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Launchumo — agentic threat model

5.8AIVSS 5.8 · Medium

Launchumo is a low-risk, low-autonomy AI directory platform. Its primary security risks are traditional web vulnerabilities, such as malicious submissions, link hijacking, or XSS, rather than complex agentic execution threats.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.6AARS uplift 0.2Factor sum 0.5/10Threat ×0.9Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.00
Self-Modification
0.00
Dynamic Tool Use
0.00
Persistent Memory
0.10
Contextual Awareness
0.10
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.10
Opacity & Reflexivity
0.10

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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — Launchumo is described as a directory and submission platform. If it utilizes foundation models for automated categorization or description generation, it faces risks of prompt injection or biased output generation.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — The platform manages a database of submitted AI SaaS products. Key threats include database poisoning via malicious submissions (e.g., SEO spam, malicious URLs) and lack of data provenance verification.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — There is no indication of an active agentic framework or orchestration layer. If any automated workflows exist for processing submissions, they could be vulnerable to insecure tool integration.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Standard web application hosting threats apply. Vulnerabilities like SQL injection, cross-site scripting (XSS) in submission forms, or server misconfigurations could compromise the directory.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No automated evaluation, guardrails, or observability mechanisms are mentioned beyond a manual or semi-automated 'review process' for submissions.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — The directory does not specify its access control mechanisms, user authentication protocols, or compliance alignments (such as GDPR for submitter data).

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — While it indexes other AI tools, it does not programmatically interact with them. The primary ecosystem risk is serving as a trusted vector that inadvertently directs users to malicious or compromised third-party AI tools.

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.