Cisco AI Defense plugin for ADK¶

Supported in ADKPython

Cisco AI Defense is an enterprise AI security platform that provides runtime guardrails to protect against threats like prompt injection, data leakage, and harmful content. The ADK plugin integrates these guardrails directly into the ADK Runner lifecycle: it inspects prompts, model responses, and tool calls, then allows or blocks them based on configurable security policies.

Use cases¶

Runtime protection for model calls: Inspect user prompts before model calls and model outputs after generation, then allow or block based on policy (monitor or enforce).
Tool and MCP call inspection: Inspect tool call requests before execution and tool responses after execution, and block unsafe tool behavior in enforce mode with clear metadata.
Auditable decision trace and alerts: Capture decision context (action, severity, classifications, request_id/event_id) and optionally trigger an on_violation callback for monitoring and incident response.

Prerequisites¶

Cisco AI Defense account and API key
Python >= 3.10
ADK >= 1.0.0

Installation¶

pip install cisco-aidefense-google-adk

Set the AI_DEFENSE_API_KEY environment variable (and AI_DEFENSE_MCP_API_KEY for tool inspection).

Use with agent¶

Quickstart¶

Add Cisco AI Defense to any ADK agent with a single line:

from aidefense_google_adk import defend

agent = defend(agent, mode="enforce")

Or get a plugin for the entire app:

from aidefense_google_adk import defend

plugin = defend(mode="enforce")
app = App(name="my_app", root_agent=agent, plugins=[plugin])

Global plugin¶

Use CiscoAIDefensePlugin to apply inspection globally to all agents in a Runner:

from google.adk.agents import LlmAgent
from google.adk.apps import App
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService

from aidefense_google_adk import CiscoAIDefensePlugin

agent = LlmAgent(
    model="gemini-flash-latest",
    name="assistant",
    instruction="You are a helpful assistant.",
)

app = App(
    name="my_app",
    root_agent=agent,
    plugins=[
        CiscoAIDefensePlugin(mode="enforce"),
    ],
)
runner = Runner(app=app, session_service=InMemorySessionService())

Per-agent callbacks¶

Use make_aidefense_callbacks to wire inspection into a specific agent:

from google.adk.agents import LlmAgent
from aidefense_google_adk import make_aidefense_callbacks

cbs = make_aidefense_callbacks(mode="enforce")

agent = LlmAgent(
    model="gemini-flash-latest",
    name="assistant",
    instruction="You are a helpful assistant.",
)
cbs.apply_to(agent)  # wires all 4 callbacks

Modes¶

The plugin supports three operating modes:

Mode	Behavior
`monitor`	Inspect all traffic, log violations, never block (default)
`enforce`	Inspect all traffic, block requests/responses that violate policy
`off`	Skip inspection entirely

Modes can be set globally or per-channel:

CiscoAIDefensePlugin(
    mode="monitor",      # default for both
    llm_mode="enforce",  # override for LLM only
    mcp_mode="off",      # override for tools only
)

Violation callback¶

Use the on_violation callback to receive notifications for every violation in both monitor and enforce modes:

def handle_violation(result):
    print(f"Violation: {result.action} / {result.severity}")

CiscoAIDefensePlugin(
    mode="monitor",
    on_violation=handle_violation,
)

Retry and fail-open support¶

For automatic retry with exponential backoff, fail-open/fail-closed semantics, and structured Decision objects, use the AgentsecPlugin variant:

from aidefense_google_adk import AgentsecPlugin

app = App(
    name="my_app",
    root_agent=agent,
    plugins=[
        AgentsecPlugin(
            mode="enforce",
            fail_open=True,
            retry_total=3,
            retry_backoff=0.5,
        ),
    ],
)

Or at the per-agent level:

from aidefense_google_adk import make_agentsec_callbacks

cbs = make_agentsec_callbacks(mode="enforce", fail_open=True)
cbs.apply_to(agent)