Principal Researcher, Botnet & DDoS Threats

A10 Networks, Inc · San Francisco Bay Area · 1 wk ago

HybridAnalyst$200k–$215k/yrFull-time

Reverse engineer IoT botnet malware families (Mirai lineage, Go-based L7 flooders, multi-architecture binaries) to understand attack behavior at the implementation and network level.
You will reconstruct command structures, decode obfuscation, recover control flows from stripped binaries, and build precise models of how attacks manifest on the wire.
Perform dynamic malware analysis in sandboxed and purpose-built lab environments to validate static analysis and observe runtime behavior.
Design and contribute to novel detection and mitigation approaches based on malware internals and traffic behavior.
Collaborate with AI/ML teams to integrate automated analysis into research workflows. This is not passive tool usage—you will actively shape how automation is applied to real malware analysis problems.
Partner with product engineering to translate research into shipped detection capabilities.
Lead external-facing research: threat reports, technical blogs, and conference presentations. At principal level, you own the narrative and direction of research output.
Engage directly with customers in post-incident analysis, architectural guidance, and strategic threat briefings—clearly explaining both attacker behavior and defensive actions.
Work alongside senior researchers focused on IoT botnets and large-scale DDoS systems, contributing to and benefiting from a deeply technical peer environment.

Strong foundation in binary reverse engineering using tools such as Ghidra or IDA, including static analysis across multiple architectures and experience with stripped binaries and compiler-generated code; you should be comfortable working close to raw assembly and control flow, not dependent on tooling abstraction.
Hands-on experience with dynamic malware analysis in sandbox or isolated lab environments, using runtime observation to validate and extend static findings.
Working proficiency in Python and Go.
Strong understanding of network protocols at the implementation level, including the ability to interpret PCAPs and reconstruct protocol behavior.
Familiarity with DDoS botnet architectures (e.g., Mirai lineage or equivalent), ideally with direct analysis of binaries rather than secondary reporting. Experience tracking variant evolution across malware families is a strong plus.
Ability to communicate complex technical findings clearly across engineering, product, and customer audiences; at this level, communication quality is a core part of technical impact.

Experience with high-performance packet processing or mitigation systems at the network and transport layers.
Experience analyzing Go binaries in depth.
Exposure to malware source code.
Experience applying ML-assisted or vector-based approaches to malware classification, clustering, or lineage attribution.

Similar jobs