Automotive Embedded Security Tester; BH

Automotive Embedded Security Tester (BH )

Location:

Plymouth, MI Duration: 2+ year contract Key Requirements

Automotive industry background required

Experience with Electronic Control Units (ECUs)

Strong understanding of CAN (Controller Area Network) protocols

Technical Skills

Penetration testing experience

Must have experience beyond fuzz testing

Looking for candidates with security testing experience in one or more of the following areas:

USB

Wireless communications

Bluetooth

Similar embedded/connected device technologies

Embedded Systems Penetration & Fuzz Testing

Design & Execute Campaigns:
Build and execute comprehensive penetration testing campaigns against a wide variety of automotive embedded targets.

Advanced Fuzzing:
Configure and deploy targeted fuzzing frameworks (e.g., AFL++, lib Fuzzer, Peach, Defensics) against vehicle computers, ECUs, and clusters.

Vulnerability Discovery:
Uncover memory corruption vulnerabilities (buffer overflows, use-after-free), resource exhaustion, and complex logic flaws that automated static analyzers often miss.

Comprehensive Wireless & Wired Protocol Analysis

Wired Vehicle Networks:
Intercept, manipulate, and inject traffic across internal wired topologies, including CAN, CAN-FD, Automotive Ethernet (SOME/IP, DoIP), LIN, and Flex Ray. You will utilize industry-standard tools like Vector CANoe/CANalyzer and Vehicle Spy.

Wireless Ecosystems:
Aggressively analyze and exploit vulnerabilities across every wireless communication interface. This includes deep-dive assessments of Bluetooth/BLE, Wi-Fi (802.11), Cellular networks (4G/LTE, 5G, and C-V2X), UWB, NFC, and traditional RF/Keyless Entry Systems (RKE/PEPS) using Software Defined Radios (SDRs like HackRF, USRP).

Hardware & Firmware Reverse Engineering

Physical Attack Vectors:
Conduct hands-on, hardware-level security testing to identify physical attack vectors.

Hardware Debugging & Exploitation:
Utilize tools like Logic Analyzers, Bus Pirate, J-Link, and UART/JTAG/SPI debuggers, side-channel analysis (SCA), and voltage/clock fault injection techniques.

Firmware Analysis:
Extract firmware from flash memory for subsequent reverse engineering and static analysis using disassemblers like IDA Pro.

AI-Enhanced Fuzzing and Vulnerability Discovery

Develop and apply AI-driven fuzzing techniques, using machine learning to intelligently guide test case generation and uncover complex vulnerabilities in vehicle software.

Utilize ML models to perform automated analysis of source code and binaries, identifying potential zero-day vulnerabilities that evade traditional static and dynamic analysis tools.

Automated Anomaly Detection in Vehicle Networks

Implement and manage machine learning systems to analyze real-time data from CAN, Automotive Ethernet, and wireless channels, automatically detecting anomalous patterns indicative of a cyberattack.

Adversarial AI/ML System Testing

Conduct security assessments of on-board AI/ML systems (e.g., those used for perception, sensor fusion, or decision-making in autonomous driving).

Design and execute adversarial attacks (e.g., data poisoning, evasion attacks) to test the resilience and integrity of automotive AI models.

Strategic Remediation

Actionable Reporting:
Document findings in meticulous, highly technical reports that include mitigation strategies.

Engineering

Collaboration:

Partner directly with other security tester/consultants to craft actionable, robust remediation strategies that fix the root cause of vulnerabilities.

What We Are Looking For Experience & Education

Bachelor's or Master's degree in Computer Science, Cybersecurity, Computer Engineering, or a heavily related technical discipline.

Proven experience in applying AI/ML techniques to cybersecurity challenges, such as intelligent fuzzing, anomaly detection, or securing machine learning systems.

3+ years of hands-on experience in penetration testing, vulnerability research, or reverse engineering, specifically focused on automotive embedded systems, IoT devices, or specialized custom hardware.

Deep Technical Expertise & Certifications

Deep understanding of automotive E/E architectures, RTOS (e.g., QNX, VxWorks, AUTOSAR OS), and POSIX-based systems (Automotive Linux).

Familiarity with automotive microcontrollers (e.g., Infineon AURIX Tri Core, Renesas RH850, ARM Cortex-R/M) and hardware security modules (HSM/SHE).

Strong grasp of industry-standard cybersecurity regulations and frameworks, specifically ISO/SAE 21434, UNECE WP.29 R155, and MITRE Telecommunication&CK.

Knowledge of common machine learning frameworks (e.g., Tensor Flow, PyTorch, scikit-learn) and their application in a security context.

Understanding of adversarial ML concepts and defenses.

Preferred

Certifications:

OSCP, OSCE, OSWE, eCPTX, GXPN, or specialized automotive/IoT security certifications.

Programming & Tooling Proficiency

Proficiency in scripting and low-level programming languages such as Python, C/C++, Bash, or Assembly (ARM/x86/Tri Core).

Experience with data science and machine learning libraries…