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← Kane CLI By TestMu AI

Kane CLI By TestMu AI — agentic threat model

8.9AIVSS 8.9 · High

Kane CLI presents a high agentic risk profile due to its ability to drive a real Chrome browser locally or in CI/CD environments, combined with its native integration with other autonomous coding agents, creating a significant vector for indirect prompt injection and local system compromise.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.83Factor sum 5.3/10Threat ×1.05Mitigation ×0.95
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.20
Dynamic Tool Use
0.80
Persistent Memory
0.20
Contextual Awareness
0.60
Dynamic Identity
0.30
Multi-Agent Interactions
0.80
Non-Determinism
0.50
Opacity & Reflexivity
0.40

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 relies on external commercial LLMs (e.g., Claude, Gemini) to interpret natural language and drive the browser. Primary threats include prompt injection and model reprogramming to bypass safety guardrails during web navigation.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — no explicit RAG or vector database is mentioned. However, the tool processes DOM structures, screenshots, and test execution data, which could be vulnerable to data exfiltration if malicious web content is processed.

L3 · Agent Frameworks✓ mapped

The agent framework orchestrates complex browser automation, autoheal logic, and vision-based waiting. The primary threat is indirect prompt injection, where a malicious website visited by the agent contains instructions that hijack the agent's execution flow, leading to unauthorized tool use.

L4 · Deployment & Infrastructure✓ mapped

Runs as a local CLI tool driving a real Chrome browser. If the execution environment is not strictly sandboxed, a compromised browser session could lead to local file access, SSRF against internal network resources, or session hijacking of developer credentials.

L5 · Evaluation & Observability✓ mapped

Provides deterministic pass/fail verification, shareable evidence links, and Playwright exports. A threat exists where an attacker could manipulate the generated evidence links or Playwright scripts to mask malicious activities or spoof successful test runs.

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

Not certain from the listing — there is no mention of built-in authentication, access control policies, or compliance certifications for the CLI tool or its evidence-sharing platform.

L7 · Agent Ecosystem✓ mapped

Designed as an 'agent-native' tool to be invoked by other agents like Claude Code, Cursor, and Gemini CLI. This creates a multi-agent trust boundary threat, where a compromised upstream coding agent can abuse Kane CLI to execute arbitrary web actions or exfiltrate data.

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.