devflow-mcp — agentic threat model
devflow-mcp acts as a high-risk orchestrator with access to GitHub, Jira, and Slack, creating a single point of compromise where prompt injection can trigger unauthorized code changes, data exfiltration, and social engineering.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.60 | |
| Multi-Agent Interactions | 0.40 | |
| Non-Determinism | 0.70 | |
| 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.
Not certain from the listing — the underlying foundation model is not specified, but it is highly vulnerable to indirect prompt injection via untrusted pull requests, commit messages, or Jira tickets which could hijack model output.
Not certain from the listing — there is no explicit mention of RAG or vector databases, but the agent processes sensitive codebase data, PR diffs, and issue tracker content which could be exfiltrated.
The agent framework integrates highly sensitive tools (GitHub, Jira, Slack APIs). Insecure tool integration or lack of strict input validation allows malicious inputs to trigger unauthorized actions like merging code or posting to Slack.
The deployment aggregates GitHub, Jira, and Slack tokens on a single server. Compromise of this host or container exposes all three high-value environments simultaneously, enabling lateral movement.
Not certain from the listing — there are no mentioned guardrails, evaluation frameworks, or observability tools to detect anomalous agent behavior or malicious tool execution before actions are taken.
The agent lacks visible authorization boundaries or human-in-the-loop controls, meaning a single set of credentials grants broad, automated write access across multiple enterprise platforms.
The agent operates in a multi-tool ecosystem (MCP), where a compromise in one connected service (e.g., a malicious Slack message or Jira comment) can cascade to execute unauthorized actions in GitHub.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).