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Home – ISO 27000 Assessments
AI systems create security vulnerabilities traditional information security frameworks miss: training data poisoning, model extraction attacks, and AI-generated output leaking confidential information. Our ISO 27000 certification ensures comprehensive security assessments addressing both conventional and AI-specific risks.
Traditional information security protects systems from external threats—hackers, malware, unauthorized access. It assumes threats come from outside trying to get in.
AI creates fundamentally different security risks that exist inside your systems: models trained on data they shouldn’t access, AI outputs accidentally exposing confidential information, adversarial attacks manipulating AI decisions, and training data poisoning corrupting model behavior.
Standard ISO 27000 assessments miss these AI-specific vulnerabilities because they focus on traditional security controls. AI systems need security assessments addressing both conventional threats and AI-unique risks.
Our ISO 27000 certification provides the information security foundation. Our AI expertise extends it to address vulnerabilities that standard assessments don’t evaluate.
What It Covers:
What It Proves: We understand formal information security management frameworks recognized globally by regulators, auditors, and enterprises.
Why This Matters For AI: ISO 27000 provides the security foundation AI systems require. We extend it with AI-specific security assessments addressing vulnerabilities the standard doesn’t explicitly cover.
Vulnerability: AI models learn from training data. Compromised training data creates compromised AI systems.
What We Assess:
Risk If Ignored: AI models making incorrect decisions based on maliciously modified training data, creating business impact or compliance violations.
Vulnerability: Attackers can reverse-engineer AI models through carefully crafted queries, stealing intellectual property representing significant development investment.
What We Assess:
Risk If Ignored: Competitors or adversaries stealing AI models representing millions in development investment.
Vulnerability: AI systems trained on confidential data can accidentally expose that information through generated outputs.
What We Assess:
Risk If Ignored: HIPAA violations, trade secret exposure, or other data breaches triggered by AI outputs containing training data fragments.
AI systems becoming business-critical require infrastructure preventing single points of failure.
Vulnerability: Carefully crafted inputs can manipulate AI decisions, bypassing business rules or creating incorrect outputs.
What We Assess:
Risk If Ignored: AI systems manipulated into making decisions that violate policy, regulations, or business logic.
Vulnerability: AI models deployed in production face traditional security threats plus AI-specific risks.
What We Assess:
Risk If Ignored: Standard cyberattacks compromising AI systems or stealing model files.
AI governance requires security assessment as a core component. You can't govern risks you haven't identified.
ISO 27000 security assessments feed into NIST AI Risk Management Framework implementation, providing the security risk data governance frameworks require.
ISO 27000 assessments produce documentation auditors and regulators recognize, satisfying security compliance requirements.
ISO 27000 emphasizes ongoing security management, not one-time assessments—essential for AI systems that evolve as they retrain on new data.
Security assessment identifies vulnerabilities. Governance frameworks determine acceptable risk levels and mitigation strategies.
Healthcare, financial services, and other regulated industries have security requirements beyond generic best practices.
Requirements:
What We Assess: HIPAA-specific security controls for AI systems plus AI-unique vulnerabilities like training data leakage.
Requirements:
What We Assess: Financial services security standards plus algorithmic attack resistance for AI making financial decisions.
Common Needs:
Identify AI systems requiring assessment, data classification levels, and applicable regulatory requirements.
Evaluate existing security controls against ISO 27000 standards and AI-specific security requirements.
Test AI systems for traditional vulnerabilities plus AI-specific risks like adversarial attacks and data leakage.
Prioritize identified vulnerabilities based on likelihood and impact, considering business and regulatory context.
Provide specific, actionable recommendations for addressing identified security gaps.
Assist with implementing security improvements and validating effectiveness.
8-12 weeks for comprehensive assessment including remediation support.
ISO 27000 certification validates knowledge of information security frameworks. Enterprise experience validates ability to apply them in complex organizations.
Our founder implemented security for mission-critical systems at IBM serving Fortune 500 clients where security failures had severe consequences.
We assess AI security for healthcare, financial services, and other regulated industries with strict security requirements beyond generic best practices.
We've supported clients through regulatory audits and security assessments, understanding what auditors evaluate and documentation they require.
We provide security recommendations organizations can actually implement within budget and timeline constraints, not theoretical perfection requiring unlimited resources.
AI governance requires security assessment as a core component. You can't govern risks you haven't identified.
Complete evaluation of AI systems against ISO 27000 standards plus AI-specific security requirements.
Comparison of current security posture against ISO 27000 requirements identifying specific improvements needed.
Implementation assistance for identified security improvements.
Security documentation satisfying auditors and regulators.
Continuous security assessment as AI systems evolve.
Auditors and regulators recognize ISO 27000 as credible security framework. Assessments by certified professionals carry weight during compliance reviews.
ISO 27000 provides systematic security assessment methodology ensuring no critical areas are overlooked.
ISO 27000 is globally recognized standard, important for organizations operating across jurisdictions.
ISO 27000 emphasizes ongoing security management, aligning with AI systems requiring continuous security monitoring.
When evaluating AI security consultants, ISO 27000 certification provides independent validation of security expertise.
Schedule a consultation to discuss your AI security requirements. We’ll assess current security posture and provide realistic recommendations for addressing gaps.
Traditional cybersecurity protects against external threats—hackers, malware, unauthorized access. AI security addresses different risks: training data poisoning where attackers corrupt model behavior, model extraction where competitors steal intellectual property, adversarial attacks manipulating AI decisions, and output leakage where AI accidentally exposes confidential training data. Both matter, but AI requires specialized security assessment beyond traditional approaches.
Not necessarily. Assessment priority depends on AI system criticality and data sensitivity. Business-critical AI making important decisions, AI handling confidential data, or AI in regulated industries needs comprehensive assessment. Experimental AI or low-risk automation may need lighter security review. We help determine appropriate security assessment level during consultation.
Initial comprehensive assessment when deploying AI systems. Then ongoing monitoring with formal reassessment annually or when significant changes occur—new training data, major model updates, expanded use cases, or regulatory changes. AI systems that retrain frequently need more frequent security review than static systems.
Yes. We assess third-party AI services, vendor-provided AI systems, and commercial AI platforms. Assessment approach differs—we evaluate vendor security controls, data handling practices, and integration security rather than internal model architecture. Important for organizations using SaaS AI services or vendor-provided AI solutions.
ISO 27000 is international information security standard focused on security management systems. SOC 2 is American auditing standard evaluating service organization controls. Both address security but different frameworks. For AI, ISO 27000 provides more comprehensive security assessment methodology. Many organizations need both—ISO 27000 for internal security management, SOC 2 for customer assurance when providing AI services.
