IBBS — agentic threat model
IBBS is a security evaluation agent focused on prompt-injection testing, presenting low direct operational risk but moderate ecosystem risk if its cryptographic badging mechanism or sandbox isolation is compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.40 | |
| Non-Determinism | 0.20 | |
| Opacity & Reflexivity | 0.20 |
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.
Not certain from the listing — the service tests external agents' foundation models against prompt injection, but its own underlying foundation model architecture is not specified.
Not certain from the listing — the service utilizes 5 specific adversarial prompt scenarios, but details regarding its own internal data operations, training data, or vector stores are not provided.
Not certain from the listing — while it orchestrates sandbox testing against target agents, the specific internal agent framework, planning mechanisms, or tool-calling implementation of IBBS itself are not detailed.
The service runs tests in a controlled sandbox environment to isolate adversarial prompt execution, and provides a local self-check tool to prevent external infrastructure exposure during initial developer testing.
The core capability is evaluation, specifically testing robustness against 5 real-world prompt-injection scenarios and generating verifiable cryptographic proof of the evaluation results.
Provides cryptographic signing of security badges to ensure independent verifiability and trust, serving as a compliance and assurance mechanism for third parties.
Designed to interact directly with external third-party agents within a sandbox to evaluate their security, presenting potential risks of cascading failures if the tested agent behaves maliciously during evaluation.
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.