Phone Number Detection Scanner

Web applications serve as the primary digital touchpoint between organizations and their customers, partners, and the general public. Contact information including phone numbers is routinely published on corporate websites to facilitate sales inquiries, customer support, technical assistance, and press communication. These numbers appear most commonly in page footers, dedicated contact pages, about pages, and support sections, and are often replicated across multiple subpages through shared templates. Organizations ranging from small businesses to large enterprises publish one or more phone numbers, which may belong to general support lines, regional offices, named individuals, or executive teams. Web applications built on content management systems frequently aggregate contact details across pages without a centralized audit of what is publicly surfaced. The collection of phone numbers from web properties is a standard step in OSINT reconnaissance conducted by both security assessors and malicious actors seeking communication channels into an organization.

Phone number detection refers to the automated identification of contact numbers that are publicly accessible within a web application's HTML content. Numbers may appear in plain text within page bodies, encoded inside anchor tags as tel: links, or embedded within structured contact blocks alongside addresses and email addresses. While publishing a phone number is often intentional and sometimes legally required, the automated aggregation of these numbers at scale creates risks that manual publication does not anticipate. Harvested phone numbers are routinely used as inputs for vishing campaigns, where attackers impersonate trusted organizations to extract credentials, payment details, or sensitive internal information from staff. Role-specific numbers such as those associated with IT support, finance, or executive assistants are particularly valuable to attackers conducting targeted social engineering operations. Organizations may be unaware of how many distinct numbers are surfaced across their subpages, particularly when contact details are embedded in page templates or populated dynamically from CRM systems.

The scanner fetches the root page of the target asset via a headless browser, falling back to a plain HTTP request if the browser-based fetch fails. It then parses anchor tags to identify contact-related subpages using an extensive keyword list that includes contact, iletisim, hakkimizda, about, support, help, get-in-touch, reach-us, connect, contactus, hello, and contact-form, visiting up to two matching pages on the same domain. On each collected HTML document, script and style blocks are stripped before the remaining text is scanned with a regular expression that matches common international phone number formats including sequences with plus signs, spaces, dots, hyphens, parentheses, and slashes. Each match is validated by counting the digit characters present, accepting only those containing between ten and fifteen digits to conform to international numbering standards and filter out false positives such as version numbers or ZIP codes. Deduplicated phone numbers are associated with their source pages and reported as number-to-URL pairs in the detailed output. The two-page crawl limit keeps the scan targeted while still capturing numbers that appear exclusively on dedicated contact or support subpages.

Harvested phone numbers are primary targets for vishing attacks, where adversaries call staff while impersonating vendors, IT support, or executives to manipulate them into revealing passwords, transferring funds, or granting system access. Direct-dial numbers for finance, HR, or executive assistant roles enable highly targeted pretexting attacks where the attacker's knowledge of the correct contact number adds credibility to the deception. Phone numbers collected from web pages are frequently sold to or shared among spam and robocall networks, resulting in persistent unsolicited communications that consume staff time and degrade operational productivity. In combination with email addresses harvested from the same pages, phone numbers enable multi-channel social engineering campaigns that are significantly harder for targets to identify as fraudulent. SIM swapping attacks can be initiated against individuals whose personal mobile numbers are published on organizational pages, allowing attackers to take over phone-based two-factor authentication. Numbers associated with customer-facing support lines can be impersonated in reverse-vishing scenarios, where attackers send phishing emails instructing victims to call a spoofed number that mimics the organization's legitimate support line.