Glossary
Red Teaming
Adversarial testing of AI agent systems where security professionals attempt to exploit vulnerabilities, bypass safeguards, or trigger unintended behaviors.
What is Red Teaming?
Red teaming simulates real-world attacks to identify weaknesses before malicious actors exploit them. Red team exercises involve attempts at prompt injection, permission escalation, data exfiltration, and other attack vectors relevant to AI systems. This proactive security approach helps organizations understand their true risk posture and prioritize defensive improvements.
Effective red teaming for AI agents requires expertise in both traditional cybersecurity and AI-specific vulnerabilities. Teams test not just technical controls but also business logic, decision-making processes, and interaction with other systems. Regular red team exercises, followed by remediation and retesting, create a continuous security improvement cycle.
Example
A red team tests a financial agent by attempting prompt injection to access unauthorized account data, crafting inputs designed to trigger erroneous transactions, and probing API integrations for authentication bypasses. They successfully extract training data through a subtle prompt vulnerability, which the security team then patches before deployment.
How Signet addresses this
Signet's Security dimension highly values regular red team testing. Agents that undergo professional adversarial testing and demonstrate remediation of discovered issues build stronger security trust, while untested agents or those with known unpatched vulnerabilities receive lower Security scores.
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