AI Agent Compromised: Can Your AI Engineer and SOC Team Defend at Machine Speed?

As enterprises put autonomous AI agents to work, a new question emerges: when an agent behaves unexpectedly, is it an application issue, a compromised identity, or an adversary manipulating the agent to expose sensitive data?

Answering it takes more than any single team or tool. Splunk by Cisco brings observability, security, and agentic AI together on one trusted data foundation, so the people who build AI agents and the people who defend them can work from the same evidence with a coordinated response.

Defend at Machine Speed: When an AI Agent Becomes an Attack Vector

AI agents execute tasks, access sensitive information, and make decisions on their own. While that autonomy delivers value, it also creates new risk: an application can appear healthy while an adversary manipulates an agent into exposing data.

In our .conf26 keynote demo we showcased this scenario. An AI engineer uses Splunk Agent Observability to investigate unusual agent behavior. Agent behavior signals revealed a malicious prompt that resulted in data leakage. What initially looked like an operational anomaly was actually a security threat.

In most organizations, this would start a separate SOC investigation, with teams manually sharing evidence and reconstructing the incident. Splunk removes that gap. Splunk Agent Observability now sends alerts directly to Splunk Enterprise Security, and AI-powered capabilities automatically begin investigation and containment.

Turn Machine Data into Agentic Action: From Detection to Response

Detecting suspicious activity is only the beginning. The real challenge is turning that intelligence into action before the threat escalates.

Splunk’s data platform is the foundation. Application telemetry, logs, traces, security events, and identity activity reveal what's happening across increasingly complex environments.

Our agentic capabilities help correlate signals, investigate threats, and recommend or initiate response actions, reducing the manual effort required to move from detection to remediation.

After containing the initial attack, AI-assisted investigation recommends a security guardrail to prevent similar incidents. The analyst reviews and authorizes the new guardrail. When the adversary attempts the attack again, the new control blocks it at machine speed.

Optimize AI at Scale: Visibility, Performance, and Trust

Resilient AI operations require understanding how agents behave before, during, and after an incident.

With Splunk Agent Observability, AI engineers get visibility into agent behavior, performance, and the rationale for their actions. They can create and optimize new evals quickly as new edge cases are discovered and quickly turn those evals into guardrails that keep agents in check.

They can control costs by tracking token usage and spending across users and projects and combine costs across multiple model vendors into one view. And give security teams visibility into agent activity, identities, and emerging risks for a comprehensive view of agentic vulnerabilities as they unfold.

Watch Mia and Anya Fight Back

Want to see how unified resilience comes to life?

In this demonstration, two employees, Mia an AI engineer, and Anya, a SOC analyst, race to stop an adversary attempting to exfiltrate sensitive data through a compromised AI agent.

Watch how they, and their AI powered agents working across environments, enable a coordinated SRE/SOC response in minutes, versus what previously could take days, even months.

Watch the demo: AI Agent Compromised — Mia and Anya Fight Back →