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OffensiveSecurityResearcher—AndroidUserSpace&AI-AugmentedVulnerabilityResearch
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“Offensive Security Researcher — Android User Space & AI-Augmented Vulnerability Research”
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Full Job Description
DESCRIPTION We are seeking an Offensive Security Researcher with a focus on Android user space security and a strong interest in applying AI/LLM-assisted workflows to advanced vulnerability research. The role involves identifying, analyzing, and exploiting vulnerabilities across Android user space components, including native services, system applications, framework components, IPC surfaces, media stacks, vendor customizations, and security-relevant platform integrations. In addition to hands-on vulnerability research, this role includes helping design and integrate AI-assisted workflows that support reverse engineering, code exploration, patch diffing, crash triage, root-cause analysis, variant discovery, fuzzing workflows, exploit development, and research knowledge management. This is not a prompt engineering role. We are looking for someone with real Android security research depth who wants to explore how LLMs and agentic AI systems can augment expert researchers working on complex mobile targets. RESPONSIBILITIES - Discover and analyze vulnerabilities in Android user space components, including native daemons, system services, framework layers, privileged applications, media components, and vendor-specific attack surfaces. - Reverse engineer Android internals, proprietary components, vendor modifications, IPC mechanisms, binder interfaces, native libraries, and security boundaries. - Analyze vulnerabilities involving memory corruption, logic flaws, privilege escalation, insecure IPC, unsafe deserialization, race conditions, permission model weaknesses, and sandbox escapes. - Develop proof-of-concept exploits and produce clear, rigorous technical documentation. - Track Android platform security mitigations and assess their effectiveness against real-world exploitation techniques. - Use fuzzing, crash analysis, patch diffing, static analysis, dynamic instrumentation, and variant analysis to identify high-value vulnerability classes. - Contribute to the design an
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