← Atlassian MCP (mcp-atlassian)
Atlassian MCP (mcp-atlassian) — agentic threat model
The Atlassian MCP agent introduces high agentic risk due to its direct read/write access to sensitive organizational documentation and issue tracking systems, making it a prime target for indirect prompt injection via untrusted collaborator content.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.50 | |
| 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.
Not certain from the listing — The underlying foundation model is not specified as this is an MCP server integration. However, the model is highly vulnerable to indirect prompt injection and reprogramming via malicious instructions embedded in Confluence pages or Jira tickets.
Confluence and Jira act as the primary knowledge base and data operations layer. There is a severe risk of data poisoning and indirect prompt injection, as untrusted collaborators can edit pages or tickets to exfiltrate sensitive organizational data or manipulate agent behavior.
The agent framework exposes powerful tools for reading and writing to Jira and Confluence. Insecure tool integration or lack of strict input validation on tool arguments could allow an attacker to execute unauthorized API actions or modify critical project tracking data.
Not certain from the listing — The deployment environment depends on where the MCP host and server are run. The primary infrastructure threat is the exposure of the Atlassian API token, which if compromised, grants broad access to the organization's entire Atlassian suite.
Not certain from the listing — There are no mentioned built-in guardrails, logging, or observability features to detect anomalous tool calls, data exfiltration attempts, or malicious prompt injections occurring through the MCP interface.
The security posture relies heavily on the scope of the provided Atlassian API token. Without granular OAuth scopes or user-impersonation controls, the agent operates with the full permissions of the token owner, violating the principle of least privilege.
As an MCP tool, this agent is designed to be called by other orchestrator agents. This creates a risk of cascading failures and trust abuse, where a compromised upstream agent can abuse the Atlassian tools to modify documentation or delete Jira issues.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).