ECCouncil Updated 212-89 Exam Questions and Answers by ettie

Comprehensive and Detailed Explanation (ECIH-aligned):

This scenario reflects the post-incident recovery and reporting phase outlined in the ECIH curriculum. After containment and eradication, organizations must address legal, regulatory, and investigative requirements, especially when financial fraud and executive compromise are involved.

Option A is correct because forwarding detailed incident reports to a government cybercrime agency constitutes legal escalation and investigation support. ECIH stresses the importance of cooperation with law enforcement in cases involving fraud, financial loss, or cross-border criminal activity. Proper documentation supports potential prosecution, restitution efforts, and regulatory compliance.

Options B, C, and D are technical recovery actions unrelated to legal follow-up.

By engaging authorities with verified evidence, the organization fulfills its recovery obligations beyond technical remediation, aligning with ECIH best practices.

In a disassociation attack, the attacker sends disassociation frames to a wireless access point (AP) using a spoofed MAC address of a client or to the client pretending to be the AP. This forces the target to disconnect and often reconnect, causing a disruption in the wireless connectivity. Such attacks can be used to create a denial-of-service condition for the client, making the network resource unavailable. The primary objective of this attack is not to eavesdrop but to disrupt the normal operation of the wireless connection between the client and the AP.

Logging User IDs (D) can pose privacy concerns and may conflict with regulations such as the General Data Protection Regulation (GDPR), which emphasizes the protection of personal data and privacy. Therefore, while logging details such as Timestamps, Session IDs, and Source IP addresses are essential for security auditing to track when events occur, who is initiating sessions, and from where, care must be taken with User IDs. The handling of personally identifiable information (PII) must comply with privacy laws and organizational policies to safeguard individual privacy rights.

Generation-based fuzz testing is a strategy where new test data is generated from scratch based on a predefined model that specifies the structure, type, and format of the input data. This approach is systematic and relies on a deep understanding of the format and protocol of the input data to create test cases that are both valid and potentially revealing of vulnerabilities. This contrasts with mutation-based fuzz testing, where existing data samples are modified (mutated) to produce new test cases, and log-based and protocol-based fuzz testing, which use different approaches to test software robustness and security.