Runtime security monitoring for AI agents. In-process. No data leaves your environment.
Project description
scandar-guard
Runtime security monitoring for AI agents. Drop-in wrapper for Anthropic, OpenAI, LangChain, CrewAI, and AutoGen.
Zero data leaves your environment. All inspection runs in-process.
Install
pip install scandar-guard
Quick Start
from anthropic import Anthropic
from scandar_guard import guard, GuardConfig
client = guard(Anthropic(), GuardConfig(
agent_id="my-agent",
asg_telemetry=True,
asg_api_key="sk_your_key",
))
# Use as normal — Guard monitors every call
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}],
)
Context Manager (recommended)
from scandar_guard import guard_session, GuardConfig
with guard_session(Anthropic(), GuardConfig(
agent_id="my-agent",
asg_telemetry=True,
asg_api_key="sk_your_key",
)) as client:
response = client.messages.create(...)
# session_end telemetry sent automatically on exit
CrewAI
from crewai import Crew
from scandar_guard.integrations.crewai import ScandarCrewAIMonitor
monitor = ScandarCrewAIMonitor(api_key="sk_xxx")
crew = Crew(
agents=[...],
tasks=[...],
step_callback=monitor.step_callback,
task_callback=monitor.task_callback,
)
AutoGen
from autogen import ConversableAgent
from scandar_guard.integrations.autogen import register_scandar_hooks
agent = ConversableAgent(name="my-agent", ...)
register_scandar_hooks(agent, api_key="sk_xxx")
What it detects
- Prompt injection (direct, indirect, encoded, multi-turn)
- Tool argument injection and data exfiltration sequences
- Privilege escalation and anomalous tool call patterns
- Behavioral profile deviations with per-agent baselines
- 140+ detection rules mapped to OWASP LLM Top 10
Scandar Overwatch
When asg_telemetry=True and asg_api_key are set, Guard sends anonymized telemetry (tool names, finding categories, threat scores — never prompts or content) to the Scandar Overwatch for fleet-wide visibility.
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