The agent kill chain framework
A behavioral attack model for autonomous AI systems
Autonomous AI agents have evolved from text generators into active computational actors, introducing novel failure modes that traditional security frameworks cannot detect or govern. Reasoning drift, self-escalation of privileges, and emergent tool misuse demand a new approach to AI security.
Discover how the agent kill chain framework addresses this by providing the first structured behavioral model for the lifecycle of agentic AI misuse. Download this white paper to understand how the Agent Kill Chain provides security teams with the shared language and defenses needed to move from reactive prompt guards to comprehensive behavioral governance.
FAQs
Artificial intelligence is crucial in security intelligence because it enhances threat detection, automates response actions and enables predictive analysis of potential threats. AI algorithms can analyze large volumes of data to identify patterns and anomalies, helping security teams detect and respond to cyber threats more efficiently. Additionally, AI technologies can aid in identifying vulnerabilities, predicting security risks and providing actionable intelligence to improve overall cybersecurity posture.
Yes. Capabilities like Mobot and the SOC Analyst Agent process customer telemetry to perform investigations, run queries, and generate findings. All processing occurs securely within your platform context, and customer data is never used to train generalized AI models. Administrators can turn off Dojo AI capabilities at any time through Feature Management or by submitting a support ticket.
Customers that previously opted out of Sumo Logic AI capabilities will not get access to these or future AI capabilities until they explicitly opt back in.