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Maximizing Penetration Testing Success with Effective Reconnaissance Techniques using ChatGPT

Sheetal Temara

arXiv:2307.06391v1cs.CRcs.AI

TL;DR

The paper examines whether ChatGPT can provide useful information for penetration-testing reconnaissance, a potential cybersecurity use case. It uses tailored questions to elicit target information and reports that the responses cover multiple aspects of the target, while noting that usable results depend on prompt composition and can change over time.

  • Problem

    The paper explores ChatGPT’s potential value for reconnaissance, an information-security use case that could support securing organizations’ Internet-accessible assets.

    Source: Introduction · p. 2

  • Method

    The study supplied reconnaissance data requests to ChatGPT and tailored prompts to seek usable target information.

    Source: Methodology · pp. 2–3

  • Results

    ChatGPT returned varied reconnaissance information, including target IP ranges, SSL/TLS details, linked websites, technology stacks, and network protocols.

    Source: Discussion · pp. 7–8

  • Takeaways & Limitations

    The gathered background information can support planning for later penetration-test phases, and the paper presents ChatGPT as a valuable reconnaissance tool.

    Source: Discussion · p. 8, Conclusion · p. 8

    Usable responses require carefully composed questions, and responses can become invalid or change over time as ChatGPT is trained.

    Source: Discussion · p. 8, Conclusion · p. 9

Abstract

from arXiv · show

ChatGPT is a generative pretrained transformer language model created using artificial intelligence implemented as chatbot which can provide very detailed responses to a wide variety of questions. As a very contemporary phenomenon, this tool has a wide variety of potential use cases that have yet to be explored. With the significant extent of information on a broad assortment of potential topics, ChatGPT could add value to many information security uses cases both from an efficiency perspective as well as to offer another source of security information that could be used to assist with securing Internet accessible assets of organizations. One information security practice that could benefit from ChatGPT is the reconnaissance phase of penetration testing. This research uses a case study methodology to explore and investigate the uses of ChatGPT in obtaining valuable reconnaissance data. ChatGPT is able to provide many types of intel regarding targeted properties which includes Internet Protocol (IP) address ranges, domain names, network topology, vendor technologies, SSL/TLS ciphers, ports & services, and operating systems used by the target. The reconnaissance information can then be used during the planning phase of a penetration test to determine the tactics, tools, and techniques to guide the later phases of the penetration test in order to discover potential risks such as unpatched software components and security misconfiguration related issues. The study provides insights into how artificial intelligence language models can be used in cybersecurity and contributes to the advancement of penetration testing techniques. Keywords: ChatGPT, Penetration Testing, Reconnaissance

Introduction

Penetration testing uses authorized assessments to identify exploitable vulnerabilities and design flaws, with reconnaissance gathering target information to guide testing. ChatGPT’s conversational capabilities make it a potential reconnaissance tool.

Introduction

  • A penetration test is an authorized assessment that mimics an attack to evaluate security controls and identify exploitable vulnerabilities or design flaws.Testers use tools, techniques, and procedures like those of malicious actors.Source: Introduction · p. 2
  • Reconnaissance gathers detailed information about an assessment’s scope, including technologies, SSL/TLS settings, cookies, third-party relationships, network topology, and operating systems.This information can help testers understand the target and plan testing for potential risks.Source: Introduction · p. 2
  • ChatGPT’s natural-language interaction and response capabilities give it potential value as a tool for penetration-testing reconnaissance.The paper describes ChatGPT as a dialogue system based on human conversations and natural-language processing.Source: Introduction · p. 2

Methodology

The study used ChatGPT to obtain common penetration-testing reconnaissance data types and considered how that information could guide later testing phases. It emphasizes reusable questions and prompt tailoring to obtain usable results.

Methodology

  • The study provided common penetration-testing reconnaissance data types to ChatGPT and sought information that could guide later test execution and exploitation.Expected target background included technology stack, vendor relationships, encryption techniques, and network topology.Source: Methodology · pp. 2–3
  • The researchers sought reusable questions that could request valuable reconnaissance data as a standard practice for assessments.Questions had to be tailored to obtain information usable in reconnaissance.Source: Methodology · p. 3
  • Trial and error was needed because questions requesting specific data did not always produce desirable results, making prompt engineering necessary to procure usable information.Source: Methodology · p. 3

Results

ChatGPT returned varied target reconnaissance information, including network and web-property details, technologies, and encryption-related data. The examples describe potential outputs and their relevance to mapping targets and planning testing.

Results

  • ChatGPT can return target IP ranges in CIDR format, where the trailing number indicates the number of addresses in the range.The paper frames the comprehensive range list as the target’s attack surface and notes that network nodes may contain vulnerabilities.Source: Results · p. 3
  • ChatGPT can provide domain details such as primary domains, subdomains, other and international domains, gTLDs, and subsidiary domains.The paper links domain information to mapping infrastructure and identifying potential risks such as vulnerable software components.Source: Results · p. 4
  • ChatGPT can return vendor technologies spanning CDNs, web servers, advertising and analytics engines, CRM, libraries, APIs, SSO, and integration tools.The paper says this information can inform planning about potential vulnerabilities, tools, and simulated attacks.Source: Results · p. 4
  • ChatGPT can list SSL ciphers and certificate authorities, including AES128_GCM_SHA_256, AES_256_GCM_SHA_384, and DigiCert.Testers need to understand cipher deficiencies that could put sensitive data at risk.Source: Results · pp. 4–5
  • ChatGPT can return SSL/TLS versions and related security technologies, including TLS 1.0–1.3, SSL 3.0, PFS, HSTS, ALPN, ECC, PKP, CT, RSA, and OCSP stapling.The passage notes that deprecated SSL/TLS versions can present a possibility of data decryption by malicious actors.Source: Results · p. 5
  • ChatGPT can list partner websites linked to a target, which the paper treats as potential entry points and components of the target’s attack surface.The described query asks for partner websites, including FQDNs, linked directly to the target website.Source: Results · p. 5
  • ChatGPT can return network protocols associated with a target, including HTTP, HTTPS, DNS, SMTP, NTP, SSH, BGP, SNMP, TCP, UDP, IPv4, and VPN.The paper notes that some protocols may be exploited to establish a foothold and enable access to sensitive information or lateral movement.Source: Results · p. 6

Discussion

The study reports that ChatGPT can return varied reconnaissance information and improve efficiency by consolidating capabilities found in multiple tools. Its usefulness is bounded by prompting challenges and changing responses, while the study covers only some generally useful reconnaissance data types.

Discussion

  • ChatGPT can provide insight into a target organization’s technology stack, web applications, attack surface, and web properties, supporting reconnaissance planning such as tool selection, test configuration, and exploit selection (Chowdhary et al. (2020)).Prompting ChatGPT to continue may retrieve additional information containing the desired response.Source: Discussion · p. 7
  • ChatGPT returned IP ranges, SSL/TLS versions and ciphers, partner websites, technology stacks, and network protocols, consolidating capabilities found in several tools.The authors say this background information supports preparation for later penetration-test phases.Source: Discussion · pp. 7–8
  • Prompting required trial and error, and requests could be rejected or yield unusable data; responses that were previously useful could later become invalid.The authors say testers need to compose questions to attain usable reconnaissance results.Source: Discussion · p. 8
  • The study examined selected reconnaissance data useful in many scenarios, leaving scenario-specific data types and prompt research for future work.The authors say the set of information ChatGPT could gather may be expanded for a wider range of penetration-testing scenarios.Source: Discussion · p. 8

Conclusion

The conclusion presents ChatGPT as a valuable reconnaissance tool whose outputs can inform planning for the next penetration-test phase. It also cautions that responses can change as ChatGPT is trained, and frames the findings as an initial basis for further work.

Conclusion

  • The conclusion presents observations about ChatGPT reconnaissance and insights obtainable about penetration-testing targets.Source: Conclusion · p. 8
  • ChatGPT’s reconnaissance information can be used directly to plan the next penetration-test phase and may provide insights that previously required multiple tools or were not easily acquired.The authors conclude that the returned information makes ChatGPT valuable for penetration-test reconnaissance.Source: Conclusion · p. 8
  • Because ChatGPT is continually trained, responses—especially security details about target organizations—can change over time, requiring flexible prompt tailoring.The authors describe this research’s information as an inception for reconnaissance with ChatGPT, to be built on over time.Source: Conclusion · p. 9

Funding

The research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Funding

  • The research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.Source: Funding · p. 11

Authors’ Contributions

Sheetal Temara designed the study, conducted the research, collected and analyzed the data, and wrote the manuscript.

Authors’ Contributions

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