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Showing 20 results · Page 2 for “EC-Council”. More results are available below.
CCISO · Security foundations
Confidentiality limits who can see information, integrity protects against unauthorized changes, and availability keeps services usable. A control may support several objectives, but the imm…
CEH · Network protection
A network rule should express a justified communication path with the necessary source, destination, protocol and service. Segmentation limits how far a compromise can spread, but only when …
CEH · Authorized penetration testing
A penetration test starts with explicit scope, permitted techniques, timing and stop conditions. These boundaries protect operations and make results interpretable. Demonstrate the impact ne…
CEH · Web application security
Browser-side checks improve usability but can be bypassed. The server must validate input and authorize the requested operation on the specific object. Keep data separate from executable que…
CHFI · Digital evidence
Digital evidence is useful only when its origin and handling can be explained. Record collection details, preserve originals where appropriate, and analyze controlled copies. Hashes can help…
CHFI · Traffic analysis
A packet capture records traffic visible at a particular point, so its location and timing affect what it can prove. Follow the conversation across requests, responses, retransmissions and r…
CHFI · Security findings and communication
A useful security finding connects an affected asset, the observed weakness, the conditions for exploitation and the resulting impact. Include enough reproducible evidence to verify the conc…
CND · Risk assessment and treatment
Risk combines the possibility of an unwanted event with its consequences for an objective. Identify the asset, threat and conditions before choosing a response. Controls may reduce likelihoo…
CND · Security architecture
A trust boundary is where data or actions cross between components with different security assumptions. Map those crossings and require appropriate validation, identity checks and authorizat…
CND · Security foundations
Confidentiality limits who can see information, integrity protects against unauthorized changes, and availability keeps services usable. A control may support several objectives, but the imm…
COASP · AI security boundaries
This concept review develops the reasoning needed for ai security boundaries. Start by identifying the relevant assets, permissions, evidence and trust boundaries. Distinguish what the obser…
COASP · Generative AI systems
A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…
COASP · Responsible AI evaluation
Aggregate accuracy can hide poor performance for particular users or situations. Evaluate representative subgroups and realistic failure cases, and consider privacy, misuse and human oversig…
CPENT · Active Directory assessment concepts
This concept review develops the reasoning needed for active directory assessment concepts. Start by identifying the relevant assets, permissions, evidence and trust boundaries. Distinguish …
CPENT · Authorized penetration testing
A penetration test starts with explicit scope, permitted techniques, timing and stop conditions. These boundaries protect operations and make results interpretable. Demonstrate the impact ne…
CPENT · Security findings and communication
A useful security finding connects an affected asset, the observed weakness, the conditions for exploitation and the resulting impact. Include enough reproducible evidence to verify the conc…
CPENT · Web assessment reasoning
This concept review develops the reasoning needed for web assessment reasoning. Start by identifying the relevant assets, permissions, evidence and trust boundaries. Distinguish what the obs…
CRAGE · AI security boundaries
This concept review develops the reasoning needed for ai security boundaries. Start by identifying the relevant assets, permissions, evidence and trust boundaries. Distinguish what the obser…
CRAGE · Generative AI systems
A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…
CRAGE · Responsible AI evaluation
Aggregate accuracy can hide poor performance for particular users or situations. Evaluate representative subgroups and realistic failure cases, and consider privacy, misuse and human oversig…
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