Megan — agentic threat model
Megan exhibits a high agentic risk profile due to its deep integrations with critical business systems (ATS, Slack, and corporate calendars) and its autonomous capability to screen candidates and schedule events. The primary attack vectors include prompt injection via untrusted candidate resumes and unauthorized actions within connected enterprise APIs.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| 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 models are not specified. Standard risks of adversarial prompt injection via uploaded candidate resumes or interview transcripts could lead to model reprogramming or biased evaluation outputs.
Processes highly sensitive candidate PII, resumes, and interview notes. A major threat is indirect prompt injection via malicious resumes designed to force the agent to recommend a candidate or exfiltrate other applicants' data.
The agent orchestrates multi-step workflows including screening, scheduling, and Slack notifications. Vulnerabilities here include insecure tool integration with ATS and calendar APIs, potentially allowing unauthorized scheduling or data modification.
Not certain from the listing — deployment infrastructure, hosting environment, and sandboxing mechanisms for processing untrusted resume files are not disclosed.
Not certain from the listing — there is no mention of real-time guardrails, drift detection, or logging mechanisms to monitor Megan's screening decisions for bias or manipulation.
Not certain from the listing — while handling recruiting data requires strict compliance (GDPR, CCPA, and local AI hiring laws), the listing does not cite specific compliance certifications, access controls, or audit logs.
Interacts with external ecosystems via Slack, Google/Microsoft Calendars, and ATS platforms. A compromise of Megan could lead to cascading failures, such as unauthorized calendar manipulation or malicious Slack messaging within the organization.
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.