Surge AI — agentic threat model
Surge AI is a read-only market intelligence platform with low agentic risk, as it lacks autonomous execution, transactional capabilities, or multi-agent coordination. Its primary security risks lie in data poisoning of the public signals it ingests and potential confidentiality breaches of proprietary business intelligence queries.
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 | 0.20 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.30 |
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 uses proprietary or fine-tuned LLMs for sentiment analysis and signal filtering. Threats include adversarial inputs in public data (e.g., coordinated bot campaigns on Reddit/TikTok) poisoning the sentiment/trend outputs.
Not certain from the listing — ingests trillions of public internet signals (Google, Reddit, Amazon, TikTok, YouTube). High risk of data poisoning from malicious web content, SEO manipulation, or bot farms skewing the market intelligence.
Not certain from the listing — orchestration details are not disclosed. Likely uses a pipeline architecture rather than a complex agentic framework. Threats include insecure tool integration with external APIs or scrapers.
Not certain from the listing — hosted as a closed-source SaaS platform. Standard cloud security threats apply, such as unauthorized access to the analytics dashboard or data storage.
Not certain from the listing — no details on monitoring or guardrails. Gaps in drift detection could lead to undetected degradation in sentiment analysis accuracy over time.
Not certain from the listing — mentions a 'privacy-friendly model' without cookies, but lacks details on enterprise access controls, compliance standards (e.g., SOC 2), or audit logging.
Not certain from the listing — operates as a standalone SaaS platform with no indicated multi-agent or marketplace integrations.
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.