CISSP Certification Exam Outline Summary

1.1 - Understand, adhere to, and promote professional ethics

• ISC2 Code of Professional Ethics
• Organizational code of ethics

1.2 - Understand and apply security concepts

• Confidentiality, integrity, and availability, authenticity, and nonrepudiation (5 Pillars of Information Security)

1.3 - Evaluate and apply security governance principles

• Alignment of the security function to business strategy, goals, mission, and objectives
• Organizational processes (e.g., acquisitions, divestitures, governance committees)
• Organizational roles and responsibilities
• Security control frameworks (e.g., International Organization for Standardization (ISO), National Institute of Standards and Technology (NIST), Control Objectives for Information and Related Technology (COBIT), Sherwood Applied Business Security Architecture (SABSA), Payment Card Industry (PCI), Federal Risk and Authorization Management Program (FedRAMP))
• Due care/due diligence

1.4 - Understand legal, regulatory, and compliance issues that pertain to information security in a holistic context

• Cybercrimes and data breaches
• Licensing and Intellectual Property requirements
• Import/export controls
• Transborder data flow
• Issues related to privacy (e.g., General Data Protection Regulation (GDPR), California Consumer Privacy Act, Personal Information Protection Law, Protection of Personal Information Act)
• Contractual, legal, industry standards, and regulatory requirements

1.5 - Understand requirements for investigation types (i.e., administrative, criminal, civil, regulatory, industry standards)

1.6 - Develop, document, and implement security policy, standards, procedures, and guidelines

1.7 - Identify, analyze, assess, prioritize, and implement Business Continuity (BC) requirements

• Business impact analysis (BIA)
• External dependencies

1.8 - Contribute to and enforce personnel security policies and procedures

• Candidate screening and hiring
• Employment agreements and policy driven requirements
• Onboarding, transfers, and termination processes
• Vendor, consultant, and contractor agreements and controls

1.9 - Understand and apply risk management concepts

• Threat and vulnerability identification
• Risk analysis, assessment, and scope
• Risk response and treatment (e.g., cybersecurity insurance)
• Applicable types of controls (e.g., preventive, detection, corrective)
• Control assessments (e.g., security and privacy)
• Continuous monitoring and measurement
• Reporting (e.g., internal, external)
• Continuous improvement (e.g., risk maturity modeling)
• Risk frameworks (e.g., International Organization for Standardization (ISO), National Institute of Standards and Technology (NIST), Control Objectives for Information and Related Technology (COBIT), Sherwood Applied Business Security Architecture (SABSA), Payment Card Industry (PCI))

1.10 - Understand and apply threat modeling concepts and methodologies

1.11 - Apply Supply Chain Risk Management (SCRM) concepts

• Risks associated with the acquisition of products and services from suppliers and providers (e.g., product tampering, counterfeits, implants)
• Risk mitigations (e.g., third-party assessment and monitoring, minimum security requirements, service level requirements, silicon root of trust, physically unclonable function, software bill of materials)

1.12 - Establish and maintain a security awareness, education, and training program

• Methods and techniques to increase awareness and training (e.g., social engineering, phishing, security champions, gamification)
• Periodic content reviews to include emerging technologies and trends (e.g., cryptocurrency, artificial intelligence (AI), blockchain)
• Program effectiveness evaluation

2.1 - Identify and classify information and assets

• Data classification
• Asset Classification

2.2 - Establish information and asset handling requirements

2.3 - Provision information and assets securely

• Information and asset ownership
• Asset inventory (e.g., tangible, intangible)
• Asset management

2.4 - Manage data lifecycle

• Data roles (i.e., owners, controllers, custodians, processors, users/subjects)
• Data collection
• Data location
• Data maintenance
• Data retention
• Data remanence
• Data destruction

2.5 - Ensure appropriate asset retention (e.g., End of Life (EOL), End of Support)

2.6 - Determine data security controls and compliance requirements

• Data states (e.g., in use, in transit, at rest)
• Scoping and tailoring
• Standards selection
• Data protection methods (e.g., Digital Rights Management (DRM), Data Loss Prevention (DLP), Cloud Access Security Broker (CASB))

3.1 - Research, implement and manage engineering processes using secure design principles

• Threat modeling
• Least privilege
• Defense in depth
• Secure defaults
• Fail securely
• Segregation of Duties (SoD)
• Keep it simple and small
• Zero trust or trust but verify
• Privacy by design
• Shared responsibility
• Secure access service edge

3.2 - Understand the fundamental concepts of security models (e.g., Biba, Star Model, Bell-LaPadula)

3.3 - Select controls based upon systems security requirements

3.4 - Understand security capabilities of Information Systems (IS) (e.g., memory protection, Trusted Platform Module (TPM), encryption/decryption)

3.5 - Assess and mitigate the vulnerabilities of security architectures, designs, and solution elements

• Client-based systems
• Server-based systems
• Database systems
• Cryptographic systems
• Industrial Control Systems (ICS)
• Cloud-based systems (e.g., Software as a Service (SaaS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS))
• Distributed systems
• Internet of Things (IoT)
• Microservices (e.g., application programming interface (API))
• Containerization
• Serverless
• Embedded systems
• High-Performance Computing systems
• Edge computing systems
• Virtualized systems

3.6 - Select and determine cryptographic solutions

• Cryptographic life cycle (e.g., keys, algorithm selection)
• Cryptographic methods (e.g., symmetric, asymmetric, elliptic curves, quantum)
• Public key infrastructure (PKI) (e.g., quantum key distribution)

3.7 - Understand methods of cryptanalytic attacks

• Brute force
• Ciphertext only
• Known plaintext
• Frequency analysis
• Chosen ciphertext
• Implementation attacks
• Side-channel
• Fault injection
• Timing
• Man-in-the-Middle (MITM)
• Pass the hash
• Kerberos exploitation
• Ransomware

3.8 - Apply security principles to site and facility design

3.9 - Design site and facility security controls

• Wiring closets/intermediate distribution facilities
• Server rooms/data centers
• Media storage facilities
• Evidence storage
• Restricted and work area security
• Utilities and Heating, Ventilation, and Air Conditioning (HVAC)
• Environmental issues (e.g., natural disasters, man-made)
• Fire prevention, detection, and suppression
• Power (e.g., redundant, backup)

3.10 - Manage the information system lifecycle

• Stakeholders needs and requirements
• Requirements analysis
• Architectural design
• Development /implementation
• Integration
• Verification and validation
• Transition/deployment
• Operations and maintenance/sustainment
• Retirement/disposal

4.1 - Apply secure design principles in network architectures

• Open System Interconnection (OSI) and Transmission Control Protocol/Internet Protocol (TCP/IP) models
• Internet Protocol (IP) version 4 and 6 (IPv6) (e.g., unicast, broadcast, multicast, anycast)
• Secure protocols (e.g., Internet Protocol Security (IPSec), Secure Shell (SSH), Secure Sockets Layer (SSL)/ Transport Layer Security (TLS))
• Implications of multilayer protocols
• Converged protocols (e.g., Internet Small Computer Systems Interface (iSCSI), Voice over Internet Protocol (VoIP), InfiniBand over Ethernet, Compute Express Link)
• Transport architecture (e.g., topology, data/control/management plane, cut-through/store-and-forward)
• Performance metrics (e.g., bandwidth, latency, jitter, throughput, signal-to-noise ratio)
• Traffic flows (e.g., north-south, east-west)
• Physical segmentation (e.g., in-band, out-of-band, air-gapped)
• Logical segmentation (e.g., virtual local area networks (VLANs), virtual private networks (VPNs), virtual routing and forwarding, virtual domain)
• Micro-segmentation (e.g., network overlays/encapsulation; distributed firewalls, routers, intrusion detection system (IDS)/intrusion prevention system (IPS), zero trust)
• Edge networks (e.g., ingress/egress, peering)
• Wireless networks (e.g., Bluetooth, Wi-Fi, Zigbee, satellite)
• Cellular/mobile networks (e.g., 4G, 5G)
• Content distribution networks (CDN)
• Software defined networks (SDN), (e.g., application programming interface (API), Software-Defined Wide- Area Network, network functions virtualization)
• Virtual Private Cloud (VPC)
• Monitoring and management (e.g., network observability, traffic flow/shaping, capacity management, fault detection and handling)

4.2 - Secure network components

• Operation of infrastructure (e.g., redundant power, warranty, support)
• Transmission media (e.g., physical security of media, signal propagation quality)
• Network Access Control (NAC) systems (e.g., physical, and virtual solutions)
• Endpoint security (e.g., host-based)

4.3 - Implement secure communication channels according to design

• Voice, video, and collaboration (e.g., conferencing, Zoom rooms)
• Remote access (e.g., network administrative functions)
• Data communications (e.g., backhaul networks, satellite)
• Third-party connectivity (e.g., telecom providers, hardware support)

5.1 - Control physical and logical access to assets

• Information
• Systems
• Devices
• Facilities
• Applications
• Services

5.2 - Design identification and authentication strategy (e.g., people, devices, and services)

• Groups and Roles
• Authentication, Authorization and Accounting (AAA) (e.g., multi-factor authentication (MFA), password-less authentication)
• Session management
• Registration, proofing, and establishment of identity
• Federated Identity Management (FIM)
• Credential management systems (e.g., Password vault)
• Single sign-on (SSO)
• Just-In-Time

5.3 - Federated identity with a third-party service

• On-premise
• Cloud
• Hybrid

5.4 - Implement and manage authorization mechanisms

• Role-based access control (RBAC)
• Rule based access control
• Mandatory access control (MAC)
• Discretionary access control (DAC)
• Attribute-based access control (ABAC)
• Risk based access control
• Access policy enforcement (e.g., policy decision point, policy enforcement point)

5.5 - Manage the identity and access provisioning lifecycle

• Account access review (e.g., user, system, service)
• Provisioning and deprovisioning (e.g., on /off boarding and transfers)
• Role definition and transition (e.g., people assigned to new roles)
• Privilege escalation (e.g., use of sudo, auditing its use)
• Service accounts management

5.6 - Implement authentication systems

6.1 - Design and validate assessment, test, and audit strategies

• Internal (e.g., within organization control)
• External (e.g., outside organization control)
• Third-party (e.g., outside of enterprise control)
• Location (e.g., on-premises, cloud, hybrid)

6.2 - Conduct security control testing

• Vulnerability assessment
• Penetration testing (e.g., red, blue, and/or purple team exercises)
• Log reviews
• Synthetic transactions/benchmarks
• Code review and testing
• Misuse case testing
• Coverage analysis
• Interface testing (e.g., user interface, network interface, application programming interface (API))
• Breach attack simulations
• Compliance checks

6.3 - Collect security process data (e.g., technical and administrative)

• Account management
• Management review and approval
• Key performance and risk indicators
• Backup verification data
• Training and awareness
• Disaster Recovery (DR) and Business Continuity (BC)

6.4 - Analyze test output and generate report

• Remediation
• Exception handling
• Ethical disclosure

6.5 - Conduct or facilitate security audits

• Internal (e.g., within organization control)
• External (e.g., outside organization control)
• Third-party (e.g., outside of enterprise control)
• Location (e.g., on-premises, cloud, hybrid)

7.1 - Understand and comply with investigations

• Evidence collection and handling
• Reporting and documentation
• Investigative techniques
• Digital forensics tools, tactics, and procedures
• Artifacts (e.g., data, computer, network, mobile device)

7.2 - Conduct logging and monitoring activities

• Intrusion detection and prevention (IDPS)
• Security Information and Event Management (SIEM)
• Continuous monitoring and tuning
• Egress monitoring
• Log management
• Threat intelligence (e.g., threat feeds, threat hunting)
• User and Entity Behavior Analytics (UEBA)

7.3 - Perform Configuration Management (CM) (e.g., provisioning, baselining, automation)

7.4 - Apply foundational security operations concepts

• Need-to-know/least privilege
• Separation of Duties (SoD) and responsibilities
• Privileged account management
• Job rotation
• Service-level agreements (SLA)

7.5 - Apply resource protection

• Media management
• Media protection techniques
• Data at rest/data in transit

7.6 - Conduct incident management

• Detection
• Response
• Mitigation
• Reporting
• Recovery
• Remediation
• Lessons learned

7.7 - Operate and maintain detection and preventative measures

• Firewalls (e.g., next generation, web application, network)
• Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS)
• Whitelisting/blacklisting
• Third-party provided security services
• Sandboxing
• Honeypots/honeynets
• Anti-malware
• Machine learning and Artificial Intelligence (AI) based tools

7.8 - Implement and support patch and vulnerability management

7.9 - Understand and participate in change management processes

7.10 - Implement recovery strategies

• Backup storage strategies (e.g., cloud storage, onsite, offsite)
• Recovery site strategies (e.g., cold vs. hot, resource capacity agreements)
• Multiple processing sites
• System resilience, high availability (HA), Quality of Service (QoS), and fault tolerance

7.11 - Implement Disaster Recovery (DR) processes

• Response
• Personnel
• Communications (e.g., methods)
• Assessment
• Restoration
• Training and awareness
• Lessons learned

7.12 - Test Disaster Recovery Plans (DRP)

• Read-through/tabletop
• Walkthrough
• Simulation
• Parallel
• Full interruption
• Communications (e.g., stakeholders, test status, regulators)

7.13 - Participate in Business Continuity (BC) planning and exercises

7.14 - Implement and manage physical security

• Perimeter security controls
• Internal security controls

7.15 - Address personnel safety and security concerns

• Travel
• Security training and awareness (e.g., insider threat, social media impacts, two-factor authentication (2FA) fatigue)
• Emergency management
• Duress

8.1 - Understand and integrate security in the Software Development Life Cycle (SDLC)

• Development methodologies (e.g., Agile, Waterfall, DevOps, DevSecOps, Scaled Agile Framework)
• Maturity models (e.g., Capability Maturity Model (CMM), Software Assurance Maturity Model (SAMM))
• Operation and maintenance
• Change management
• Integrated Product Team

8.2 - Identify and apply security controls in software development ecosystems

• Programming languages
• Libraries
• Tool sets
• Integrated Development Environment
• Runtime
• Continuous Integration and Continuous Delivery (CI/CD)
• Software configuration management (CM)
• Code repositories
• Application security testing (e.g., static application security testing (SAST), dynamic application security testing (DAST), software composition analysis, Interactive Application Security Test (IAST))

8.3 - Assess the effectiveness of software security

• Auditing and logging of changes
• Risk analysis and mitigation

8.4 - Assess security impact of acquired software

• Commercial-off-the-shelf (COTS)
• Open source
• Third-party
• Managed services (e.g., enterprise applications)
• Cloud services (e.g., Software as a Service (SaaS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS))

8.5 - Define and apply secure coding guidelines and standards

• Security weaknesses and vulnerabilities at the source-code level
• Security of application programming interfaces (API)
• Secure coding practices
• Software-defined security

Security leadership now requires a deep understanding of how AI assets shift the organizational risk posture. Within this domain, the CISSP Exam Outline emphasizes the integration of ML models and LLMs into existing risk management frameworks. This includes establishing governance for AI ethics and mitigating algorithmic bias, ensuring that automated decision-making processes align with legal, regulatory and privacy requirements.

Furthermore, AI integration touches upon third-party risk management. As organizations increasingly rely on external AI service providers, CISSPs must be equipped to evaluate the security of AI supply chains. This involves assessing the transparency of data sourcing and the resilience of provider-managed models against evolving threats, ensuring that AI adoption does not create unmanaged blind spots in the corporate security strategy.

In the realm of asset security, data is the lifeblood of AI, and its protection is paramount. This domain now covers the classification and handling of AI-specific assets, such as training datasets, pre-trained models and model weights. We focus on maintaining data integrity throughout the AI lifecycle, ensuring that the information used to “teach” these systems has not been tampered with or poisoned by malicious actors.

Privacy remains a cornerstone of this domain, specifically regarding how AI systems process Personally Identifiable Information (PII). Integration efforts focus on technical controls like differential privacy and data masking within AI environments. By treating ML models as high-value intellectual property, we provide a roadmap for managing the collection, storage and eventual destruction of data in a way that satisfies both security and privacy mandates.

The architecture and engineering domain addresses the structural defenses required to host and run AI safely. This includes the design of secure enclaves for high-performance AI compute and the implementation of robust input-validation mechanisms to defend against prompt injection and adversarial attacks. The CISSP Exam Outline integrates AI by looking at the shared responsibility models inherent in cloud-based AI services, ensuring the underlying infrastructure is resilient to the unique computational demands of neural networks.

Beyond physical and logical hosting, this domain includes the engineering of “Explainable AI” as a security requirement. By building systems that provide transparency into how they reached a specific output, security engineers can better audit AI behavior. This integration ensures that security architecture isn’t just a perimeter around a system, but a transparent framework that supports the verification and validation of AI-driven security controls.

As AI workloads move across the network, this domain focuses on securing the transit of massive datasets and the communication between distributed AI nodes. Integration involves implementing specialized micro-segmentation and Zero Trust Architecture (ZTA) to isolate AI training environments from the rest of the enterprise network. This prevents lateral movement in the event of a compromised AI interface.

Additionally, we address the role of AI in network defense. CISSPs are tasked with understanding how AI-driven Network Detection and Response (NDR) tools identify anomalous traffic patterns that traditional signature-based systems might miss. By securing the channels used for “inference at the edge,” we ensure that the communication pathways supporting AI remain confidential and available.

Identity remains the primary perimeter in an AI-driven world. Within Domain 5, the CISSP Exam Outline focuses on managing identities for non-human entities, specifically AI agents and automated service accounts. This integration ensures that AI systems operate under the Principle of Least Privilege, preventing “privilege escalation” where an AI might gain unauthorized access to sensitive data repositories during its learning or execution phase.

The CISSP Exam Outline also incorporates the use of AI to enhance IAM through behavioral biometrics and adaptive authentication. By leveraging AI to analyze user login patterns and detect anomalies in real-time, CISSPs can implement more dynamic access controls. This dual focus ensures that while we secure the AI’s identity, we also use AI to make the entire organization’s identity infrastructure more resilient.

Security testing must now evolve to include “Red Teaming” for AI systems. Within this domain, the CISSP Exam Outline integrates methodologies for testing model robustness against evasion and extraction attacks. Professionals audit AI systems not just for software bugs, but for “logic flaws” in the model’s output that could be exploited by an adversary.

Furthermore, we address the use of AI to automate the vulnerability management lifecycle. By integrating AI-powered scanning tools, organizations can prioritize remediation efforts based on real-time threat intelligence. This ensures that security assessments are continuous rather than point-in-time, allowing for the rapid identification of vulnerabilities in both traditional code and complex ML architectures.

In the Security Operations Center (SOC), AI is a force multiplier. This domain focuses on the integration of AI and ML into Security Orchestration, Automation and Response (SOAR) platforms. The CISSP Exam Outline addresses how to manage “Alert Fatigue” by using AI to correlate disparate events and provide high-fidelity context to security analysts, allowing for faster incident response.

Operationally, we also cover the “Security of AI” during the production phase. This includes monitoring for “Model Drift”—where an AI’s performance degrades over time—and responding to live adversarial attacks. By blending traditional incident response with AI-specific monitoring, CISSPs ensure that the organization’s operational resilience keeps pace with the speed of automated threats.

As AI transforms how code is written, Domain 8 has evolved to secure the modern development lifecycle. The CISSP Exam Outline incorporates the use of AI-assisted coding tools, focusing on the risks of “hallucinated” vulnerabilities or the accidental inclusion of insecure code snippets generated by LLMs. The focus is on integrating automated AI security testing into the CI/CD pipeline to catch these flaws before they reach production.

Additionally, this domain addresses the security of the software supply chain as it pertains to ML libraries and frameworks. Professionals are tasked with identifying and mitigating “Model Hijacking” or “Inference Attacks” that target the software layer. By embedding AI considerations into the Software Development Life Cycle (SDLC), we ensure that developers can leverage the efficiency of AI without compromising the integrity of the finished product.