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PT0-002 Reconnaissance and Enumeration Practice Question

A penetration tester is performing active reconnaissance on a web application and needs to discover parameters that the application accepts. Which TWO tools are most commonly used for parameter discovery? (Select TWO.)

⚠ Common exam trap

In the CompTIA Pentest+ context, the trap is that candidates often confuse general-purpose web scanners (like Nikto) or CMS-specific tools (like WPScan) with dedicated parameter discovery tools, leading them to select options that perform different reconnaissance tasks.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

ffuf

ffuf (A) is correct because it is a fast web fuzzer that can brute-force URL parameters, directories, and POST data using wordlists, making it a standard tool for parameter discovery during active reconnaissance. Arjun (E) is correct because it is purpose-built for HTTP parameter discovery, using a large built-in wordlist and heuristics to find hidden GET/POST parameters efficiently. theHarvester (B) is not correct because it focuses on OSINT gathering of emails, subdomains, and hosts from public sources rather than discovering application parameters. WPScan (C) is not correct because it targets WordPress-specific vulnerabilities and enumeration, not generic parameter discovery. Nikto (D) is not correct because it is a web server scanner for misconfigurations and known issues, not a parameter brute-forcing tool.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✓

    ffuf

    Why this is correct

    ffuf performs fuzzing by substituting wordlist entries into request positions, detecting accepted parameters through response differences in status codes, length or reflection. This directly satisfies the stem's requirement to discover parameters the application accepts during active reconnaissance, using its `-w` wordlist and filter flags to isolate valid hits.

  • ✗

    theHarvester

    Why it's wrong here

    theHarvester gathers emails, subdomains and hostnames from public sources such as search engines and certificate transparency logs, providing OSINT rather than parameter enumeration. It is tempting during reconnaissance because it maps an organisation's external footprint, but it never interacts with the application's request handling to reveal accepted parameters.

  • ✗

    WPScan

    Why it's wrong here

    WPScan fingerprints WordPress core, plugins and themes for known vulnerabilities; it does not discover arbitrary application parameters. It is tempting because it actively probes a web application and reports findings, but its checks are CMS-specific signatures, whereas parameter discovery requires fuzzing query strings, form fields and headers.

  • ✗

    Nikto

    Why it's wrong here

    Nikto is a web server scanner that reports outdated software, misconfigurations and known vulnerabilities; it does not enumerate application parameters. It is tempting because it performs active reconnaissance against web targets, but its checks target server banners and files, not the query or form parameters the engagement requires.

  • ✓

    Arjun

    Why this is correct

    Arjun brute-forces hidden HTTP parameters using a bundled wordlist, issuing requests with candidate names and flagging those that alter the response. This directly satisfies the stem's requirement to discover parameters the application accepts during active reconnaissance, complementing Burp Suite's parameter-mining capability.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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