Bug Bounty Take-Aways – 01 – NahamSec Edition
YouTube: @NahamSec Playlist: https://www.youtube.com/playlist?list=PLKAaMVNxvLmAkqBkzFaOxqs3L66z2n8LA ─ This document synthesizes insights from a series of live bug bounty reconnaissance sessions and interviews with prominent security researchers and hackers. The core themes that emerge are the diverse and evolving nature of reconnaissance, the critical role of customized tooling and automation, and the profound value of community, collaboration, and continuous learning. Reconnaissance is presented not as a monolithic process but as a spectrum of philosophies, ranging from broad, automated discovery of attack surfaces to “reconless” deep dives into application logic. Successful practitioners tailor their approach to the target and their personal strengths, often blending large-scale data gathering with manual analysis. A vast arsenal of open-source and custom-built tools is employed, with an emphasis on chaining simple, single-purpose utilities through scripting—predominantly in Bash—to create powerful, personalized workflows. Beyond the technical, the sources emphasize a mindset of perseverance, creativity, and intellectual curiosity. The community is depicted as a vital resource for knowledge sharing and collaboration, which is repeatedly cited as essential for finding critical vulnerabilities. Advice for newcomers centers on building a solid foundation in application security, focusing on one vulnerability class at a time, reading disclosed reports, and practicing consistently through platforms like CTFs and VDPs, rather than pursuing immediate financial gain. Ultimately, success in bug bounty hunting is portrayed as a marathon of continuous learning, adaptation, and disciplined effort, not a sprint for easy bugs. Reconnaissance: Philosophies and Approaches Reconnaissance (recon) is the foundational phase of bug bounty hunting, but its execution varies dramatically among practitioners. The source context reveals several distinct philosophies and methodologies. 1. Broad Attack Surface Discovery This is the most common approach, focusing on identifying as many assets belonging to a target as possible. Subdomain Enumeration: The primary goal is to discover all subdomains. This is achieved through both passive and active methods. Passive Sources: Tools query public data sources like certificate transparency logs (cert.sh, Cert Spotter, Censys), DNS aggregators (assetfinder, findomain, Sublist3r), and historical archives (Wayback Machine). Active Methods: Once a baseline list of subdomains is established, tools like massdns and altdns are used for brute-forcing with wordlists and performing permutations to discover unlinked subdomains. Root Domain Discovery: A key technique involves using certificate transparency logs to find primary or root domains that are not immediately obvious. By searching for the organization’s name in certificates, hunters can uncover entirely separate domains (e.g., ops.yahoo.com, bf1.yahoo.com) which can then be used as seeds for further subdomain enumeration. This “search and destroy” method significantly expands the potential scope. IP and Certificate Scanning: Advanced techniques involve scanning the entire internet or large cloud provider IP ranges for TLS certificates containing target-owned domain names. This can uncover assets that do not have public DNS records, giving the hunter access to a unique attack surface that others might miss. 2. Deep Dive and “Reconless” Approaches In contrast to broad discovery, this methodology focuses on deeply understanding a single application or a small set of core applications. Application Logic Mapping: This “reconless” or manual approach involves interacting with an application as a user (and as different user roles, like admin or low-privilege user) to map out its features, workflows, and business logic. The goal is to identify structural issues, permission flaws, and authentication vulnerabilities that automated scanners would miss. Reading Documentation: A frequently cited technique is to thoroughly read all available developer documentation, API guides, and tutorials for the target application or its underlying technologies. This provides a sanctioned list of endpoints, parameters, and expected behaviors that can be systematically tested. Source Code and JavaScript Analysis: This involves manually or automatically parsing JavaScript files to discover hidden API endpoints, routes, parameters, and developer comments. Diffs of JavaScript files over time are used to identify new and emerging functionality before it is fully released. 3. Continuous Reconnaissance This strategy involves automating the discovery process to monitor targets over time for changes. Automated Monitoring: Scripts are set up to run periodically (e.g., daily or weekly) to perform subdomain enumeration and endpoint discovery. The results are compared against a known baseline to identify new assets as soon as they appear. Change Detection: Tools like anychanges are used to monitor specific endpoints for modifications, which could indicate new code deployments and potential vulnerabilities. 4. Information Gathering Recon is defined as more than just finding technical assets. It extends to gathering any information that provides context about the target. OSINT: This includes analyzing a company’s GitHub repositories for leaked credentials, internal hostnames, or sensitive code. It also involves reviewing the company’s careers page to understand the technologies they use and the structure of their teams. Historical Analysis: Using the Wayback Machine to find old, forgotten endpoints, parameters, and JavaScript files that may still be active but are no longer linked from the main application. Core Methodologies and Approaches Analysis of the provided context reveals several overarching methodologies that guide the work of top-tier hackers and security researchers. These approaches, while varied in execution, share common principles of thoroughness, creativity, and efficiency. The Foundational Role of Reconnaissance Reconnaissance, or “recon,” is universally cited as the most critical and foundational stage of any offensive security engagement. It is the process of identifying and gathering information about a target’s assets. Practitioner approaches can be broadly categorized into two philosophies: Functionality-Driven Recon: This manual, in-depth approach prioritizes a deep understanding of a single application’s features and business logic. Practitioners like Farah Hawa and Rhynorater champion this method, which involves meticulously mapping every function, taking extensive notes in platforms like Notion, and downloading all associated JavaScript files for analysis. The goal is to discover logical flaws, access control issues, and vulnerabilities that automated scanners typically miss. Asset-Driven Recon: This large-scale, automated approach focuses on discovering the entirety of a target’s external footprint, including subdomains, IP ranges, and related corporate entities. This is the philosophy behind tools like Axiom and the workflows of experts like Dan Miessler and codingo_. The process involves using multiple data sources (e.g., SecurityTrails, Rapid7 FDNS, reverse whois lookups) and chaining tools