Cortega security solutions
Cortega adds real-time, agentic security to block attacks on models, agents and chatbots. Cortega also provides adversarial agentic testing technology to help harden your applications.
Book a demo →What makes an attack agentic? →
Runtime protection
Network firewalls control connections; basic content filters check individual messages. Neither alone establishes whether an agent is following a legitimate instruction. Cortega inspects routed LLM and MCP traffic for manipulation across conversations, untrusted context and proposed tool actions, alongside sensitive-data checks.
Explore the solutionAdversarial evaluation
A prompt checklist can miss an attacker who changes approach after a refusal. Cortega tests adaptive conversations, poisoned memory and tool-access boundaries against your application’s rules, so teams can examine the sequence that produced a policy violation and retest the controls.
Explore the solutionWhy agentic attacks need additional controls
Existing controls remain useful. The gap is what they can infer about the agent’s task, the source of an instruction and the authority behind an action.
A connection to an approved model or tool can contain a request to disclose data or misuse an account. Network rules govern reachability; application policy must also check the requested action and its arguments.
Keys, model allowlists and rate limits govern access and consumption. On their own, they cannot determine whether text from a document or tool result should influence an agent’s next action. That requires context inspection and tool authorization.
Individual turns may look harmless while an adaptive conversation changes the task. A content classifier may also miss instructions embedded in retrieved data. Evaluate conversation context and proposed actions alongside sensitive-content checks.
From our research library