darkoperator/dnsrecon

DNS Enumeration Script

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darkoperator/dnsrecon has 3k+ stars and 550+ forks on GitHub, is written in Python, and was last pushed on Oct 12, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 6 minutes ago
Added to GitGenius on September 22nd, 2026
Created on December 16th, 2010
Open Issues & Pull Requests: 2 (+0)
GitHub issues: Enabled
Number of forks: 576
Total Stargazers: 3,083 (+0)
Total Subscribers: 90 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 17.2 days
Mean response time: 258.8 days
90th percentile: 963.0 days
Tracked items: 29

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 132 days
Stale 30+ days: 1
Stale 90+ days: 1

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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  • Help Wanted (6)
  • Feature request (5)
  • feedback-required (1)

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Detailed Description

DNSRecon is a DNS enumeration tool that performs reconnaissance on domain name systems for security assessment and network troubleshooting purposes.

The tool addresses the need to gather DNS information about a target domain or network through multiple enumeration techniques. It works by offering a suite of DNS query methods: zone transfer checks against all nameservers, enumeration of standard DNS records like MX, SOA, NS, A, AAAA, SPF and TXT, SRV record discovery, top-level domain expansion, wildcard resolution detection, subdomain brute forcing using wordlists, reverse PTR lookups across IP ranges or CIDR blocks, and DNS cache checking. The tool can also enrich findings by integrating with Shodan to expand netblocks discovered in SPF and WHOIS data, with optional active validation to confirm results.

DNSRecon suits penetration testers and security professionals performing domain reconnaissance, as well as network administrators troubleshooting DNS issues. It works best when you need comprehensive DNS information gathering across multiple enumeration vectors in a single tool. The project provides both a command-line interface and a REST API for integration into automated workflows. The REST API enforces thread limits and includes safeguards around wordlist directory configuration to prevent accidental exposure of sensitive files.

The project maintains active development with regular updates to dependencies and tooling. The codebase includes automated testing infrastructure and code quality checks through linting and formatting. Installation is streamlined through modern Python packaging tools, with Python 3.12 or higher required. Development setup is documented with clear instructions for contributors to install dependencies, run tests, and perform code quality validation.