agent-bom runtime
AI Runtime Security Monitoring and Context Graph Analysis
Install & Use
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Help me install this AI Skill: agent-bom runtime. It is used for: AI Runtime Security Monitoring and Context Graph Analysis Full Skill content: https://321skill.com/skills/agent-bom-runtime/raw/index.md Read that page and install it.
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This Skill addresses the pain points of runtime security monitoring for AI agents. In real-world deployments, AI agent behavior is difficult to track. Correlating lateral movement, audit logs, and CVE analysis often relies on manual effort, which is inefficient and prone to oversight. agent-bom runtime enables security teams to quickly pinpoint anomalous behavior through context graph analysis, runtime audit log correlation with CVE discovery, and vulnerability analysis queries.
Usage is straightforward. Simply install agent-bom in your terminal and invoke its three core tools via natural language commands: context_graph (builds agent context graphs and detects lateral movement), analytics_query (queries vulnerability trends and historical events), and runtime_correlate (cross-references audit logs with CVE data). You can then directly instruct the AI with prompts like "Analyze the context graph of the current agent" or "Correlate recent CVE findings from audit logs."
It is ideal for operations engineers and agent developers who need to monitor AI agent security, especially for enterprises that have deployed multiple AI agents or agent workflows and require real-time visibility into agent behavior, security event tracking, and rapid response.
We recommend running runtime_correlate periodically within CI/CD pipelines and persisting analytical data in ClickHouse to track historical trends. Note that it primarily relies on user-provided JSONL-formatted audit log files, does not automatically discover files on disk, and operates offline by default to fully protect user privacy.
Key Features
Unlike traditional APM tools (e.g., Datadog APM), agent-bom runtime is specifically designed to model the runtime context graph of AI agents, detect lateral movement paths, and automatically correlate events from audit logs with CVE databases. Traditional APM typically focuses on application performance metrics and lacks the specialized behavioral security analysis capabilities required for AI agents.
Limitations
Requires a Python 3.11+ runtime environment. Optional dependencies include kubectl (for Kubernetes context) and ClickHouse (for analytical storage). Audit logs must be in the JSONL format generated by agent-bom proxy; it cannot directly read log files in other formats.
FAQ
Are API keys required for configuration?
Zero credentials required; no API keys are needed. Optionally, you can configure a ClickHouse URL for persistent analytical storage, but it will not automatically discover or infer credentials.
Which operating systems are supported?
Supports macOS, Linux, and Windows, but requires Python 3.11+.
Installation guide for AI assistants
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Visit https://321skill.com/skills/agent-bom-runtime/raw/index.md to read the original Skill definition (Markdown format) for agent-bom runtime, and install it according to the instructions.
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