply with regulations, and strengthen cybersecurity defenses.

DISC InfoSec offer free initial high level assessment – Based on your needs DISC InfoSec offer ongoing compliance management or vCISO retainer.

Information Security Risk Management for ISO 27001/ISO 27002

Is a Risk Assessment required to justify the inclusion of Annex A controls in the Statement of Applicability?

Many companies perceive ISO 27001 as just another compliance expense?

ISO 27001: Guide & key Ingredients for Certification

An Overview of ISO/IEC 27001:2022 Annex A Security Controls

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Mar 07 2025

Is a Risk Assessment required to justify the inclusion of Annex A controls in the Statement of Applicability?

Category: ISO 27k,Risk Assessment,Security controls,Security Risk Assessment — disc7 @ 6:59 am

“The SOA can easily be produced by examining the risk assessment to identify the necessary controls and risk treatment plan to identify those that are planned to be implemented. Only controls identified in the risk assessment can be included in the SOA. Controls cannot be added to the SOA independent of the risk assessment. There should be consistency between the controls necessary to realize selected risk treatment options and the SOA. The SOA can state that the justification for the inclusion of a control is the same for all controls and that they have been identified in the risk assessment as necessary to treat one or more risks to an acceptable level. No further justification for the inclusion of a control is needed for any of the controls.”

This paragraph from ISO 27005 explains the relationship between the Statement of Applicability (SoA) and the risk assessment process in an ISO 27001-based Information Security Management System (ISMS). Here’s a breakdown of the key points:

  1. SoA Derivation from Risk Assessment
    • The SoA must be based on the risk assessment and risk treatment plan.
    • It should only include controls that were identified as necessary during the risk assessment.
    • Organizations cannot arbitrarily add controls to the SoA without a corresponding risk justification.
  2. Consistency with Risk Treatment Plan
    • The SoA must align with the selected risk treatment options.
    • This ensures that the controls listed in the SoA effectively address the identified risks.
  3. Justification for Controls
    • The SoA can state that all controls were chosen because they are necessary for risk treatment.
    • No separate or additional justification is needed for each individual control beyond its necessity in treating risks.

Why This Matters:

  • Ensures a risk-driven approach to control selection.
  • Prevents the arbitrary inclusion of unnecessary controls, which could lead to inefficiencies.
  • Helps in audits and compliance by clearly showing the link between risks, treatments, and controls.

Practical Example of SoA and Risk Assessment Linkage

Scenario:

A company conducts a risk assessment as part of its ISO 27001 implementation and identifies the following risk:

  • Risk: Unauthorized access to sensitive customer data due to weak authentication mechanisms.
  • Risk Level: High
  • Risk Treatment Plan: Implement multi-factor authentication (MFA) to reduce the risk to an acceptable level.

How This Affects the SoA:

  1. Control Selection:
    • The company refers to Annex A of ISO 27001 and identifies Control A.9.4.1 (Use of Secure Authentication Mechanisms) as necessary to mitigate the risk.
    • This control is added to the SoA because the risk assessment identified it as necessary.
  2. Justification in the SoA:
    • The SoA will list A.9.4.1 – Secure Authentication Mechanisms as an included control.
    • The justification can be:
      “This control has been identified as necessary in the risk assessment to mitigate the risk of unauthorized access to customer data.”
    • No additional justification is needed because the link to the risk assessment is sufficient.
  3. What Cannot Be Done:
    • The company cannot arbitrarily add a control, such as A.14.2.9 (Protection of Test Data), unless it was identified as necessary in the risk assessment.
    • Adding controls without risk justification would violate ISO 27005’s requirement for consistency.

Key Takeaways:

  • Every control in the SoA must be traceable to a risk.
  • The SoA cannot contain controls that were not justified in the risk assessment.
  • Justification for controls can be standardized, reducing documentation overhead.

This approach ensures that the ISMS remains risk-based, justifiable, and auditable.

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Nov 25 2024

Adding Value with Adding Value with Risk-Based Information Security

Category: ISO 27k,NIST CSF,Risk Assessment,Security Risk Assessment — disc7 @ 8:27 am

The article emphasizes the importance of integrating risk management and information security management systems (ISMS) for effective IT security. It recommends a risk-based approach, leveraging frameworks like ISO/IEC 27001 and NIST Cybersecurity Framework (CSF) 2.0, to guide decisions that counteract risks while aligning with business objectives. Combining these methodologies enhances control accuracy and ensures that organizational assets critical to business goals are appropriately classified and protected.

An enterprise risk management system (ERMS) bridges IT operations and business processes by defining the business value of organizational assets. This alignment enables ISMS to identify and safeguard IT assets vital to achieving organizational objectives. Developing a registry of assets through ERMS avoids redundancies and ensures ISMS efforts are business-driven, not purely technological.

The NIST CSF 2.0 introduces a “govern” function, improving governance, priority-setting, and alignment with security objectives. It integrates with frameworks like ISO 27001 using a maturity model to evaluate controls’ effectiveness and compliance. This approach ensures clarity, reduces redundancies, and provides actionable insights into improving cybersecurity risk profiles and resilience across the supply chain.

Operationally, integrating frameworks involves a centralized tool for managing controls, aligning them with risk treatment plans (RTP), and avoiding overlaps. By sharing metrics across frameworks and using maturity models, organizations can efficiently evaluate security measures and align with business goals. The article underscores the value of combining ISO 27001’s holistic ISMS with NIST CSF’s risk-focused profile to foster continual improvement in an evolving digital ecosystem.

For example, let’s consider an elementary task such as updating the risk policy. This is part of control 5.1 of ISO27001 on information security policies. It is part of the subcategory GV.PO-01 of the NIST CSF on policies for managing cybersecurity risks, but it is also present in the RTP with regard to the generic risk of failure to update company policies. The elementary control tasks are evaluated individually. Then, the results of multiple similar tasks are aggregated to obtain a control of one of the various standards, frameworks or plans that we are considering.

Best method for evaluating the effectiveness of control activities may be to adopt the Capability Maturity Model Integration (CMMI). It is a simple model for finding the level of maturity of implementation of an action with respect to the objectives set for that action. Furthermore, it is sufficiently generic to be adaptable to all evaluation environments and is perfectly linked with gap analysis. The latter is precisely the technique suitable for our evaluations – that is, by measuring the current state of maturity of implementation of the control and comparing it with the pre-established level of effectiveness, we are able to determine how much still needs to be done.

In short, the advantage of evaluating control tasks instead of the controls proposed by the frameworks is twofold.

  • The first advantage is in the very nature of the control task that corresponds to a concrete action, required by some business process, and therefore well identified in terms of role and responsibility. In other words, something is used that the company has built for its own needs and therefore knows well. This is an indicator of quality in the evaluation.
  • The second advantage is in the method of treatment of the various frameworks. Instead of building specific controls with new costs to be sustained for their management, it is preferable to identify each control of the framework for which control tasks are relevant and automatically aggregate the relative evaluations. The only burden is to define the relationship between the companys control tasks and the controls of the chosen framework, but just once.

More details and considerations on pros and cons are described in recent ISACA Journal article, “Adding Value With Risk-Based Information Security.”

Source: National Institute of Standards and Technology, The NIST Cybersecurity Framework (CSF) 2.0, USA, 2024, https://www.nist.gov/informative-references

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Nov 19 2024

Threat modeling your generative AI workload to evaluate security risk

Category: AI,Risk Assessment — disc7 @ 8:40 am

AWS emphasizes the importance of threat modeling for securing generative AI workloads, focusing on balancing risk management and business outcomes. A robust threat model is essential across the AI lifecycle stages, including design, deployment, and operations. Risks specific to generative AI, such as model poisoning and data leakage, need proactive mitigation, with organizations tailoring risk tolerance to business needs. Regular testing for vulnerabilities, like malicious prompts, ensures resilience against evolving threats.

Generative AI applications follow a structured lifecycle, from identifying business objectives to monitoring deployed models. Security considerations should be integral from the start, with measures like synthetic threat simulations during testing. For applications on AWS, leveraging its security tools, such as Amazon Bedrock and OpenSearch, helps enforce role-based access controls and prevent unauthorized data exposure.

AWS promotes building secure AI solutions on its cloud, which offers over 300 security services. Customers can utilize AWS infrastructure’s compliance and privacy frameworks while tailoring controls to organizational needs. For instance, techniques like Retrieval-Augmented Generation ensure sensitive data is redacted before interaction with foundational models, minimizing risks.

Threat modeling is described as a collaborative process involving diverse roles—business stakeholders, developers, security experts, and adversarial thinkers. Consistency in approach and alignment with development workflows (e.g., Agile) ensures scalability and integration. Using existing tools for collaboration and issue tracking reduces friction, making threat modeling a standard step akin to unit testing.

Organizations are urged to align security practices with business priorities while maintaining flexibility. Regular audits and updates to models and controls help adapt to the dynamic AI threat landscape. AWS provides reference architectures and security matrices to guide organizations in implementing these best practices efficiently.

Threat composer threat statement builder

You can write and document these possible threats to your application in the form of threat statements. Threat statements are a way to maintain consistency and conciseness when you document your threat. At AWS, we adhere to a threat grammar which follows the syntax:

A [threat source] with [prerequisites] can [threat action] which leads to [threat impact], negatively impacting [impacted assets].

This threat grammar structure helps you to maintain consistency and allows you to iteratively write useful threat statements. As shown in Figure 2, Threat Composer provides you with this structure for new threat statements and includes examples to assist you.

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Nov 05 2024

ISO 27001 clauses 6.1.2 and 6.1.3 on information security risk assessment should be relocated to clause 8

Category: ISO 27k,Risk Assessment,Security Risk Assessment — disc7 @ 9:03 am

Clause 6.1.1 is often misunderstood and frequently overlooked. It requires organizations to assess risks and opportunities specifically related to the Information Security Management System (ISMS)—focusing not on information security itself, but on the ISMS’s effectiveness. This is distinct from the information security risk assessment activities outlined in 6.1.2 and 6.1.3, which require different methods and considerations.

In practice, it’s rare for organizations to assess ISMS-specific risks and opportunities (per 6.1.1), and certification auditors seldom address this requirement.

To clarify, it’s proposed that the information security risk assessment activities (6.1.2 and 6.1.3) be moved to clause 8. This aligns with the structure of other management system standards (e.g., ISO 22301 for Business Continuity Planning). Additionally, a note similar to ISO 22301’s should be included:

“Risks in this sub clause relate to information security, while risks and opportunities related to the effectiveness of the management system are addressed in 6.1.1.”

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Nov 04 2024

The Risk Assessment Process and the tool that supports it

Category: ISO 27k,Risk Assessment,Security Risk Assessment — disc7 @ 12:00 pm

The “Risk Assessment analysis” covers key areas of risk assessment in information security:

  1. Risk Assessment Process: The core steps include identifying assets, analyzing risks, and evaluating the value and impact of each risk. This process helps determine necessary controls and treatments to mitigate or accept risks.
  2. Types of Risk:
    • Asset-Based Risk: Focuses on assessing risks to tangible assets like data or hardware.
    • Scenario-Based Risk: Evaluates hypothetical risk scenarios, such as potential data breaches.
  3. Risk Analysis:
    • Impact Analysis: Measures the financial, operational, and reputational impact of risks, assigning scores from 1 (very low) to 5 (very high).
    • Likelihood Analysis: Assesses how likely a risk event is to occur, also on a scale from 1 to 5.
  4. Risk Response Options:
    • Tolerate (accept risk),
    • Treat (mitigate risk),
    • Transfer (share risk, e.g., via insurance),
    • Terminate (avoid risk by ceasing the risky activity).
  5. Residual Risk and Risk Appetite: After treatments are applied, residual risk remains. Organizations determine their acceptable level of risk, known as risk appetite, to guide their response strategies.

These structured steps ensure consistent, repeatable risk management across information assets, aligning with standards like ISO 27001.

The Risk Assessment Process involves systematically identifying and evaluating potential risks to assets. This includes:

  • Identifying Assets: Recognizing valuable information assets, such as data or physical equipment.
  • Risk Analysis: Analyzing the potential threats and vulnerabilities related to these assets to assess the level of risk they pose.
  • Evaluating Impact and Likelihood: Measuring the potential impact of each risk and estimating how likely each risk is to occur.
  • Implementing Controls: Deciding on control measures to mitigate, transfer, accept, or avoid each risk, based on organizational risk tolerance.

To streamline this process, organizations often use risk assessment tools. These tools assist by automating data collection, calculating risk levels, and supporting decision-making on risk treatments, ultimately making the assessment more consistent, thorough, and efficient.

CyberComply makes compliance with cybersecurity requirements and data privacy laws simple and affordable.

  • Manage all your cybersecurity and data privacy obligations
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  • Get immediate visibility of critical data and key performance indicators
  • Stay ahead of regulatory changes with our scalable compliance solution
  • Reduce errors and improve completeness of risk management processes
  • Identify and treat data security risks before they become critical concerns

Reduce data security risks with agility and efficiency

  • Quickly identify and treat data security risks before they become critical concerns with the intuitive, easy-to-use risk manager tool
  • Keep track of data security compliance requirements and the security controls you have in place in conjunction with critical laws and information security frameworks
  • Demonstrate compliance with ISO 27001, the leading information security management standard, with powerful built-in reports
  • The software includes control sets from ISO 27001, ISO 27017, ISO 27018, ISO 22301, ISO 27032, NIST, CSA CCM, the PCI DSS, SOC 2, and the CPRA

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