Dragonfruit AI — agentic threat model
Dragonfruit AI presents a moderate-to-high risk profile primarily driven by its role as a Web3 security advisor; a compromise or failure in its auditing logic could lead to catastrophic financial losses for users relying on its safety badges and risk assessments.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.40 |
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 underlying foundation model is unspecified. The primary threat is adversarial prompt injection or evasion techniques where a malicious smart contract's source code is obfuscated to bypass LLM-based detection of mint/freeze functions.
Not certain from the listing — The agent relies on real-time smart contract data, liquidity pool metrics, and holder concentration data. Gaps in data provenance or poisoning of the external blockchain APIs/vector stores could lead to incorrect risk ratings and false safety badges.
Not certain from the listing — The orchestration framework is not detailed. Potential threats include insecure tool integration where the agent's static analysis tools or blockchain parsers are exploited via malformed contract code or malicious RPC nodes.
Not certain from the listing — The hosting and sandboxing environment for analyzing untrusted smart contracts is unknown. If the agent executes dynamic analysis or dry-runs of contracts without strict sandboxing, it risks container escape or host compromise.
Not certain from the listing — No observability or evaluation guardrails are mentioned. The lack of transparent logging and drift detection could allow silent failures in the auditing logic, leading to undetected false negatives (missing a rug-pull mechanism).
Not certain from the listing — There is no mention of compliance frameworks, access controls, or third-party audits. The lack of verified identity and access management for issuing 'verification badges' poses a risk of unauthorized badge generation.
Not certain from the listing — No multi-agent interactions or marketplace integrations are described. If integrated into broader Web3 ecosystems, compromised security alerts could trigger automated cascading liquidations or panic-selling by downstream agents.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).