ECCouncil Updated 312-50v13 Exam Questions and Answers by evie-mae

The scenario describes a wireless discovery method where the tester only listens to the airwaves and does not transmit probe requests or inject frames. In CEH terms, this is passive reconnaissance, commonly referred to as passive footprinting in the wireless context. Passive footprinting relies on capturing and analyzing existing 802.11 management traffic such as beacon frames (periodically broadcast by access points) and probe responses sent to other clients, allowing the tester to identify SSIDs, BSSIDs (MAC addresses of access points), channel numbers, supported data rates, and sometimes security capabilities, all without generating traffic that could alert administrators or trigger wireless intrusion detection systems.

Active footprinting, by contrast, involves transmitting frames—most notably probe requests—to solicit probe responses from access points, which increases detectability. The question explicitly says Ethan does not send probe requests and does not inject data packets, which rules out active methods. “Network Discovery Software” is too generic; tools can be used for either passive or active discovery, but the technique in use is defined by behavior on the wireless medium, not the presence of software. “Wash” is a specific tool/command associated with enumerating WPS-enabled access points; while it can be used during reconnaissance, the question is testing the broader technique rather than a specific utility, and the defining characteristic here is silent listening.

CEH defensive guidance notes that passive discovery is stealthier because it leverages normal beaconing behavior. Organizations mitigate reconnaissance by using wireless monitoring, rogue AP detection, strong encryption configurations, disabling unnecessary broadcasts where feasible, and maintaining continuous wireless security assessments.

CEH explains that MAC flooding overwhelms a switch’s CAM table, causing it to fail open. When the table fills, the switch broadcasts frames out all ports, behaving like a hub. This exposes unicast traffic to attackers operating in promiscuous mode.

Comprehensive Explanation from CEH v13 Courseware:

CEH v13 describes worms as standalone malicious programs capable of self-replication without requiring user assistance. Unlike viruses, which need a host file and are triggered typically by user actions, worms propagate autonomously by scanning networks, exploiting vulnerabilities, or copying themselves to accessible machines. Worms are known for causing rapid, widespread damage by consuming bandwidth, degrading system performance, and creating backdoors for attackers. Classic examples such as Conficker, WannaCry, and SQL Slammer reinforce the destructive potential of automated propagation. CEH stresses that worms often use network shares, open ports, or unpatched vulnerabilities to move laterally. In contrast, keyloggers harvest keystrokes, ransomware encrypts data and demands payment, and viruses require user involvement to spread. The behavior in the scenario—automatic replication across the network—is the defining characteristic of worm activity according to CEH’s malware taxonomy.

The highest-priority proactive control “to embed into the organization’s development lifecycle” is including quantum-resistance checks in the SDLC and code review processes. The scenario emphasizes a company-wide, long-term risk reduction strategy while development continues on a major refactor. In that context, the most scalable and durable control is governance and engineering hygiene: ensuring that new features and refactored components do not reintroduce weak or legacy cryptography and that teams consistently select algorithms and key sizes aligned with modern guidance and future migration plans.

Embedding checks into the SDLC means instituting standards and guardrails such as approved cryptographic libraries, banned algorithm lists (e.g., legacy RSA key sizes, deprecated curves, weak hashes), cryptography design reviews, automated dependency scanning for crypto usage, and CI/CD policy gates that flag noncompliant implementations. This approach reduces “crypto sprawl,” prevents new technical debt, and creates a structured path to transition toward post-quantum or quantum-resistant approaches as the organization modernizes systems.

Why the other choices are not the best “highest priority” SDLC-embedded control:

Encrypt stored data with quantum-resistant algorithms (B) may be appropriate for protecting long-lived sensitive data (“harvest now, decrypt later”), but it is a targeted technical control and may not be feasible immediately across many services during refactoring. It also does not by itself prevent developers from continuing to implement legacy public-key schemes elsewhere.

Quantum-specific firewalls (C) is not a realistic or standard control for post-quantum readiness in typical enterprise environments.

Fragmenting data across locations (D) can help resilience/confidentiality in some designs but does not address the core issue: preventing continued reliance on weak public-key cryptography.

Therefore, the best answer is A. Include quantum-resistance checks in SDLC and code review processes.