Principal Cybersecurity Attack Surface Management Infrastructure Detective

Role 1:

Job Summary: The Principal Cybersecurity Attack Surface Management Infrastructure Detective will be responsible for the effective discovery, attribution, and documentation of the internal attack surface. This role requires, a strong understanding of attack surfaces, and the ability to develop and implement robust security strategies. The ideal candidate will have extensive experience in inventory management, security best practices, and a proactive approach to threat detection and response.
Key Responsibilities:

• Conduct thorough assessments of attack surfaces and identify areas of risk using various tools.
• Develop and enforce security policies, standards, and best practices for attack surface management.
• Monitor and analyze data from attack surface management tools to detect and respond to security incidents.
• Stay current with the latest trends, threats, and technologies in attack surface management.
• Conduct training and awareness programs on attack surface management for network and security teams.
• Prepare and present detailed reports on attack surface management posture and incident response activities.
• Work with AI technologies, including training Large Language Models (LLM) and utilizing Retrieval-Augmented Generation (RAG).

Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Cybersecurity, or a related field. A master's degree is preferred.
• Minimum of 7-10 years of experience in cybersecurity, with a focus on attack surface management and tool operations.
• Strong knowledge of attack surface management tools, such as:
• Xpanse and Censys: For identifying devices and services exposed to the internet.
• Armis: For digital footprint and attack surface analysis.
• Tenable: For continuous monitoring and vulnerability management.

Proven experience in identifying and mitigating attack surface risks and vulnerabilities.

Excellent analytical, problem-solving, and communication skills.

Ability to work effectively in a collaborative, fast-paced environment.

Relevant certifications such as CISSP, CEH, or equivalent are highly desirable.

Development experience in Python, JavaScript, Bash Scripting, C/C+/C#, or GO desired.

Proficiency in network monitoring tools (Wireshark, Netflow, sFlow).

Desired Skills:

• Experience with web applications and web application firewalls.
• Understanding of web application/site APIs, i.e. REST method.
• Experience with AI technologies (LLM, RAG).

Role 2:

More on the application side but need to have inventory management will help build policies/business processes with web apps

Job Summary: The Principal Cybersecurity Attack Surface Management Application Detective will be responsible for the effective discovery, attribution, and documentation of Client s application attack surface. This role requires, a strong understanding of attack surfaces, and the ability to develop and implement robust security strategies. The ideal candidate will have extensive experience in inventory management, application/web application security best practices, and a proactive approach to threat detection and response. Key Responsibilities:

• Conduct thorough assessments of application/web application attack surfaces and identify areas of risk using various tools.
• Develop and enforce security policies, standards, and best practices for attack surface management.
• Monitor and analyze data from attack surface management tools to detect and respond to security incidents.
• Monitor and analyze data from various Web Application Firewall solutions to ensure all applications/web applications are properly protected.
• Stay current with the latest trends, threats, and technologies in application/web application attack surface management.
• Conduct training and awareness programs on attack surface management for network and security teams.
• Prepare and present detailed reports on attack surface management posture and incident response activities.
• Work with AI technologies, including training Large Language Models (LLM) and utilizing Retrieval-Augmented Generation (RAG).

Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Cybersecurity, or a related field. A master's degree is preferred.
• Minimum of 7-10 years of experience in cybersecurity, with a focus on attack surface management and tool operations.
• Strong knowledge of attack surface management tools such as:
• Xpanse and Censys: For identifying devices and services exposed to the internet.
• Armis: For digital footprint and attack surface analysis.
• Tenable: For continuous monitoring and vulnerability management.
• F5/Barracuda/Akami WAF platforms: For ensuring appropriate coverage and monitoring of application network controls.
• Proven experience in identifying and mitigating attack surface risks and vulnerabilities.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work effectively in a collaborative, fast-paced environment.
• Relevant certifications such as CISSP, CEH, or equivalent are highly desirable.
• Development experience in Python, JavaScript, Bash Scripting, C/C+/C#, or GO desired.
• Proficiency in network monitoring tools (Wireshark, Netflow, sFlow).

Desired Skills:

• Experience with web applications and web application firewalls.
• Understanding of web application/site APIs, i.e. REST method.
• Experience with AI technologies (LLM, RAG).