NOFireAI — agentic threat model
NOFireAI possesses a high-risk profile due to its deep integration into critical infrastructure (Kubernetes, databases, and observability platforms) and its capability to generate executable scripts and runbooks, making prompt injection or agent compromise highly impactful.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.90 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Integrates with external LLM providers (OpenAI, Mistral, LLaMA). Highly vulnerable to prompt injection attacks that could manipulate the generated root cause analysis or inject malicious commands into the generated remediation scripts and runbooks.
Ingests highly sensitive data from observability platforms, metrics, logs, Kubernetes, and databases. Risks include data exfiltration of sensitive database records or logs, and log/telemetry poisoning to mislead the root cause analysis engine.
Not certain from the listing — the specific orchestration framework is not detailed, but the agent's tool-calling capabilities for querying Kubernetes and databases present significant risks of tool misuse or unauthorized data access if the agent's planning logic is subverted.
Not certain from the listing — deployment architecture (SaaS vs. on-premise) is unspecified. However, storing and utilizing high-privilege credentials (Kubernetes tokens, database credentials) presents severe risks of credential theft and lateral movement if the hosting environment is compromised.
Not certain from the listing — no guardrails or evaluation mechanisms are mentioned. A lack of output validation on generated scripts could allow syntactically incorrect or destructive commands to be presented to SRE teams.
Not certain from the listing — no compliance certifications (e.g., SOC2, ISO 27001) or fine-grained access controls are specified, which are critical given the agent's access to production environments.
Not certain from the listing — there is no mention of multi-agent coordination or marketplace integrations, meaning ecosystem-level risks are currently minimal.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.