CBROPS - Understanding Cisco Cybersecurity Operations Fundamentals
Articles covering Cisco CyberOps Associate (CBROPS 200-201) exam objectives. These guides focus on security operations fundamentals, monitoring, host and network analysis, and incident response.
CBROPS Objective 1.1: Describe the CIA Triad
Master the foundational CIA triad: confidentiality protecting data with encryption and access controls, integrity ensuring accuracy with hashing and digital signatures, availability maintaining uptime with redundancy and DDoS protection, balancing trade-offs, and understanding threats to each principle.
CBROPS Objective 1.2: Compare Security Deployments
Compare security deployment models: network security (firewalls, IPS, WAF), endpoint protection (EDR, agents), application security (SAST, DAST, RASP), agent-based vs agentless monitoring, antivirus evolution, SIEM/SOAR for threat detection and response automation, container and virtual environment security, and cloud security (CSPM, CASB, shared responsibility).
CBROPS Objective 1.3: Describe Security Terms
Master essential security terminology: threat intelligence (IOCs, TTPs, strategic/tactical/operational), threat hunting (hypothesis-driven proactive investigation), malware analysis (static and dynamic techniques), threat actors (nation-states, cybercriminals, hacktivists, insiders), runbook automation (RBA), reverse engineering, sliding window anomaly detection, threat modeling (STRIDE), and DevSecOps.
CBROPS Objective 1.4: Compare Security Concepts
Compare fundamental security concepts: risk assessment (qualitative matrices and quantitative SLE/ARO/ALE calculations), risk scoring with CVSS (base, temporal, environmental metrics), risk reduction strategies (mitigation, avoidance, transfer, acceptance), threats as potential danger sources, vulnerabilities as exploitable weaknesses, and exploits as attack methods leveraging vulnerabilities.
CBROPS Objective 1.5: Describe the Principles of the Defense-in-Depth Strategy
Master defense-in-depth principles implementing layered security across physical security, perimeter defense (firewalls, IPS, DMZ), network security (segmentation, VLANs, zero trust), endpoint protection (EDR, hardening, whitelisting), application security (WAF, secure coding), data protection (encryption, DLP), and human layer (awareness training, policies), ensuring redundancy and diversity eliminate single points of failure.
CBROPS Objective 1.6: Compare Access Control Models
Compare access control models: Discretionary Access Control (DAC) where owners control permissions, Mandatory Access Control (MAC) using security labels and clearances, Role-Based Access Control (RBAC) assigning permissions by job function, Attribute-Based Access Control (ABAC) with dynamic attribute policies, rule-based and time-based access control, and AAA framework (Authentication, Authorization, Accounting).
CBROPS Objective 1.7: Describe Terms as Defined in CVSS
Master CVSS (Common Vulnerability Scoring System) metrics: Attack Vector (Network, Adjacent, Local, Physical), Attack Complexity (Low, High), Privileges Required (None, Low, High), User Interaction (None, Required), Scope (Unchanged, Changed), impact metrics (CIA: None/Low/High), Temporal metrics (Exploit Maturity, Remediation Level, Report Confidence), and Environmental metrics customizing scores for organizational context.
CBROPS Objective 1.8: Identify the Challenges of Data Visibility in Detection
Identify data visibility challenges across domains: Network visibility issues (encrypted traffic, high volumes, segmentation blind spots, east-west traffic, cloud virtual networks), Host visibility challenges (endpoint coverage gaps, resource constraints, OS diversity, ephemeral containers), and Cloud visibility complexities (shared responsibility, dynamic infrastructure, API limitations, multi-cloud heterogeneity).
CBROPS Objective 1.9: Identify Potential Data Loss from Traffic Profiles
Identify data exfiltration through traffic profile analysis: Establish baselines (upload/download ratios, protocol distributions, temporal patterns), detect anomalies (unusual volumes, off-hours transfers, uncommon destinations), recognize exfiltration methods (DNS tunneling, HTTPS uploads, cloud storage abuse, email), analyze indicators (beaconing, data staging), and implement detection (DLP, NetFlow, DNS monitoring, SIEM).