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Cybersecurity Expert in Threat Research
Il y a 2 mois
ENEA Qosmos division is a leading provider of Deep Packet Inspection (DPI) technology, enabling customers to gain application visibility, accelerate time to market, and benefit from continuous signature updates.
Our DPI engine recognizes over 3800 protocols and can extract over 5000 metadata, providing a true picture of network traffic.
The RoleWe are seeking a highly skilled Cybersecurity Expert in Threat Research & Detection to join our innovative and collaborative R&D team.
As a key member of our team, you will contribute to implementing our company's strategy in cybersecurity, focusing on threat research and detection.
Responsibilities- Lead the setup and automation of a cybersecurity lab for malware and TTPs analysis, experimentation, and training purposes.
- Lead malware analysis, extract malware IOCs and TTPs, and produce high-fidelity detection signatures.
- Participate in research related to machine learning-based threat and anomaly detection focusing on network traffic.
- Contribute to the design of new cybersecurity-oriented products and features on top of Qosmos NG DPI.
- Educate, train, and provide guidance to R&D team members on key cybersecurity subjects.
- Carry out experiments and prototyping to determine the feasibility of solutions to complex engineering problems.
- Contribute to conversations on product strategy and direction.
We are looking for an expert with a passion for threat research and detection, and a deep understanding of the cybersecurity threat landscape.
You will bring:
- Expertise in threat research and detection, with a deep understanding of the cybersecurity threat landscape.
- Ability to qualify and develop high-quality detection signatures based on analysis of malicious behavior.
- Proficiency in writing Suricata rules is highly appreciated.
- Experience with systems such as IDPS, NDR, XDR, SIEM, or SOAR.
- Familiarity with existing TTP frameworks (MITRE ATT&CK, Cyber Kill Chain).
- Strong communication and collaboration skills.
- Willingness to get things done, take initiative, and challenge existing assumptions and conventions.
Experience in applying Machine Learning/Deep Learning techniques to detecting network threats or network anomalies, and experience with programming languages such as Python, C, or Rust, are highly valued.
