Mobile Security Researcher Jobs in Texas (NOW HIRING)

• Conducting in-depth reverse engineering and vulnerability analysis across various architectures and platforms, including x86/64, ARM, PowerPC, and more
• Researching and analyzing operating system and application internals, identifying and understanding security strengths and weaknesses of those systems
• Developing and enhancing functionality by adding features and capabilities to undocumented interfaces
• Modeling and analyzing in-memory compiled application behavior to identify potential vulnerabilities and improve security measures
• Developing and understanding mobile/embedded systems and kernel modules, particularly related to vulnerability research
• Participating actively in our extensive Vulnerability Research mentorship program, sharing knowledge and collaborating with colleagues

• Proficient understanding of wireless networking and associated security protocols, such as Wi-Fi (802.11), Bluetooth, or cellular networks (2G/3G/4G/5G). Familiarity with common vulnerabilities and attack vectors in wireless communication
• Strong grasp of legacy exploit mitigations and bypass techniques, including but not limited to Address Space Layout Randomization (ASLR), Data Execution Prevention (DEP/NX), Stack Cookies (Canaries), and Control Flow Integrity (CFI). Experience in identifying and circumventing these security measures
• In-depth knowledge of both security and network fundamentals, such as cryptography, authentication, access control, and network protocols (TCP/IP, UDP, DNS, HTTP, etc.). Understanding the security implications and potential vulnerabilities associated with these concepts
• Programming experience with both scripted languages (preferably Python3) and compiled languages (preferably C). Ability to write efficient and secure code for vulnerability research and exploit development purposes
• Familiarity with low-level architectures such as x86, ARM, or MIPS. Understanding the underlying principles, instruction sets, and memory models of these architectures for vulnerability identification and analysis
• Experience with operating system internals and implementations, including Windows, Linux, or macOS. Knowledge of system structures, process management, memory management, and security mechanisms at the kernel level
• Excellent oral, written, and interpersonal communication skills, with the ability to effectively convey complex technical concepts and interact with customers and team members alike

• Experience with vulnerability research and reverse engineering of real-time operating systems (RTOS), such as FreeRTOS, QNX, or VxWorks. Understanding the unique security challenges and attack vectors specific to RTOS environments
• Bachelor's or postgraduate degree in Computer Science, Computer Engineering, or a related field
• Experience with software protection and binary armoring techniques, such as anti-debugging, code obfuscation, or tamper resistance. Understanding the methods employed to protect software from reverse engineering and vulnerability discovery
• Proficiency in agile development methodologies, including Scrum or Kanban, for efficient collaboration and iterative development in a cybersecurity context
• Familiarity with low-level iOS/Android development and associated security considerations, such as jailbreaking or rooting, application sandboxing, or secure interprocess communication (IPC)
• Knowledge of hypervisors and their security implications, including virtualization-based security, guest escape vulnerabilities, or hypervisor-based rootkits
• Proficiency in malware analysis, including static and dynamic analysis techniques, behavioral analysis, and code deobfuscation. Experience in identifying and analyzing malware samples to understand their capabilities and potential vulnerabilities
• Experience with constraint solving techniques, such as symbolic execution, theorem proving, or model checking, for vulnerability identification, verification, and exploit generation
• Background in machine learning, particularly in the context of vulnerability analysis and detection, such as using ML techniques to identify patterns in code or analyze network traffic for anomaly detection

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.