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TensorStax — agentic threat model

9.5AIVSS 9.5 · Critical

TensorStax poses a high agentic risk due to its autonomous capability to monitor logs and push fixes directly to critical data infrastructure like Spark, Airflow, and dbt. A compromise could lead to widespread data corruption, unauthorized data access, or malicious code execution within the enterprise data plane.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.8AARS uplift 0.72Factor sum 5.7/10Threat ×1.05Mitigation ×1.0
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.30
Dynamic Tool Use
0.80
Persistent Memory
0.50
Contextual Awareness
0.70
Dynamic Identity
0.60
Multi-Agent Interactions
0.10
Non-Determinism
0.60
Opacity & Reflexivity
0.60

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 — the underlying LLM is unspecified, but threats include prompt injection leading to unauthorized code generation or malicious pipeline fixes.

L2 · Data Operations✓ mapped

High risk due to direct integration with Spark, dbt, and data pipelines. Threats include data poisoning, unauthorized data access, and lack of lineage tracking for AI-generated models.

L3 · Agent Frameworks✓ mapped

Orchestrates tasks like building models and pushing fixes. Threats include insecure tool execution (Airflow/Spark command execution) and prompt injection hijacking the agent's planning phase to push malicious code.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — hosting details are unspecified, but the agent requires high-privilege access to internal networks/databases to interact with Spark/Airflow, risking lateral movement if compromised.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — although the agent monitors external logs, whether there are guardrails to inspect the fixes before they are pushed is unspecified, risking silent failures or drift.

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

Not certain from the listing — compliance with data privacy (GDPR/CCPA) is critical given access to company data stacks, but no access controls or audit logging features are detailed.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — no multi-agent or marketplace interactions are described, though integration with third-party plugins/tools could introduce supply chain risks.

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.