Certified in Cybersecurity Certification Exam Outline

1.1 - Understand the security concepts of information assurance

• Confidentiality
• Integrity
• Availability
• Authentication (e.g., methods of authentication, multi-factor authentication (MFA))
• Non-repudiation
• Privacy

1.2 - Understand the risk management process

• Risk management (e.g., risk priorities, risk tolerance)
• Risk identification, assessment and treatment

1.3 - Understand security controls

• Technical controls
• Administrative controls
• Physical controls

1.4 - Understand ISC2 Code of Ethics

• Professional code of conduct

1.5 - Understand governance processes

• Policies
• Procedures
• Standards
• Regulations and laws

2.1 - Understand business continuity (BC)

• Purpose
• Importance
• Components

2.2 - Understand disaster recovery (DR)

• Purpose
• Importance
• Components

2.3 - Understand incident response

• Purpose
• Importance
• Components

3.1 - Understand physical access controls

• Physical security controls (e.g., badge systems, gate entry, environmental design)
• Monitoring (e.g., security guards, closed-circuit television (CCTV), alarm systems, logs)
• Authorized versus unauthorized personnel

3.2 - Understand logical access controls

• Principle of least privilege
• Segregation of duties
• Discretionary access control (DAC)
• Mandatory access control (MAC)
• Role-based access control (RBAC)

4.1 - Understand computer networking

• Networks (e.g., Open Systems Interconnection (OSI) model, Transmission Control Protocol/Internet Protocol (TCP/IP) model, Internet Protocol version 4 (IPv4), Internet Protocol version 6 (IPv6), WiFi)
• Ports
• Applications

4.2 - Understand network threats and attacks

• Types of threats (e.g., distributed denial-of-service (DDoS), virus, worm, Trojan, man-in-the-middle (MITM), side-channel)
• Identification (e.g., intrusion detection system (IDS), host-based intrusion detection system (HIDS), network intrusion detection system (NIDS))
• Prevention (e.g., antivirus, scans, firewalls, intrusion prevention system (IPS))

4.3 - Understand network security infrastructure

• On-premises (e.g., power, data center/closets, Heating, Ventilation, and Air Conditioning (HVAC), environmental, fire suppression, redundancy, memorandum of understanding (MOU)/memorandum of agreement (MOA))
• Design (e.g., network segmentation (demilitarized zone (DMZ), virtual local area network (VLAN), virtual private network (VPN), micro-segmentation), defense in depth, Network Access Control (NAC) (segmentation for embedded systems, Internet of Things (IoT))
• Cloud (e.g., service-level agreement (SLA), managed service provider (MSP), Software as a Service (SaaS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS), hybrid)

5.1 - Understand data security

• Encryption (e.g., symmetric, asymmetric, hashing)
• Data handling (e.g., destruction, retention, classification, labeling)
• Logging and monitoring security events

5.2 - Understand system hardening

• Configuration management (e.g., baselines, updates, patches)

5.3 - Understand best practice security policies

• Data handling policy
• Password policy
• Acceptable Use Policy (AUP)
• Bring your own device (BYOD) policy
• Change management policy (e.g., documentation, approval, rollback)
• Privacy policy

5.4 - Understand security awareness training

• Purpose/concepts (e.g., social engineering, password protection)
• Importance

At the foundational level, the CC Exam Outline introduces how AI impacts the core pillars of information security: Confidentiality, Integrity and Availability. Entry level professionals understand how to apply the fundamental security principles to AI systems, specifically focusing on how data integrity is vital for preventing “model poisoning.” The integration also covers the ethical use of AI, highlighting the importance of transparency and non bias in automated decision making as part of a comprehensive security culture.

Furthermore, this domain establishes the role of AI within the broader governance, risk and compliance (GRC) landscape. Candidates are aware that AI tools are subject to the same organizational policies and legal requirements as traditional software. By understanding these high level principles, new practitioners can support senior leadership in ensuring that AI adoption aligns with the organization’s risk appetite and ethical standards.

In this domain, the CC Exam Outline incorporates how AI both complicates and enhances the resilience of an organization. From a response perspective, candidates understand the basics of how AI driven tools can assist in the early detection of security incidents. The CC Exam Outline emphasizes the role of the entry level practitioner in following established playbooks that now account for automated threats, ensuring they can provide valuable support during the initial triage of a suspected breach.

Regarding recovery and continuity, the integration focuses on the necessity of backing up not just traditional data, but the specific configurations and datasets that power AI services. The CC Exam Outline includes the concept of “Model Drift” as a potential business continuity risk, where an AI’s declining performance could impact critical operations. By using these concepts, CC holders are prepared to assist in maintaining the availability of intelligent systems during and after a disruptive event.

Access control is the first line of defense. Candidates understand that just like human users, AI “bots” and automated service accounts must be managed through a formal lifecycle—from provisioning to deprovisioning. The integration emphasizes the Principle of Least Privilege, allowing entry-level staff to verify that automated systems only have the permissions necessary to perform their designated tasks.

Additionally, the CC Exam Outline includes how AI is used to strengthen authentication through behavioral analysis. Candidates understand the foundational concepts of Multi-Factor Authentication (MFA) and how AI can help detect “impossible travel” or anomalous login patterns. This ensures that new professionals understand both how to secure the AI’s access and how AI serves as a silent partner in protecting user identities across the enterprise.

For network security, the CC Exam Outline incorporates the basics of how AI influences traffic monitoring and threat prevention. Entry-level practitioners understand the concept of AI-powered firewalls and Intrusion Detection Systems (IDS) that go beyond simple signature matching. By understanding how these tools use machine learning to identify unusual network behavior, candidates are better equipped to monitor dashboards and report potential anomalies to senior analysts.

The integration also addresses the security of the pathways that AI data travels. The CC Exam Outline describes the importance of network segmentation to keep AI development environments isolated from sensitive production data. This foundational knowledge allows CC professionals to support the implementation of Zero Trust principles, ensuring that the network remains a secure environment for the transmission of high-value AI training data.

In the final domain, the CC Exam Outline focuses on the day-to-day tasks of a security professional working alongside AI. This includes the foundational understanding of how Security Information and Event Management (SIEM) tools use AI to correlate data and reduce “alert fatigue.” Candidates know how to handle the outputs of these automated systems, ensuring they can distinguish between a routine automated block and a high-priority event that requires human intervention.

We also introduce the “Security of the AI Workspace,” focusing on the safe use of web-based AI tools and LLMs in an office environment. Candidates are prepared to identify the risks of “Data Leakage” when employees interact with public AI services. Subtasks within this domain ensure that candidates can serve as effective “human firewalls,” protecting the organization’s data integrity in an increasingly automated world.