Offensive Security Researcher

About the role

Join Check Point’s Exposure Management Research Group to lead offensive research for the newly formed Agentic Exposure Validation (AEV) team. You will bring hands‑on red‑team expertise to an AI‑driven platform that validates real‑world attack paths across customers’ environments.

Key responsibilities

• Design and execute offensive research against external attack surfaces such as web applications, APIs, cloud‑exposed services, identity platforms, and edge infrastructure.
• Transform single findings into demonstrated impact through exploit chaining, lateral movement, and blast‑radius analysis.
• Write and maintain exploitation methodologies and attack hypotheses that power the agentic AEV engine.
• Review agent runs, separate proven impact from claimed impact, and improve prompts, methods, and guardrails.
• Set the bar for customer‑ready findings with clear impact stories, reproducible chains, and remediation guidance.
• Collaborate with threat‑intelligence researchers to turn in‑the‑wild attacker behavior into validation plays.
• Close the purple loop by turning proven attack paths into detection and protection logic with detection engineering teams.
• Contribute to internal knowledge sharing and, where appropriate, external publications or talks.

Required profile

• 2+ years of hands‑on offensive security experience (red teaming, penetration testing, or offensive research).
• Demonstrated exploitation depth beyond confirming vulnerabilities, including exploit chaining, privilege escalation, lateral movement, and business impact.
• Comfort with non‑deterministic offense such as business‑logic flaws, misconfigurations, credential/token abuse, and information‑disclosure entry points.
• Strong scripting and automation skills, preferably in Python.
• Clear written communication able to explain complex attack chains to engineers and CISOs.
• Consulting background covering many customer environments is a strong advantage.
• Broad exposure to defensive technologies, security controls, and vendors.
• Experience with template‑based or automated scanning frameworks (e.g., Nuclei) and detection engineering (Snort/Suricata, YARA, SIEM).
• Interest or experience with large language models (LLMs) or agentic AI workflows.

Required skills

• Python scripting and automation.
• Nuclei scanning framework.
• Snort and Suricata rule development.
• YARA rule creation.
• SIEM detection logic.
• Large language models (LLMs) and agentic AI concepts.