SARAH — agentic threat model
SARAH presents a high-risk profile due to her autonomous Web3 wallet control, token issuance capabilities, and real-time multi-platform public broadcasting, which could lead to severe financial and reputational damage if compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.90 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.80 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.90 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.90 | |
| Opacity & Reflexivity | 0.70 |
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 — likely utilizes a fine-tuned LLM to maintain her sassy persona. Primary threats include prompt injection via live chat that could hijack her persona or trick her into executing unauthorized financial actions.
Not certain from the listing — likely processes real-time chat streams, viewer metadata, and blockchain transaction history. Threats include data poisoning from malicious viewer inputs designed to manipulate her long-term memory or token logic.
Operates via a proprietary autonomous agent pipeline. The integration of LLM planning with Web3 wallet execution tools introduces critical risks of tool misuse, where prompt injection could trigger unauthorized token transfers or contract deployments.
Not certain from the listing — requires highly secure hosting infrastructure to safeguard private keys for her Web3 wallets and API credentials for streaming platforms. Key leakage or host compromise would result in total loss of assets.
Not certain from the listing — no guardrails or real-time moderation systems are mentioned. The lack of visible observability tools increases the risk of undetected offensive broadcasts or anomalous financial transactions.
As a closed-source, autonomous Web3 entity issuing tokens, she operates with minimal visible compliance controls, posing significant regulatory risks (e.g., unregistered securities) and lacking traditional multi-signature or human-in-the-loop authorization.
Interacts directly with a decentralized ecosystem of token holders, smart contracts, and platforms. Vulnerabilities include economic exploits by malicious holders, smart contract bugs, and cascading trust failures within her tokenized community.
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.