Google AI Threat Defense
Google AI Threat Defense is an AI-powered cybersecurity platform designed to help organizations proactively predict, prioritize, and remediate threats at machine speed. Combining the reasoning capabilities of Gemini, contextual risk analysis from Wiz, automated code remediation through Gemini and CodeMender, and frontline threat intelligence from Mandiant, the platform enables security teams to continuously identify exposures, validate risks, accelerate remediation, and monitor environments for emerging threats. Built around a four-step framework of Prepare, Scan, Remediate, and Monitor, Google AI Threat Defense helps organizations strengthen security across multicloud, AI, SaaS, code, and hybrid environments while reducing response times and improving operational resilience against modern AI-driven attacks.
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Raven
Raven is a runtime application security platform designed to protect cloud-native applications by operating directly inside the application during execution, rather than relying on external defenses. It provides real-time visibility into how code actually runs, allowing it to understand execution flows, libraries, and function-level behavior in order to detect and stop malicious activity before it occurs. Unlike traditional tools such as WAF or EDR that monitor from the outside, Raven embeds itself within the application, enabling it to prevent exploits, supply chain attacks, and zero-day threats even when no known vulnerability or CVE exists. It continuously monitors runtime behavior, identifies abnormal patterns or misuse of legitimate logic, and responds immediately to block harmful execution. It also helps teams prioritize security efforts by filtering out the majority of irrelevant vulnerabilities and focusing only on those that are truly exploitable.
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ARTEMIS by Repello
ARTEMIS by Repello AI hunts for vulnerabilities in your AI applications by simulating attacks that malicious actors would use. ARTEMIS tests, identifies, and helps remediate security risks before they can be exploited in production environments. This is powered by world's largest AI-specific threat intelligence repositories.
Key Features:
1. Simulates real-world attacks against your AI systems
2. Maps vulnerabilities across your AI infrastructure
3. Provides actionable mitigation recommendations
4. Adapts to evolving threats as your AI applications grow
Built by security engineers to protect AI from attackers. Secure your AI early in development and throughout deployment.
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Sysdig Secure
Cloud, container, and Kubernetes security that closes the loop from source to run. Find and prioritize vulnerabilities; detect and respond to threats and anomalies; and manage configurations, permissions, and compliance. See all activity across clouds, containers, and hosts. Use runtime intelligence to prioritize security alerts and remove guesswork. Shorten time to resolution using guided remediation through a simple pull request at the source. See any activity within any app or service by any user across clouds, containers, and hosts. Reduce vulnerability noise by up to 95% using runtime context with Risk Spotlight. Prioritize fixes that remediate the greatest number of security violations using ToDo. Map misconfigurations and excessive permissions in production to infrastructure as code (IaC) manifest. Save time with a guided remediation workflow that opens a pull request directly at the source.
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