Mindgard
Mindgard is an automated AI red teaming and offensive security platform purpose-built for AI systems and agents. Built for security and engineering teams accountable for AI in development and production, it continuously red teams models, agents, and applications to find the vulnerabilities most likely to cause a breach, validate whether guardrails and controls hold, and show teams how to close each gap.
AI red teaming tests emulate real attacker behavior across prompt injection, jailbreaks, data extraction, poisoning, and agentic tool abuse, and map findings to OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and the EU AI Act. Unlike traditional AppSec tools or manual penetration testing, Mindgard cuts AI risk assessment from weeks to hours, pinpoints and validates defensive gaps, and supports continuous policy compliance as AI systems change. Capabilities: AI Discovery & Recon, AI Red Teaming, AI Assessment, AI Runtime Protection, Model Scanning, AI Governance & Compliance. SOC 2 Type
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Cisco AI Defense
Cisco AI Defense is a comprehensive security solution designed to enable enterprises to safely develop, deploy, and utilize AI applications. It addresses critical security challenges such as shadow AI—unauthorized use of third-party generative AI apps—and application security by providing full visibility into AI assets and enforcing controls to prevent data leakage and mitigate threats. Key components include AI Access, which offers control over third-party AI applications; AI Model and Application Validation, which conducts automated vulnerability assessments; AI Runtime Protection, which implements real-time guardrails against adversarial attacks; and AI Cloud Visibility, which inventories AI models and data sources across distributed environments. Leveraging Cisco's network-layer visibility and continuous threat intelligence updates, AI Defense ensures robust protection against evolving AI-related risks.
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Protecto
While enterprise data is exploding and scattered across various systems, oversight of driving privacy, data security, and governance has become very challenging. As a result, businesses hold significant risks in the form of data breaches, privacy lawsuits, and penalties. Finding data privacy risks in an enterprise is a complex, and time-consuming effort that takes months involving a team of data engineers. Data breaches and privacy laws are requiring companies to have a better grip on which users have access to the data, and how the data is used. But enterprise data is complex, so even if a team of engineers works for months, they will have a tough time isolating data privacy risks or quickly finding ways to reduce them.
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Enkrypt AI
Enkrypt AI is an agentic AI security and compliance platform designed to protect AI applications, models, agents, and their interactions throughout deployment. The platform combines continuous red teaming, real-time guardrails, monitoring, and policy enforcement to help organizations identify and mitigate AI security, safety, compliance, and brand risks. Enkrypt AI dynamically tests AI systems with use-case-specific attacks to uncover issues such as prompt injection, jailbreaking, data leakage, hallucinations, bias, harmful content, model drift, and unsafe agent actions. Real-time guardrails analyze AI interactions and block threats as they occur while adapting to changing prompts and emerging risks. Its compliance capabilities translate internal policies and external regulations into automated controls while producing evidence that organizations can use for audits and governance.
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