The Compliance Gap Nobody Talks About

Every compliance framework worth its weight now references "emerging threats," "AI-powered attack vectors," and "deepfake scenarios." NIS2 mandates comprehensive security testing against evolving threats. DORA requires scenario-based testing for financial institutions. The EU AI Act demands adversarial validation of AI systems.

Now ask your current security awareness vendor a simple question: Can you test my organization against a deepfake voice clone of our CEO requesting an emergency wire transfer?

The answer, overwhelmingly, is no. Traditional vendors are still running the same email phishing simulations they built in 2019. They test whether your employees click a suspicious link. They don't test whether your employees, processes, and technology can withstand a coordinated AI-powered social engineering attack across voice, video, and messaging channels.

That's the compliance gap. And it's growing wider every quarter as regulatory bodies tighten their language around AI-specific threats.

What Auditors Are Starting to Ask

Regulatory bodies are no longer satisfied with checkbox compliance. NIS2 enforcement began in 2024. DORA went into effect in January 2025. The EU AI Act is being phased in through 2026. Auditors are asking harder questions about whether your security program addresses the threats of today, not just the threats of five years ago.

When your auditor asks how you test against AI-powered social engineering, and they will, "we run quarterly phishing simulations" is no longer a sufficient answer. You need evidence that your people, processes, and technology have been stress-tested against deepfake voice clones, AI-generated video impersonation, and multi-channel attack orchestration.

That's exactly what Breacher.ai delivers. We are a threat research firm that conducts real-world AI social engineering attacks against your organization, providing the documentation, attestation, and peer benchmarks that compliance teams need to demonstrate regulatory alignment.

Global Framework Mapping

Below is a detailed mapping of the specific regulatory requirements Breacher.ai addresses across every major compliance framework. These aren't aspirational alignments. These are the specific articles, annexes, and control requirements our assessments produce evidence for.

NIS2 (EU Network and Information Security Directive 2)

• Article 20: Governance Cybersecurity training for management and staff. Our managed training programs deliver ongoing, measurable awareness education that satisfies continuous compliance requirements.
• Article 21(2): Human Factors in Cybersecurity Risk management measures must address human factors. Our red team assessments test employee susceptibility to AI-powered social engineering, producing quantifiable vulnerability scores.
• Article 21(2): Security Incident Handling Organizations must validate incident response procedures. We pressure-test escalation chains, helpdesk verification processes, and executive approval workflows against deepfake attack scenarios.
• Article 21(2): Supply Chain Security Testing must extend across partner and vendor networks. Our simulation platform enables supply chain security testing at scale through multi-tenant deployment.
• Article 21(2)(e): Network and Information Systems Security Technical controls must be validated against emerging threats. We test security controls, detection tools, and authentication systems against AI-generated attacks.

DORA (Digital Operational Resilience Act)

• Article 8: ICT and Security Risk Management Financial entities must implement comprehensive ICT risk management including scenario-based testing, third-party risk assessment, and human risk factors validation. Breacher.ai delivers all three simultaneously.
• Article 13(6): ICT Incident Management Training Regular staff training on ICT incident identification and response. Our continuous simulation programs provide ongoing training with completion metrics suitable for regulatory reporting.

EU AI Act

• Article 15: Accuracy, Robustness, and Cybersecurity High-risk AI systems require adversarial testing and validation. Breacher.ai's Deepfake Detection Controls Assessment provides independent, third-party adversarial testing of AI detection systems against real-world attack scenarios.
• Technical Documentation Requirements AI system validation must be documented for compliance purposes. Our assessment reports provide auditor-acceptable evidence of AI system testing and performance benchmarks.

ISO/IEC 27001:2022

• Annex A 5.7: Threat Intelligence Organizations must collect and analyze threat intelligence on emerging attack vectors. Breacher.ai operates as a threat research firm, producing real-world intelligence from active deepfake attack simulations.
• Annex A 6.3: Awareness, Education, and Training Demonstrates ongoing security awareness programs with measurable outcomes. Our adaptive learning dashboards document training frequency, content delivery, and effectiveness metrics.
• Annex A 8.8: Technical Vulnerability Management Validates that technical controls are effective against current threats. Our platform tests detection capabilities, authentication systems, and security tooling against AI-generated attack vectors.

NIST Cybersecurity Framework (CSF)

• GV.AT & PR.AT: Awareness and Training Security awareness training that addresses current threat landscape. Our programs go beyond click-rate testing to include deepfake voice, video, and multi-channel social engineering scenarios.
• ID.RA: Risk Assessment Risk identification must include emerging threats. Our Deepfake Resilience Score provides quantifiable risk data specific to AI-powered social engineering exposure.
• DE.CM: Continuous Monitoring Ongoing security monitoring and validation. Monthly simulation programs demonstrate continuous testing cadence with trend data and improvement tracking.
• RS.AN: Incident Response Analysis Validates that incident response procedures work under pressure. We test escalation chains, verification protocols, and containment procedures against realistic attack scenarios.

SOC 2 Type II

• CC1.4: Security Awareness Training Documented security awareness programs with evidence of employee participation. Our platform produces completion metrics, performance analytics, and improvement documentation.
• CC3.2: Risk Identification and Assessment Identification of risks including emerging threat vectors. Our assessment data demonstrates that AI-powered social engineering risks have been identified, tested, and measured.
• CC7.2: Security Incident Detection Monitoring and detection capabilities for security events. Our testing validates whether detection controls and human alerting procedures function against deepfake attack scenarios.

SOX (Sarbanes-Oxley Act)

• Section 404: Internal Controls Assessment Validates technical controls preventing deepfake-based financial fraud. Tests authentication and authorization controls against AI impersonation attacks targeting financial processes. Third-party attestation supports internal control documentation for financial statement audits.

NIST AI Risk Management Framework (AI RMF)

• MAP 1.5: AI Risk Identification Identifies AI risks across operational contexts. Our assessments map organizational exposure to AI-generated social engineering threats across all business functions.
• MEASURE 2.6: AI System Accuracy Validates AI detection system accuracy and false positive/negative rates. Our Deepfake Detection Controls Assessment provides statistical validation of detection capabilities with benchmark comparisons.
• MANAGE 4.2: Deployed AI System Value Ongoing testing validates continued effectiveness of detection controls. Continuous assessment programs demonstrate sustained performance measurement and management.

FedRAMP / FISMA

• AT-2: Literacy Training and Awareness Validates that technical controls supplement human awareness against emerging threats. Our assessments test both human detection capabilities and supporting technology controls.
• IR-3: Incident Response Testing Tests detection and response capabilities against emerging threat scenarios. Independent assessment reports are suitable for FedRAMP continuous monitoring requirements.

HIPAA

• 164.308(a)(5): Security Awareness and Training Security awareness programs must address current threats. Our simulations include healthcare-specific scenarios targeting PHI access through AI-powered social engineering.
• 164.308(a)(6): Security Incident Procedures Incident response procedures must be tested and documented. Our assessments validate whether healthcare staff can detect and escalate deepfake impersonation attempts targeting patient data.

What Traditional Vendors Can't Deliver

The gap between what compliance frameworks require and what legacy security awareness vendors provide is widening every quarter. Here's where the industry falls short and where Breacher.ai fills the void.

How Each Solution Addresses Compliance

Breacher.ai's three solution pillars map directly to the compliance requirements outlined above. Each produces distinct compliance evidence suitable for audit documentation, board reporting, and regulatory submissions.

Deepfake Red Team Assessments™

Enterprise-grade adversarial testing that produces the highest-value compliance evidence. Our red team conducts live deepfake voice, video, and multi-channel social engineering attacks against your organization, testing people, processes, and technology simultaneously.

• NIS2 Article 21 Tests human factors, security incident handling, and technical controls validation against AI-powered attack scenarios.
• DORA Article 8 Fulfills scenario-based testing, third-party risk assessment, and human risk factors validation requirements for financial entities.
• EU AI Act Article 15 Provides independent adversarial testing validation of AI detection systems with documented results.
• SOX Section 404 Validates internal controls against AI-powered financial fraud with third-party attestation for audit documentation.
• NIST CSF ID.RA & DE.CM Addresses risk assessment with quantifiable Deepfake Resilience Scores and continuous monitoring validation.
• SOC 2 CC3.2 & CC7.2 Provides evidence for risk identification and security incident detection control effectiveness.

Agentic AI Simulation Platform

Scalable AI simulation for partners and enterprises. Multi-tenant architecture enables deployment across partner networks, portfolio companies, and distributed organizations with centralized compliance reporting.

• NIS2 Article 21(2) Enables supply chain security testing across partner networks at scale.
• DORA Article 8 Supports ICT risk management with continuous, automated scenario-based testing.
• NIST AI RMF MEASURE 2.6 Validates AI detection system accuracy with statistical benchmarking across deployments.
• FedRAMP AT-2 & IR-3 Delivers independent assessment reports suitable for continuous monitoring requirements.
• ISO 27001 Annex A 8.8 Tests technical vulnerability management against AI-generated attack vectors across the technology stack.
• HIPAA 164.308(a)(5) Provides healthcare-specific social engineering scenarios targeting PHI access with compliance documentation.

Managed Awareness & Training Programs

Continuous, measured security education that satisfies the "ongoing" and "regular" training requirements mandated across every major framework. Monthly simulations with adaptive learning produce the documentation auditors need.

• NIS2 Article 20 Delivers ongoing cybersecurity training for management and staff with monthly simulation reports and completion metrics.
• DORA Article 13(6) Meets ICT incident management training obligations with annual reports including completion rates and performance analytics.
• ISO 27001 Annex A 6.3 Satisfies awareness, education, and training requirements with measurable, adaptive learning programs and dashboard documentation.
• SOC 2 CC1.4 Documents security awareness program participation with completion metrics and improvement tracking for audit evidence.
• NIST CSF GV.AT & PR.AT Fulfills training requirements with ongoing measurement, trend data, and AI-specific threat scenario coverage.
• HIPAA 164.308(a)(6) Addresses security incident procedure testing with documented training on deepfake detection and escalation protocols.

The Bottom Line

Layer 7 is the new perimeter. Compliance frameworks know it. Your auditors know it. The question is whether your security program has caught up.

Every dollar invested in endpoint protection, network segmentation, and zero trust architecture is irrelevant when an adversary bypasses all of it with a deepfake voice clone and a spoofed Zoom call. The compliance frameworks are evolving to reflect this reality. Your testing needs to evolve with them.

At Breacher.ai, we run the same AI-powered social engineering attacks that nation-state threat actors are deploying in the wild, against Fortune 500 security teams, in controlled environments that produce the empirical data and compliance documentation your organization needs. We test people, processes, and technology simultaneously, because that's how real adversaries operate, and that's what modern compliance frameworks demand.