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Posium — agentic threat model

8.9AIVSS 8.9 · High

Posium poses moderate-to-high agentic risk due to its autonomous interaction with web and mobile applications, which requires dynamic tool use (browsers/emulators) and multi-agent coordination, potentially exposing staging environments to unauthorized actions if compromised.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 1.4Factor sum 5.6/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.20
Dynamic Tool Use
0.80
Persistent Memory
0.40
Contextual Awareness
0.70
Dynamic Identity
0.20
Multi-Agent Interactions
0.70
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely utilizes third-party foundation models to generate test cases. Threats include prompt injection via the application UI being tested, which could hijack the test generation process.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — requires access to application source code, DOM structures, or mobile application packages. Threats include the exfiltration of proprietary code or sensitive mock data used during testing.

L3 · Agent Frameworks✓ mapped

Orchestrates QA agents to interact with Web and Mobile applications. Threats include tool misuse where the agent executes destructive actions (e.g., deleting database records via UI) or is manipulated by malicious UI elements.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — being open source, it is likely self-hosted. Threats include container escape or host compromise if the testing environment is not properly sandboxed from the rest of the network.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — requires robust logging of agent decisions and test execution. Threats include blind spots where malicious actions performed by the agent are masked as standard test failures.

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

Not certain from the listing — security controls depend on the deployment environment. Threats include unauthorized users triggering test suites that interact with sensitive staging or production-like environments.

L7 · Agent Ecosystem✓ mapped

Utilizes multiple 'QA Agents' to automate testing. Threats include cascading failures or trust abuse between the coordinating agents, leading to unauthorized test execution paths or corrupted test states.

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.