Superposition — agentic threat model
Superposition acts as an AI headhunter, presenting moderate risk primarily centered around the handling of sensitive candidate PII, potential algorithmic bias in recruitment, and the risk of automated spear-phishing if outreach capabilities are compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.50 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.60 | |
| Opacity & Reflexivity | 0.50 |
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 relies on commercial LLMs for parsing resumes and drafting outreach. Vulnerable to prompt injection that could manipulate candidate scoring or generate toxic/biased recruitment messages.
Not certain from the listing — processes high volumes of candidate profiles, resumes, and startup requirements. Risks include PII exfiltration, unauthorized scraping, and data poisoning of candidate databases or vector stores.
Not certain from the listing — orchestrates search queries and candidate filtering. Insecure tool integration could allow malicious resume payloads to exploit parsing libraries or orchestrator logic.
Not certain from the listing — requires secure hosting to protect API integrations with job boards, LinkedIn, or email delivery services. Compromise could lead to API key theft or infrastructure abuse.
Not certain from the listing — requires robust observability to detect and prevent algorithmic bias, drift in candidate matching criteria, and anomalous bulk data exports.
Not certain from the listing — must adhere to strict data privacy regulations (GDPR, CCPA) regarding candidate consent and employment non-discrimination laws governing automated hiring tools.
Not certain from the listing — may integrate with external Applicant Tracking Systems (ATS) or HR platforms. Vulnerabilities in these integrations could lead to cascading data exposure across the startup's HR ecosystem.
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.