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“90% aren’t ready for AI attacks, are you?”, with remediation guidance at the end:
1. Organizations are lagging in AI‑era security A recent Accenture report warns that while AI is rapidly reshaping business operations, around 90% of organizations remain unprepared for AI‑driven cyberattacks. Alarmingly, 63% fall into what Accenture labels the “Exposed Zone”—lacking both a defined cybersecurity strategy and critical technical safeguards.
2. Threat landscape outpacing defenses AI has increased the speed, scope, and sophistication of cyber threats far beyond what current defenses can manage. Approximately 77% of companies do not practice essential data and AI security hygiene, leaving their business models, data architectures, and cloud environments dangerously exposed.
3. Cybersecurity must be integrated into AI initiatives Paolo Dal Cin of Accenture underscores that cybersecurity can no longer be an afterthought. Growing geopolitical instability and AI‑augmented attacks demand that security be designed into AI projects from the very beginning to maintain competitiveness and customer trust.
4. AI systems need governance and protection Daniel Kendzior, Accenture’s global Data & AI Security lead, stresses the importance of formalizing security policies and maintaining real‑time oversight of AI systems. This includes ensuring secure AI development, deployment, and operational readiness to stay ahead of evolving threats.
5. Cyber readiness varies sharply across regions The report reveals stark geographic differences in cybersecurity maturity. Only 14% of North American and 11% of European organizations are deemed “Reinvention Ready,” while in Latin America and the Asia‑Pacific region, over 70% remain in the “Exposed Zone,” highlighting major readiness disparities.
6. Reinvention‑Ready firms lead in resilience and trust The top 10% of organizations—the “Reinvention Ready” group—are demonstrably more effective at defending against advanced attacks. They block threats nearly 70% more successfully, cut technical debt, improve visibility, and enhance customer trust, illustrating that maturity aligns with tangible business benefits.
Implement accountability structures and frameworks tuned to AI risks, ensuring compliance and alignment with business goals.
Incorporate security into AI design
Embed protections into every stage of AI system development, from data handling to model deployment and infrastructure configuration.
Secure and monitor AI systems continuously
Regularly test AI pipelines, enforce encryption and access controls, and proactively update threat detection capabilities.
Leverage AI defensively
Use AI to streamline security workflows—automating threat hunting, anomaly detection, and rapid response.
Conduct maturity assessments by region and function
Benchmark cybersecurity posture across different regions and business units to identify and address vulnerabilities.
Commit to education and culture change
Train staff on AI‑related risks and security best practices, and shift the organizational mindset to view cybersecurity as foundational rather than optional.
By adopting these measures, companies can climb into the “Reinvention Ready Zone,” significantly reducing their risk exposure and reinforcing trust in their AI‑enabled operations.
“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 businesses are at risk due to growing cyber threats, regulatory pressure, and ethical concerns. They often process vast amounts of sensitive data, making them prime targets for breaches and data misuse. Malicious actors can exploit AI systems through model manipulation, adversarial inputs, or unauthorized access. Additionally, lack of standardized governance and compliance frameworks exposes them to legal and reputational damage. As AI adoption accelerates, so do the risks.
AI businesses are at risk because they often handle large volumes of sensitive data, rely on complex algorithms that may be vulnerable to manipulation, and operate in a rapidly evolving regulatory landscape. Threats include data breaches, model poisoning, IP theft, bias in decision-making, and misuse of AI tools by attackers. Additionally, unclear accountability and lack of standardized AI security practices increase their exposure to legal, reputational, and operational risks.
Why it matters
It matters because the integrity, security, and trustworthiness of AI systems directly impact business reputation, customer trust, and regulatory compliance. A breach or misuse of AI can lead to financial loss, legal penalties, and harm to users. As AI becomes more embedded in critical decision-making—like healthcare, finance, and security—the risks grow more severe. Ensuring responsible and secure AI isn’t just good practice—it’s essential for long-term success and societal trust.
To reduce risks in AI businesses, we can:
Implement strong governancewith AIMS – Define clear accountability, policies, and oversight for AI development and use.
Secure data and models – Encrypt sensitive data, restrict access, and monitor for tampering or misuse.
Conduct risk assessments – Regularly evaluate threats, vulnerabilities, and compliance gaps in AI systems.
Ensure transparency and fairness – Use explainable AI and audit algorithms for bias or unintended consequences.
Stay compliant – Align with evolving regulations like GDPR, NIST AI RMF, or the EU AI Act.
Train teams – Educate employees on AI ethics, security best practices, and safe use of generative tools.
Proactive risk management builds trust, protects assets, and positions AI businesses for sustainable growth.
ISO/IEC 42001:2023 – from establishing to maintain an AI management system (AIMS)
BSI ISO 31000 is standard for any organization seeking risk management guidance
ISO/IEC 27001 and ISO/IEC 42001, both standards address risk and management systems, but with different focuses. ISO/IEC 27001 is centered on information security—protecting data confidentiality, integrity, and availability—while ISO/IEC 42001 is the first standard designed specifically for managing artificial intelligence systems responsibly. ISO/IEC 42001 includes considerations like AI-specific risks, ethical concerns, transparency, and human oversight, which are not fully addressed in ISO 27001. Organizations working with AI should not rely solely on traditional information security controls.
While ISO/IEC 27001 remains critical for securing data, ISO/IEC 42001 complements it by addressing broader governance and accountability issues unique to AI. The article suggests that companies developing or deploying AI should integrate both standards to build trust and meet growing stakeholder and regulatory expectations. Applying ISO 42001 can help demonstrate responsible AI practices, ensure explainability, and mitigate unintended consequences, positioning organizations to lead in a more regulated AI landscape.
“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.”
Several posts published recently discuss AI security and privacy, highlighting different perspectives and concerns. Here’s a summary of the most prominent themes and posts:
Emerging Concerns and Risks:
Growing Anxiety around AI Data Privacy: A recent survey found that a significant majority of Americans (91%) are concerned about social media platforms using their data to train AI models, with 69% aware of this practice.
AI-Powered Cyber Threats on the Rise: AI is increasingly being used to generate sophisticated phishing attacks and malware, making it harder to distinguish between legitimate and malicious content.
Gap between AI Adoption and Security Measures: Many organizations are quickly adopting AI but lag in implementing necessary security controls, creating a major vulnerability for data leaks and compliance issues.
Deepfakes and Impersonation Scams: The use of AI in creating realistic deepfakes is fueling a surge in impersonation scams, increasing privacy risks.
Opaque AI Models and Bias: The “black box” nature of some AI models makes it difficult to understand how they make decisions, raising concerns about potential bias and discrimination.
Regulatory Developments:
Increasing Regulatory Scrutiny: Governments worldwide are focusing on regulating AI, with the EU AI Act setting a risk-based framework and China implementing comprehensive regulations for generative AI.
Focus on Data Privacy and User Consent: New regulations emphasize data minimization, purpose limitation, explicit user consent for data collection and processing, and requirements for data deletion upon request.
Best Practices and Mitigation Strategies:
Robust Data Governance: Organizations must establish clear data governance frameworks, including data inventories, provenance tracking, and access controls.
Privacy by Design: Integrating privacy considerations from the initial stages of AI system development is crucial.
Utilizing Privacy-Preserving Techniques: Employing techniques like differential privacy, federated learning, and synthetic data generation can enhance data protection.
Continuous Monitoring and Threat Detection: Implementing tools for continuous monitoring, anomaly detection, and security audits helps identify and address potential threats.
Employee Training: Educating employees about AI-specific privacy risks and best practices is essential for building a security-conscious culture.
Specific Mentions:
NSA’s CSI Guidance: The National Security Agency (NSA) released joint guidance on AI data security, outlining best practices for organizations.
Stanford’s 2025 AI Index Report: This report highlighted a significant increase in AI-related privacy and security incidents, emphasizing the need for stronger governance frameworks.
DeepSeek AI App Risks: Experts raised concerns about the DeepSeek AI app, citing potential security and privacy vulnerabilities.
Based on current trends and recent articles, it’s evident that AI security and privacy are top-of-mind concerns for individuals, organizations, and governments alike. The focus is on implementing strong data governance, adopting privacy-preserving techniques, and adapting to evolving regulatory landscapes.
The rapid rise of AI has introduced new cyber threats, as bad actors increasingly exploit AI tools to enhance phishing, social engineering, and malware attacks. Generative AI makes it easier to craft convincing deepfakes, automate hacking tasks, and create realistic fake identities at scale. At the same time, the use of AI in security tools also raises concerns about overreliance and potential vulnerabilities in AI models themselves. As AI capabilities grow, so does the urgency for organizations to strengthen AI governance, improve employee awareness, and adapt cybersecurity strategies to meet these evolving risks.
There is a lack of comprehensive federal security and privacy regulations in the U.S., but violations of international standards often lead to substantial penalties abroadfor U.S. organizations. Penalties imposed abroad effectively become a cost of doing business for U.S. organizations.
Meta has faced dozens of fines and settlements across multiple jurisdictions, with at least a dozen significant penalties totaling tens of billions of dollars/euros cumulatively.
Artificial intelligence (AI) and large language models (LLMs) emerging as the top concern for security leaders. For the first time, AI, including tools such as LLMs, has overtaken ransomware as the most pressing issue.
“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.”
The NIST Gap Assessment Tool is a structured resource—typically a checklist, questionnaire, or software tool—used to evaluate an organization’s current cybersecurity or risk management posture against a specific NIST framework. The goal is to identify gaps between existing practices and the standards outlined by NIST, so organizations can plan and prioritize improvements.
The NIST SP 800-171 standard is primarily used by non-federal organizations—especially contractors and subcontractors—that handle Controlled Unclassified Information (CUI) on behalf of the U.S. federal government.
Specifically, it’s used by:
Defense Contractors – working with the Department of Defense (DoD).
Contractors/Subcontractors – serving other civilian federal agencies (e.g., DOE, DHS, GSA).
Universities & Research Institutions – receiving federal research grants and handling CUI.
IT Service Providers – managing federal data in cloud, software, or managed service environments.
Manufacturers & Suppliers – in the Defense Industrial Base (DIB) who process CUI in any digital or physical format.
Why it matters:
Compliance with NIST 800-171 is required under DFARS 252.204-7012 for DoD contractors and is becoming a baseline for other federal supply chains. Organizations must implement the 110 security controls outlined in NIST 800-171 to protect the confidentiality of CUI.
✅ NIST 800-171 Compliance Checklist
1. Access Control (AC)
Limit system access to authorized users.
Separate duties of users to reduce risk.
Control remote and internal access to CUI.
Manage session timeout and lock settings.
2. Awareness & Training (AT)
Train users on security risks and responsibilities.
Provide CUI handling training.
Update training regularly.
3. Audit & Accountability (AU)
Generate audit logs for events.
Protect audit logs from modification.
Review and analyze logs regularly.
4. Configuration Management (CM)
Establish baseline configurations.
Control changes to systems.
Implement least functionality principle.
5. Identification & Authentication (IA)
Use unique IDs for users.
Enforce strong password policies.
Implement multifactor authentication.
6. Incident Response (IR)
Establish an incident response plan.
Detect, report, and track incidents.
Conduct incident response training and testing.
7. Maintenance (MA)
Perform system maintenance securely.
Control and monitor maintenance tools and activities.
8. Media Protection (MP)
Protect and label CUI on media.
Sanitize or destroy media before disposal.
Restrict media access and transfer.
9. Physical Protection (PE)
Limit physical access to systems and facilities.
Escort visitors and monitor physical areas.
Protect physical entry points.
10. Personnel Security (PS)
Screen individuals prior to system access.
Ensure CUI access is revoked upon termination.
11. Risk Assessment (RA)
Conduct regular risk assessments.
Identify and evaluate vulnerabilities.
Document risk mitigation strategies.
12. Security Assessment (CA)
Develop and maintain security plans.
Conduct periodic security assessments.
Monitor and remediate control effectiveness.
13. System & Communications Protection (SC)
Protect CUI during transmission.
Separate system components handling CUI.
Implement boundary protections (e.g., firewalls).
14. System & Information Integrity (SI)
Monitor systems for malicious code.
Apply security patches promptly.
Report and correct flaws quickly.
The NIST Gap Assessment Toolkit will cost-effectively assess your organization against the NIST SP 800-171 standard. It will help you to:
Understand the NIST SP 800-171 requirements for storing, processing, and transmitting CUI (Controlled Unclassified Information)
Quickly identify your NIST SP 800-171 compliance gaps
Plan and prioritise your NIST SP 800-171 project to ensure data handling meets U.S. DoD (Department of Defense) requirements
The ISO 42001 readiness checklist structured into ten key sections, followed by my feedback at the end:
1. Context & Scope Identify internal and external factors affecting AI use, clarify stakeholder requirements, and define the scope of your AI Management System (AIMS)
2. Leadership & Governance Secure executive sponsorship, assign AIMS responsibilities, establish an ethics‐driven AI policy, and communicate roles and accountability clearly
3. Planning Perform a gap analysis to benchmark current state, conduct a risk and opportunity assessment, set measurable AI objectives, and integrate risk practices throughout the AI lifecycle.
4. Support & Resources Dedicate resources for AIMS, create training around AI ethics, safety, and governance, raise awareness, establish communication protocols, and maintain documentation.
5. Operational Controls Outline stages of the AI lifecycle (design to monitoring), conduct risk assessments (bias, safety, legal), ensure transparency and explainability, maintain data quality and privacy, and implement incident response.
6. Change Management Implement structured change control—assessing proposed AI modifications, conducting ethical and feasibility reviews, cross‐functional governance, staged rollouts, and post‐implementation audits.
7. Performance Evaluation Monitor AIMS effectiveness using KPIs, conduct internal audits, and hold management reviews to validate performance and compliance.
8. Nonconformity & Corrective Action Identify and document nonconformities, implement corrective measures, review their efficacy, and update the AIMS accordingly.
9. Certification Preparation Collect evidence for internal audits, address gaps, assemble required documentation (including SoA), choose an accredited certification body, and finalize pre‐audit preparations .
Comprehensive but heavy: The checklist covers every facet of AI governance—from initial scoping and leadership engagement to external audits and continuous improvement.
Aligns well with ISO 27001: Many controls are familiar to ISMS practitioners, making ISO 42001 a viable extension.
Resource-intensive: Expect demands on personnel, training, documentation, and executive involvement.
Change management focus is smart: The dedication to handling AI updates (design, rollout, monitoring) is a notable strength.
Documentation is key: Templates like Statement of Applicability and impact assessment forms (e.g., AISIA) significantly streamline preparation.
Recommendation: Prioritize gap analysis early, leverage existing ISMS frameworks, and allocate clear roles—this positions you well for a smooth transition to certification readiness.
Overall, ISO 42001 readiness is achievable by taking a methodical, risk-based, and well-resourced approach. Let me know if you’d like templates or help mapping this to your current ISMS.
“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.”
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.
“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.”
Artificial Intelligence (AI) stands as a paradox in the cybersecurity landscape. While it empowers attackers with tools to launch faster, more convincing scams, it also offers defenders unmatched capabilities—if used strategically.
1. AI: A Dual-Edged Sword The post emphasizes AI’s paradox in cybersecurity—it empowers attackers to launch sophisticated assaults while offering defenders potent tools to counteract those very threats
2. Rising Threats from Adversarial AI AI emerging risks, such as data poisoning and adversarial inputs that can subtly mislead or manipulate AI systems deployed for defense
3. Secure AI Lifecycle Practices To mitigate these threats, the article recommends implementing security across the entire AI lifecycle—covering design, development, deployment, and continual monitoring
4. Regulatory and Framework Alignment It points out the importance of adhering to standards like ISO and NIST, as well as upcoming regulations around AI safety, to ensure both compliance and security .
5. Human-AI Synergy A key insight is blending AI with human oversight/processes, such as threat modeling and red teaming, to maximize AI’s effectiveness while maintaining accountability
6. Continuous Adaptation and Education
Modern social engineering attacks have evolved beyond basic phishing emails. Today, they may come as deepfake videos of executives, convincingly realistic invoices, or well-timed scams exploiting current events or behavioral patterns.
The sophistication of these AI-powered attacks has rendered traditional cybersecurity tools inadequate. Defenders can no longer rely solely on static rules and conventional detection methods.
To stay ahead, organizations must counter AI threats with AI-driven defenses. This means deploying systems that can analyze behavioral patterns, verify identity authenticity, and detect subtle anomalies in real time.
Forward-thinking security teams are embedding AI into critical areas like endpoint protection, authentication, and threat detection. These adaptive systems provide proactive security rather than reactive fixes.
Ultimately, the goal is not to fear AI but to outsmart the adversaries who use it. By mastering and leveraging the same tools, defenders can shift the balance of power.
🧠 Case Study: AI-Generated Deepfake Voice Scam — $35 Million Heist
In 2023, a multinational company in the UK fell victim to a highly sophisticated AI-driven voice cloning attack. Fraudsters used deepfake audio to impersonate the company’s CEO, directing a senior executive to authorize a $35 million transfer to a fake supplier account. The cloned voice was realistic enough to bypass suspicion, especially because the attackers timed the call during a period when the CEO was known to be traveling.
This attack exploited AI-based social engineering and psychological trust cues, bypassing traditional cybersecurity defenses such as spam filters and endpoint protection.
Defense Lesson: To prevent such attacks, organizations are now adopting AI-enabled voice biometrics, real-time anomaly detection, and multi-factor human-in-the-loop verification for high-value transactions. Some are also training employees to identify subtle behavioral or contextual red flags, even when the source seems authentic.
In early 2023, a multinational company in Hong Kong lost over $25 million after employees were tricked by a deepfake video call featuring AI-generated replicas of senior executives. The attackers used AI to mimic voices and appearances convincingly enough to authorize fraudulent transfers—highlighting how far social engineering has advanced with AI.
Source: [CNN Business, Feb 2024 – “Scammers used deepfake video call to steal millions”]
This example reinforces the urgency of integrating AI into threat detection and identity verification systems, showing how traditional security tools are no longer sufficient against such deception.
“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.”
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
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.
1. Rise of Sophisticated Impersonation Attacks Threat actors are increasingly tricking users by impersonating trusted services like ChatGPT, Cisco AnyConnect, Google Meet, and Microsoft Teams. They deploy phishing campaigns using cloned login pages or malicious files that seem legitimate, hoping to deceive users into entering credentials or downloading malware. These mimicry operations are carefully designed, with legitimate branding and context.
2. Exploiting Hybrid Work Tools With remote and hybrid work now the norm, hackers have shifted their tactics to exploit collaboration and VPN platforms. They craft malicious emails or fake notifications that appear to come from these popular services, encouraging users to click harmful links or grant permissions that facilitate unauthorized access and infection .
3. Diverse Payload Delivery Mechanisms The attacks aren’t limited to one method. Some rely on phishing emails containing malicious links or attachments, while others abuse meeting invites in Google Meet or Teams to deliver payloads. There are also standalone fake installers—such as trojanized VPN software—used to deploy remote access tools or malware under the guise of routine updates or patches .
4. Automation and Targeted Social Engineering By automating the creation of phishing sites and using AI-driven reconnaissance, attackers can construct highly specific and credible social engineering scenarios. These may include sending spoofed notifications tailored for IT admins or frequent VPN users, significantly increasing the chances of successful breaches .
5. Prevention & User Awareness Strategies The article stresses defense-in-depth strategies: enabling multi-factor authentication (MFA), verifying URLs before entering credentials, using dedicated device managers for downloads, and providing regular phishing-awareness training. It also underscores that IT teams should monitor logs for unusual login patterns and extend protection to collaboration platforms via endpoint security or email filtering .
Feedback
This piece effectively highlights a growing threat in today’s work environment—attackers hijacking the trust in widely used collaboration and VPN tools. Its strength lies in contextualizing how deepfake-style phishing is evolving with remote work trends. However, the article could benefit from more real-world examples or case studies to illustrate these threats in action. Additionally, it might be worthwhile to include references to security standards like the MITRE ATT&CK framework, which would give readers clearer insight into attack patterns and mitigation tactics. Overall, it’s a clear, timely alert that serves both as a warning and a practical guide for strengthening organizational security.
The SEC has charged a major tech company for deceiving investors by exaggerating its use of AI—highlighting that the falsehood was about AI itself, not just product features. This signals a shift: AI governance has now become a boardroom-level issue, and many organizations are unprepared.
Advice for CISOs and execs:
Be audit-ready—any AI claims must be verifiable.
Involve GRC early—AI governance is about managing risk, enforcing controls, and ensuring transparency.
Educate your board—they don’t need to understand algorithms, but they must grasp the associated risks and mitigation plans.
If your current AI strategy is nothing more than a slide deck and hope, it’s time to build something real.
AI Washing
The Securities and Exchange Commission (SEC) has been actively pursuing actions against companies for misleading statements about their use of Artificial Intelligence (AI), a practice often referred to as “AI washing”.
Here are some examples of recent SEC actions in this area:
Presto Automation: The SEC charged Presto Automation for making misleading statements about its AI-powered voice technology used for drive-thru order taking. Presto allegedly failed to disclose that it was using a third party’s AI technology, not its own, and also misrepresented the extent of human involvement required for the product to function.
Delphia and Global Predictions: These two investment advisers were charged with making false and misleading statements about their use of AI in their investment processes. The SEC found that they either didn’t have the AI capabilities they claimed or didn’t use them to the extent they advertised.
Nate, Inc.: The founder of Nate, Inc. was charged by both the SEC and the DOJ for allegedly misleading investors about the company’s AI-powered app, claiming it automated online purchases when they were primarily processed manually by human contractors.
Key takeaways from these cases and SEC guidance:
Transparency and Accuracy: Companies need to ensure their AI-related disclosures are accurate and avoid making vague or exaggerated claims.
Distinguish Capabilities: It’s important to clearly distinguish between current AI capabilities and future aspirations.
Substantiation: Companies should have a reasonable basis and supporting evidence for their AI-related claims.
Disclosure Controls: Companies should establish and maintain disclosure controls to ensure the accuracy of their AI-related statements in SEC filings and other communications.
The SEC has made it clear that “AI washing” is a top enforcement priority, and companies should be prepared for heightened scrutiny of their AI-related disclosures.
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Trust ShareVault—where security, privacy, and uptime come standard.
Top benefits of ShareVault:
Advanced Document Security ShareVault offers robust encryption, dynamic watermarking, and granular access controls to ensure that sensitive documents remain secure—whether viewed, downloaded, or shared.
Granular User Permissions Control who sees what, when, and how. ShareVault enables administrators to define user roles, set expiration dates, and restrict actions like printing or screen captures.
Real-Time Activity Monitoring Detailed audit trails and real-time analytics provide full visibility into who accessed what and when—crucial for compliance, due diligence, and risk management.
Seamless Collaboration Collaborate across teams and organizations with ease, using a user-friendly interface and support for secure Q&A, document versioning, and threaded commenting.
High Availability and Scalability ShareVault is cloud-based with 99.99% uptime, offering reliable access anytime, anywhere—ideal for fast-paced deals, global teams, and critical business operations.
ShareVault holds an ISO 27001 certification for its Security Management Program and undergoes annual third-party audits to validate its security controls, governance, and compliance. These assessments ensure continued adherence to ISO 27001, NIST 800-53r5, and 21 CFR Part 11 standards.
Sharvault Application Security
Operating Systems: A mix of open-source and proprietary server operating systems
Architecture: Multi-tenant design for data isolation
Application Server: Industry-standard Java-based application server
Database: Enterprise-grade relational database management system
Authentication: Robust security framework for user authentication and access control
Key Management: Cloud-based key management service
Data Transfer Security: Strong encryption for all data transfers
Global Performance: Content delivery network for optimized global access
Document Handling: Various tools for document processing and viewing
Search and Logging: Advanced search and logging capabilities
Email Services: Professional email delivery service
Video Security: Secure video streaming with digital rights management
Additional Database: NoSQL database for specific functionality
AI Integration: AI-powered services for document analysis and processing
Feedback: Overall ShareVault appears to have a robust and comprehensive security architecture, leveraging a range of industry-standard technologies and best practices. The use of encryption, two-factor authentication, access controls, and secure data transfer protocols demonstrates a strong commitment to data security and privacy. Additionally, the integration of AI and machine learning capabilities for tasks like redaction and OCR highlights ShareVault’s adoption of modern technologies. Overall, the application security measures described seem well-designed and appropriate for a highly secure document sharing platform.
The Open Web Application Security Project (OWASP) has released the AI Testing Guide (AITG)—a structured, technology-agnostic framework to test and secure artificial intelligence systems. Developed in response to the growing adoption of AI in sensitive and high-stakes sectors, the guide addresses emerging AI-specific threats, such as adversarial attacks, model poisoning, and prompt injection. It is led by security experts Matteo Meucci and Marco Morana and is designed to support a wide array of stakeholders, including developers, architects, data scientists, and risk managers.
The guide provides comprehensive resources across the AI lifecycle, from design to deployment. It emphasizes the need for rigorous and repeatable testing processes to ensure AI systems are secure, trustworthy, and aligned with compliance requirements. The AITG also helps teams formalize testing efforts through structured documentation, thereby enhancing audit readiness and regulatory transparency. It supports due diligence efforts that are crucial for organizations operating in heavily regulated sectors like finance, healthcare, and critical infrastructure.
A core premise of the guide is that AI testing differs significantly from conventional software testing. Traditional applications exhibit deterministic behavior, while AI systems—especially machine learning models—are probabilistic in nature. They produce varying outputs depending on input variability and data distribution. Therefore, testing must account for issues such as data drift, fairness, transparency, and robustness. The AITG stresses that evaluating model performance alone is insufficient; testers must probe how models react to both benign and malicious changes in data.
Another standout feature of the AITG is its deep focus on adversarial robustness. AI systems can be deceived through carefully engineered inputs that appear normal to humans but cause erroneous model behavior. The guide provides methodologies to assess and mitigate such risks. Additionally, it includes techniques like differential privacy to protect individual data within training sets—critical in the age of stringent data protection regulations. This holistic testing approach strengthens confidence in AI systems both internally and among external stakeholders.
The AITG also acknowledges the fluid nature of AI environments. Models can silently degrade over time due to data drift or concept shift. To address this, the guide recommends implementing continuous monitoring frameworks that detect such degradation early and trigger automated responses. It incorporates fairness assessments and bias mitigation strategies, which are particularly important in ensuring that AI systems remain equitable and inclusive over time.
Importantly, the guide equips security professionals with specialized AI-centric penetration testing tools. These include tests for membership inference (to determine if a specific record was in the training data), model extraction (to recreate or steal the model), and prompt injection (particularly relevant for LLMs). These techniques are crucial for evaluating AI’s real-world attack surface, making the AITG a practical resource not just for developers, but also for red teams and security auditors.
Feedback: The OWASP AI Testing Guide is a timely and well-structured contribution to the AI security landscape. It effectively bridges the gap between software engineering practices and the emerging realities of machine learning systems. Its technology-agnostic stance and lifecycle coverage make it broadly applicable across industries and AI maturity levels. However, the guide’s ultimate impact will depend on how well it is adopted by practitioners, particularly in fast-paced AI environments. OWASP might consider developing companion tools, templates, and case studies to accelerate practical adoption. Overall, this is a foundational step toward building secure, transparent, and accountable AI systems.
AI isn’t just another tool—it’s a paradigm shift. CISOs must now integrate AI-driven analytics into real-time threat detection and incident response. These systems analyze massive volumes of data faster and surface patterns humans might miss.
2. New vulnerabilities from AI use
Deploying AI creates unique risks: biased outputs, prompt injection, data leakage, and compliance challenges across global jurisdictions. CISOs must treat models themselves as attack surfaces, ensuring robust governance.
3. AI amplifies offensive threats
Adversaries now weaponize AI to automate reconnaissance, craft tailored phishing lures or deepfakes, generate malicious code, and launch fast-moving credential‑stuffing campaigns.
4. Building an AI‑enabled cyber team
Moving beyond tool adoption, CISOs need to develop core data capabilities: quality pipelines, labeled datasets, and AI‑savvy talent. This includes threat‑hunting teams that grasp both AI defense and AI‑driven offense.
5. Core capabilities & controls
The playbook highlights foundational strategies:
Data governance (automated discovery and metadata tagging).
Zero trust and adaptive access controls down to file-system and AI pipelines.
AI-powered XDR and automated IR workflows to reduce dwell time.
6. Continuous testing & offensive security
CISOs must adopt offensive measures—AI pen testing, red‑teaming models, adversarial input testing, and ongoing bias audits. This mirrors traditional vulnerability management, now adapted for AI-specific threats.
7. Human + machine synergy
Ultimately, AI acts as a force multiplier—not a surrogate. Humans must oversee, interpret, understand model limitations, and apply context. A successful cyber‑AI strategy relies on continuous training and board engagement .
🧩 Feedback
Comprehensive: Excellent balance of offense, defense, data governance, and human oversight.
Actionable: Strong emphasis on building capabilities—not just buying tools—is a key differentiator.
Enhance with priorities: Highlighting fast-moving threats like prompt‑injection or autonomous AI agents could sharpen urgency.
Communications matter: Reminding CISOs to engage leadership with justifiable ROI and scenario planning ensures support and budget.
AI transforms the cybersecurity role—especially for CISOs—in several fundamental ways:
1. From Reactive to Predictive
Traditionally, security teams react to alerts and known threats. AI shifts this model by enabling predictive analytics. AI can detect anomalies, forecast potential attacks, and recommend actions before damage is done.
2. Augmented Decision-Making
AI enhances the CISO’s ability to make high-stakes decisions under pressure. With tools that summarize incidents, prioritize risks, and assess business impact, CISOs move from gut instinct to data-informed leadership.
3. Automation of Repetitive Tasks
AI automates tasks like log analysis, malware triage, alert correlation, and even generating incident reports. This allows security teams to focus on strategic, higher-value work, such as threat modeling or security architecture.
4. Expansion of Threat Surface Oversight
With AI deployed in business functions (e.g., chatbots, LLMs, automation platforms), the CISO must now secure AI models and pipelines themselves—treating them as critical assets subject to attack and misuse.
5. Offensive AI Readiness
Adversaries are using AI too—to craft phishing campaigns, generate polymorphic malware, or automate social engineering. The CISO’s role expands to understanding offensive AI tactics and defending against them in real time.
6. AI Governance Leadership
CISOs are being pulled into AI governance: setting policies around responsible AI use, bias detection, explainability, and model auditing. Security leadership now intersects with ethical AI oversight and compliance.
7. Cross-Functional Influence
Because AI touches every function—HR, legal, marketing, product—the CISO must collaborate across departments, ensuring security is baked into AI initiatives from the ground up.
Summary: AI transforms the CISO from a control enforcer into a strategic enabler who drives predictive defense, leads governance, secures machine intelligence, and shapes enterprise-wide digital resilience. It’s a shift from gatekeeping to guiding responsible, secure innovation.
1. Minimize Due Diligence Surprises Unexpected revelations—such as financial inconsistencies, unresolved legal matters, or unclear intellectual property rights—can erode buyer trust and derail deals. A well-organized virtual data room (VDR) can help sellers centralize all important documents, making them easy to find and pre-reviewed. Conducting a pre-sale readiness check from a buyer’s perspective enables the seller to resolve potential red flags before due diligence begins, preserving deal momentum and buyer confidence.
2. Attract a Wider Pool of Buyers VDRs offer 24/7 global access, enabling sellers to reach prospects across regions and time zones without logistical constraints. This accessibility not only broadens the potential buyer base but also allows sellers to adjust access levels according to a buyer’s seriousness and stage in the process. More qualified buyers at the table often results in higher bids and a stronger negotiating position.
3. Speed Up the Due Diligence Timeline Extended deal timelines increase the risk of buyer fatigue, price renegotiation, or withdrawal. Modern VDRs expedite the review process by enabling features such as intelligent search, batch downloads, and scrollable document viewing. They also allow real-time Q&A and insights into buyer behavior through analytics. Proactively addressing a buyer’s focus areas keeps the transaction on track and supports deal closure.
4. Address Buyer Delays Effectively While many deal risks lie on the seller side, buyer inaction can also jeopardize outcomes. VDRs provide visibility into each buyer’s activity, allowing sellers to monitor engagement levels and act if a buyer becomes unresponsive. If needed, sellers can quickly pivot to alternative prospects without starting over—thanks to structured document control and access management in the VDR.
5. Stay Prepared for Market Fluctuations Market instability can cause buyers to hesitate or sellers to delay exits. Still, being always ready is key. A company with an up-to-date VDR can respond quickly when interest arises, regardless of market timing. This readiness increases agility and allows sellers to capitalize on windows of opportunity before they close.
6. Feedback: Practical, but Vendor-Biased The paper effectively outlines how VDRs streamline M&A deals and mitigate common failure points. Its practical guidance—such as maintaining data readiness, leveraging buyer activity data, and preventing slowdowns—reflects real concerns for sellers. However, as a vendor-produced document, it understandably leans heavily on ShareVault’s feature set. Including case studies or quantitative outcomes from actual deals would enhance credibility. Nonetheless, the core message remains solid: thoughtful use of VDRs can make or break a deal.
7. Strengthen Data Security to Protect Value Cybersecurity risks in M&A—especially data breaches through email or unsecured storage—can severely impact deal value. Sophisticated hackers increasingly target M&A communication threads for financial gain. To mitigate this, companies should avoid using email or generic cloud services for sensitive files. Instead, using a secure VDR from the outset of discussions ensures confidential information stays protected, preventing reputational and financial damage.
Well-configured VDR is more than just a secure document repository—it acts as a deal accelerator and risk mitigator. By emphasizing proactive organization, communication, and adaptability, the paper aligns VDR capabilities with common deal pitfalls. While it’s clearly written with VDR vendors in mind, the practical advice—like tag-based structures, audit logs, and pre‑emptive Q&A—is broadly applicable. Overall, valuable and actionable for anyone navigating complex M&A scenarios.
The U.S. Department of Defense (DoD) mandates that all contractors and subcontractors handling Controlled Unclassified Information (CUI) must maintain an accessible assessment of their compliance with NIST SP 800-171. This requirement supports a broader national effort to standardize cybersecurity practices, even for organizations managing unclassified or sensitive data. Ensuring compliance is crucial not only for maintaining eligibility for government contracts but also for strengthening the overall cybersecurity posture.
To support this, the NIST Gap Assessment Tool offers a structured, Excel-based template that guides organizations through the full assessment process. It includes all 14 control families and 110 security controls specified in NIST SP 800-171, allowing for streamlined tracking, documentation, and reporting. The tool is designed for usability, enabling teams to identify gaps and prioritize remediation efforts efficiently.
walks you step-by-step through each NIST SP 800-171 requirement, so you know exactly what to do next.
No cybersecurity expertise needed—complete your gap assessment in hours, not days, using clear prompts and built-in summaries
Whether you’re a small defense contractor or a subcontractor just starting with compliance, the tool helps you quickly identify gaps and generate reports that align with DoD audit expectations
Includes drop-down menus, pre-filled descriptions, and auto-calculated scoring to simplify documentation
By using the tool, you don’t just meet compliance—you also reduce the risk of losing contracts due to audit findings
The NIST Gap Assessment Tool will cost-effectively assess your organization against the NIST SP 800-171 standard
What does the tool do?
Features the following tabs: ‘Instructions’, ‘Summary’, and ‘Assessment and SSP’.
The ‘Instructions’ tab provides an easy explanation of how to use the tool and assess your compliance project, so you can complete the process without hassle.
The ‘Assessment and SSP’ tab shows all control numbers and requires you to complete your assessment of each control.
Once you have completed the full assessment, the ‘Summary’ tab provides high-level graphs for each category and overall completion. Analysis includes an overall compliance score and shows the amount of security controls that are completed, ongoing, or not applied in your organization.
The ‘Summary’ tab also provides clear direction for areas of development and how you should plan and prioritize your project effectively, so you can start the journey of providing a completed NIST SP 800-171 assessment to the DoD.
This NIST Gap Assessment Tool is not designed for conducting a detailed and granular compliance assessment.
Mapping against ISO 42001:2023 and/or the EU Artificial Intelligence (AI) Act
The AI Act & ISO 42001 Gap Analysis Tool is a dual-purpose resource that helps organizations assess their current AI practices against both legal obligations under the EU AI Act and international standards like ISO/IEC 42001:2023. It allows users to perform a tailored gap analysis based on their specific needs, whether aligning with ISO 42001, the EU AI Act, or both. The tool facilitates early-stage project planning by identifying compliance gaps and setting actionable priorities.
With the EU AI Act now in force and enforcement of its prohibitions on high-risk AI systems beginning in February 2025, organizations face growing pressure to proactively manage AI risk. Implementing an AI management system (AIMS) aligned with ISO 42001 can reduce compliance risk and meet rising international expectations. As AI becomes more embedded in business operations, conducting a gap analysis has become essential for shaping a sound, legally compliant, and responsible AI strategy.
Feedback: This tool addresses a timely and critical need in the AI governance landscape. By combining legal and best-practice assessments into one streamlined solution, it helps reduce complexity for compliance teams. Highlighting the upcoming enforcement deadlines and the benefits of ISO 42001 certification reinforces urgency and practicality.
The AI Act & ISO 42001 Gap Analysis Tool is a user-friendly solution that helps organizations quickly and effectively assess their current AI practices against both the EU AI Act and the ISO/IEC 42001:2023 standard. With intuitive features, customizable inputs, and step-by-step guidance, the tool adapts to your organization’s specific needs—whether you’re looking to meet regulatory obligations, align with international best practices, or both. Its streamlined interface allows even non-technical users to conduct a thorough gap analysis with minimal training.
Designed to integrate seamlessly into your project planning process, the tool delivers clear, actionable insights into compliance gaps and priority areas. As enforcement of the EU AI Act begins in early 2025, and with increasing global focus on AI governance, this tool provides not only legal clarity but also practical, accessible support for developing a robust AI management system. By simplifying the complexity of AI compliance, it empowers teams to make informed, strategic decisions faster.
What does the tool provide?
Split into two sections, EU AI Act and ISO 42001, so you can perform analyses for both or an individual analysis.
The EU AI Act section is divided into six sets of questions: general requirements, entity requirements, assessment and registration, general-purpose AI, measures to support innovation and post-market monitoring.
Identify which requirements and sections of the AI Act are applicable by completing the provided screening questions. The tool will automatically remove any non-applicable questions.
The ISO 42001 section is divided into two sets of questions: ISO 42001 six clauses and ISO 42001 controls as outlined in Annex A.
Executive summary pages for both analyses, including by section or clause/control, the number of requirements met and compliance percentage totals.
A clear indication of strong and weak areas through colour-coded analysis graphs and tables to highlight key areas of development and set project priorities.
The tool is designed to work in any Microsoft environment; it does not need to be installed like software, and does not depend on complex databases. It is reliant on human involvement.
Items that can support an ISO 42001 (AIMS) implementation project
Overview: DISC WinerySecure™ is a tailored cybersecurity and compliance service for small and mid-sized wineries. These businesses are increasingly reliant on digital systems (POS, ecommerce, wine clubs), yet often lack dedicated security staff. Our solution is cost-effective, easy to adopt, and customized to the wine industry.
Wineries may not seem like obvious cyber targets, but they hold valuable data—customer and employee details like social security numbers, payment info, and birthdates—that cybercriminals can exploit for identity theft and sell on the dark web. Even business financials are at risk.
Target Clients:
We care for the planet and your data
Wineries invest in luxury branding
Wineries considering mergers and acquisitions.
Wineries with 50–1000 employees
Using POS, wine club software, ecommerce, or logistics systems
Limited or no in-house IT/security expertise
🍷 Cyber & Compliance Protection for Wineries
Helping Napa & Sonoma Wineries Stay Secure, Compliant, and Trusted
🛡️ Why Wineries Are at Risk
Wineries today handle more sensitive data than ever—credit cards, wine club memberships, ecommerce sales, shipping details, and supplier records. Yet many rely on legacy systems, lack dedicated IT teams, and operate in a complex regulatory environment.
Cybercriminals know this. Wineries have become easy, high-value targets.
✅ Our Services
We offer fractional vCISO and compliance consulting tailored for small and mid-sized wineries:
🔒 Cybersecurity Risk Assessment – Discover hidden vulnerabilities in your systems, Wi-Fi, and employee habits.
📜 CCPA/CPRA Privacy Compliance – Ensure you’re protecting your customers’ personal data the California way.
🧪 Phishing & Ransomware Defense – Train your team to spot threats and test your defenses before attackers do.
🧰 Security Maturity Roadmap – Practical, phased improvements aligned with your business goals and brand.
🧾 Simple Risk Scorecard – A 10-page report you can share with investors, insurers, or partners.
🎯 Who This Is For
Family-run or boutique wineries with direct-to-consumer operations
Wineries investing in digital growth, but unsure how secure it is
Teams managing POS, ecommerce, club CRMs, M&A and vendor integrations
💡 Why It Matters
🏷️ Protect your brand reputation—especially with affluent wine club customers
💸 Avoid fines and lawsuits from privacy violations or breaches
🛍️ Boost customer confidence—safety sells
📉 Reduce downtime, ransomware risk, and compliance headaches
📞 Let’s Talk
Get a free 30-minute consultation or try our $49 Self-Assessment + 10-Page Risk Scorecard to see where you stand.
1. Strategic importance of discretion When two major companies are negotiating a merger or acquisition, even a minor leak can damage stock prices, derail the process, or collapse the deal entirely. A confidential environment is essential to preserve each party’s strategic advantage during secretive stages of the negotiation.
2. Maintaining competitive secrecy By keeping a forthcoming deal under wraps, a company can gain from stealthy operations—honing tactics and announcements without alerting rivals or disrupting the market prematurely.
3. Protecting sensitive materials during due diligence The due diligence stage demands access to proprietary analytics, trade secrets, and financial documents. A properly secured virtual data room (VDR) ensures these materials can be reviewed without risking unwanted exposure.
4. Internal stability amid uncertainty Beyond market reactions, confidentiality helps stabilize employee morale. Rumors of acquisitions can breed anxiety among staff; controlled disclosure helps maintain calm until formal announcements are made .
5. Why virtual is preferred over physical rooms Compared to traditional physical data rooms or email-based exchanges, VDRs offer encrypted, centralized, and remotely accessible document storage. They support multiple users across time zones and locales, making them far more efficient and secure
6. Advanced organization and control tools Modern VDRs include features like hierarchical tagging (as in ShareVault’s platform), robust document indexing, full-text search, and flexible file rights. Admins can finely tune access—for instance, disabling copying, printing, or even screenshots—and apply watermarks with expiration settings .
7. Enhanced transparency, auditability, and efficiency These platforms offer complete audit trails, Q&A sections, real-time alerts, and analytics. Participants can track activity, identify engagement patterns, and streamline due diligence, speeding up deal completion and improving oversight
Virtual Data Rooms (VDRs) are essential tools in mergers and acquisitions, providing a secure platform for sharing confidential documents during due diligence. They enable controlled access to sensitive information, supporting informed decision-making and effective risk management. In today’s digital landscape, where information is a critical asset, VDRs enhance corporate governance by promoting transparency, accountability, and compliance. As businesses face increasing regulatory and operational demands, adopting VDRs is not just a smart choice but a strategic necessity for maintaining strong governance and operational integrity.
Virtual data rooms are indispensable in confidential M&A contexts. They effectively combine security, efficiency, and collaboration in ways that physical or email-based systems simply cannot. The advanced features—granular permissions, audit logs, analytics, and query tools—are not just conveniences; they’re game-changers that help drive deals forward more smoothly and securely.
To truly elevate the experience, VDR providers Sharevault prioritize user-friendly interfaces—think intuitive document sorting, drag & drop, clear timestamps—and strike a better balance between robust security measures and seamless usability. When technical strength aligns with an intuitive user experience, virtual data rooms fulfill their potential, making complex, high-stakes M&A processes feel nearly effortless.
Information Security & Privacy aspect of the M&A process, especially focusing on how confidentiality, integrity, and controlled access are preserved throughout.
1. Confidentiality of Deal Intentions and Parties Involved
In early M&A stages, even the existence of negotiations must be tightly guarded. Leakage of deal discussions can lead to:
Stock volatility
Competitor disruption
Supplier or customer anxiety
Employee attrition
To prevent this, non-disclosure agreements (NDAs) are signed before sharing even basic information. VDRs enforce this by granting access only to vetted parties and logging all user activity, discouraging leaks.
2. Due Diligence Security
This is the most data-sensitive phase. Buyers review:
Financial statements
Tax filings
Contracts
Intellectual property details
Litigation history
Cyber risk posture
Each document represents potential liability if exposed. A secure VDR ensures:
End-to-end encryption (AES-256 or higher)
Multi-factor authentication (MFA)
Granular access control down to the file or section level
View-only access with no downloads, printing, or screen capture
Watermarks with user IPs and timestamps
3. Auditability and Legal Traceability
To defend the integrity of the deal and respond to any post-deal disputes, every interaction must be tracked:
Who viewed what, when, and for how long
Questions asked and answered (Q&A logs)
Document version histories
These logs are part of legal documentation and are often retained long after the deal closes.
4. Cybersecurity Risk Assessment as a Deal Factor
Buyers often assess the seller’s cybersecurity posture as part of due diligence. Poor security (e.g., history of breaches, lax controls, outdated tech) may reduce valuation or kill the deal. Common items reviewed include:
Security policies
Incident response history
SOC 2 / ISO 27001 certifications
Penetration test results
Data breach disclosures
In this case, the VDR may host security documentation that itself must be securely handled.
5. Insider Risk and Privilege Escalation Control
Not all threats are external. Internal actors—disgruntled employees, opportunists, or even curious insiders—can leak or misuse information. VDRs address this by:
Role-based access (e.g., legal, finance, HR teams see only what’s necessary)
IP restriction (limit access by location)
Time-bound access with auto-expiry
Real-time alerts on suspicious behavior (e.g., large downloads)
6. Data Sovereignty and Compliance Risks
Cross-border M&A may involve GDPR, HIPAA, CCPA, or local data protection laws. VDRs must:
Store data in approved jurisdictions
Enable redaction tools
Offer data retention and deletion policies in compliance with local law
Failing to do this may introduce legal exposure before the deal even closes.
7. Post-Deal Data Handoff and Secure Closure
After the deal, secure handoff of all data—including audit trails—is essential. VDRs often allow data archiving in encrypted format for legal teams. Proper exit procedures also include:
Revoking third-party access
Exporting logs for compliance
Certifying destruction of temporary working copies
Final Thoughts
Security in M&A isn’t just about locking down data—it’s about enabling trust between parties while protecting the value of the transaction. A single breach could derail a deal or cause post-acquisition litigation. VDRs that offer bank-grade security, forensic logging, regulatory compliance, and intuitive access control are non-negotiable in high-stakes deals. However, companies must complement technology with clear policies and trained personnel to truly secure the process.
Would you like a framework (e.g., ISO 27001-aligned) to assess the security readiness of an M&A deal? info@deurainfosec.com
1. Evolving Role of Cybersecurity Services Traditional cybersecurity engagements—such as vulnerability patching, audits, or one-off assessments—tend to be short-term and reactive, addressing immediate concerns without long-term risk reduction. In contrast, end-to-end cybersecurity programs offer sustained value by embedding security into an organization’s core operations and strategic planning. This shift transforms cybersecurity from a technical task into a vital business enabler.
2. Strategic Provider-Client Relationship Delivering lasting cybersecurity outcomes requires service providers to move beyond technical support and establish strong partnerships with organizational leadership. Providers that engage at the executive level evolve from being IT vendors to trusted advisors. This elevated role allows them to align security with business objectives, providing continuous support rather than piecemeal fixes.
3. Core Components of a Strategic Cybersecurity Program A comprehensive end-to-end program must address several key domains: risk assessment and management, strategic planning, compliance and governance, business continuity, security awareness, incident response, third-party risk management, and executive reporting. Each area works in concert to strengthen the organization’s overall security posture and resilience.
4. Risk Assessment & Management A strategic cybersecurity initiative begins with a thorough risk assessment, providing visibility into vulnerabilities and their business impact. A complete asset inventory is essential, and follow-up includes risk prioritization, mitigation planning, and adapting defenses to evolving threats like ransomware. Ongoing risk management ensures that controls remain effective as business conditions change.
5. Strategic Planning & Roadmaps Once risks are understood, the next step is strategic planning. Providers collaborate with clients to create a cybersecurity roadmap that aligns with business goals and compliance obligations. This roadmap includes near-, mid-, and long-term goals, backed by security policies and metrics that guide decision-making and keep efforts aligned with the company’s direction.
6. Compliance & Governance With rising regulatory scrutiny, organizations must align with standards such as NIST, ISO 27001, HIPAA, SOC 2, PCI-DSS, and GDPR. Security providers help identify which regulations apply, assess current compliance gaps, and implement sustainable practices to meet ongoing obligations. This area remains underserved and represents an opportunity for significant impact.
7. Business Continuity & Disaster Recovery Effective security programs not only prevent breaches but also ensure operational continuity. Business Continuity Planning (BCP) and Disaster Recovery (DR) encompass infrastructure backups, alternate operations, and crisis communication strategies. Providers play a key role in building and testing these capabilities, reinforcing their value as strategic advisors.
8. Human-Centric Security & Response Preparedness People remain a major risk vector, so training and awareness are critical. Providers offer education programs, phishing simulations, and workshops to cultivate a security-aware culture. Incident response readiness is also essential—providers develop playbooks, assign roles, and simulate breaches to ensure rapid and coordinated responses to real threats.
9. Executive-Level Communication & Reporting A hallmark of high-value cybersecurity services is the ability to translate technical risks into business language. Clear executive reporting connects cybersecurity activities to business outcomes, supporting board-level decision-making and budget justification. This capability is key for client retention and helps providers secure long-term engagements.
Feedback
This clearly outlines how cybersecurity must evolve from reactive technical support into a strategic business function. The focus on continuous oversight, executive engagement, and alignment with organizational priorities is especially relevant in today’s complex threat landscape. The structure is logical and well-grounded in vCISO best practices. However, it could benefit from sharper differentiation between foundational services (like asset inventories) and advanced advisory (like executive communication). Emphasizing measurable outcomes—such as reduced incidents, improved audit results, or enhanced resilience—would also strengthen the business case. Overall, it’s a strong framework for any provider building or refining an end-to-end security program.
