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GitGuardian MCP Server (ggmcp) — agentic threat model

8.8AIVSS 8.8 · High

The GitGuardian MCP Server introduces significant agentic risk by granting AI agents direct access to read source code, manage secret incidents, and generate honeytokens, creating a high-value target for credential exfiltration and unauthorized remediation actions.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.74Factor sum 4.7/10Threat ×1.05Mitigation ×0.95
Autonomy of Action
0.60
Goal-Driven Planning
0.40
Self-Modification
0.10
Dynamic Tool Use
0.80
Persistent Memory
0.30
Contextual Awareness
0.70
Dynamic Identity
0.50
Multi-Agent Interactions
0.40
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 — The underlying foundation model is not specified, but it is vulnerable to prompt injection that could trick the agent into ignoring detected secrets or leaking scanned code snippets in its output.

L2 · Data Operations✓ mapped

The agent directly ingests and processes sensitive source code and secret metadata. A primary threat is data exfiltration or exposure of these secrets during the scanning and triage process.

L3 · Agent Frameworks✓ mapped

The agent framework integrates tools for secret scanning, incident triage, and honeytoken generation. Insecure tool integration or prompt injection could allow an attacker to trigger unauthorized incident closures or generate malicious honeytokens.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The deployment environment of the MCP server is unspecified, but it requires secure sandboxing and strict network controls to prevent lateral movement if the host running the MCP server is compromised.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of built-in evaluation, logging, or guardrails to monitor the agent's remediation decisions, creating a risk of undetected malicious actions or false negatives in secret detection.

L6 · Security & Compliance (cross-cutting)✓ mapped

The agent handles highly sensitive operations (remediation, triage, secret access). It requires robust identity and access management (IAM) to ensure the agent only accesses repositories and incidents the user is authorized to view.

L7 · Agent Ecosystem✓ mapped

In a multi-agent MCP ecosystem, other connected agents could exploit this agent's tools to read repository contents or manipulate security incidents, leading to cascading trust failures.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).