SWE-Agent — agentic threat model
SWE-Agent presents a high agentic risk profile due to its autonomous capability to execute code and write pull requests directly to GitHub. Without explicit sandboxing or human-in-the-loop controls mentioned in the listing, a compromise could lead to arbitrary code execution and supply chain attacks.
OWASP AIVSS score rationale
| Autonomy of Action | 0.90 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.80 | |
| Dynamic Identity | 0.60 | |
| Multi-Agent Interactions | 0.10 | |
| 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.
SWE-Agent relies on foundation models like GPT-4. It is highly vulnerable to adversarial prompt injection and goal hijacking, which could trick the agent into generating malicious code or executing unauthorized commands.
Not certain from the listing — SWE-Agent navigates local codebases and GitHub repositories, but details on vector databases, RAG pipelines, or data poisoning protections are not specified.
The custom Agent-Computer Interface (ACI) acts as the orchestration framework. Vulnerabilities here could allow tool misuse, where the agent is manipulated into executing arbitrary system commands or editing critical files outside the target repository.
Not certain from the listing — While the agent executes code commands, the listing does not specify if execution is sandboxed (e.g., within Docker containers) or how secrets like GitHub tokens are securely stored and isolated.
Not certain from the listing — Real-time feedback is mentioned, but specific logging, guardrails, or observability frameworks to detect anomalous agent behavior are not detailed.
Not certain from the listing — No explicit security compliance, identity management, or authorization policies are detailed in the description to govern the agent's write access.
Not certain from the listing — The description focuses on a single-agent setup interacting with GitHub, with no mention of multi-agent orchestration or marketplace interactions.
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.