Automated Red Teaming for AI - Check Point Software

Automated Red Teaming for AI

Find safety and security failure modes that traditional testing can’t.

AI Is Moving From Language To Action. Are You Ready?

See what recent attacks revealed and how to secure agents in 2026.

Expose context-specific risk under real adversarial pressure.

Application-Specific risks Surface vulnerabilities unique to your AI’s architecture, context, and real world usage patterns.
Safety and compliance gaps Test the robustness of your AI against harmful outputs policy violations, and inappropriate content generation.
Security weaknesses Test your AI’s defenses against prompt injection, jailbreaks, data leakage, and unauthorized actions.
Regression and drift Catch when model updates, system changes, or capability additions introduce new risks.

Execute broad and targeted red team campaigns to systematically assess application risk across evolving models and prompts.

Test across 400+ foundation models, custom model deployments, live applications, and agent end points.

Run comprehensive automated scans across security, safety, responsible AI risk categories, or launch focused adversarial campaigns.

Generate attack scenarios tailored to your architecture, prompts, controls, and operational context, not just generic prompt libraries.

Re-run structured adversarial tests after model updates, prompt changes, or new capabilities to evaluate how risk shifts over time.

Incorporate evolving attack techniques informed by ongoing adversarial research and real-word red teaming experience.

Execute testing across multiple models, applications, and agent architectures from a single platform.

AI Red Teaming supports development, validation, and ongoing operations as AI systems evolve.

Evaluate During Development – Run adversarial tests as prompts, guardrails, and model configurations change to assess risk early.
Validate Before Production – Execute comprehensive scans and targeted red team campaigns against live applications and agents prior to release.
Re-test as Systems Evolve – Schedule recurring adversarial testing after model updates, prompt changes, or new capabilities to detect regressions.