Globus Agent — agentic threat model
The Globus Agent presents a moderate-to-high risk profile due to its deep integration with sensitive employee PII and unstructured talent data, combined with automated communication and job processing capabilities. A compromise could lead to massive data exfiltration, biased automated hiring decisions, or unauthorized communications with candidates.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.50 | |
| Non-Determinism | 0.50 | |
| 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 specific foundation models powering Globus AI are not disclosed. Standard risks include prompt injection leading to biased talent matching or unauthorized extraction of training data patterns.
The agent ingests unstructured talent data, free text, and employee competencies. This creates a high-exposure surface for data poisoning (e.g., resumes engineered to exploit parser vulnerabilities) and unauthorized exfiltration of sensitive HR PII.
The agent orchestrates workforce requirements and automates job order processing. Vulnerabilities in the orchestration framework could allow attackers to manipulate job prioritization or hijack communication tools to send malicious links to candidates.
Not certain from the listing — The hosting environment (SaaS, private cloud, or on-premise) is not specified. Standard infrastructure risks include insecure API endpoints connecting the agent to internal HR databases.
Not certain from the listing — While performance tracking and analytics are mentioned, there is no detail on security-specific observability, guardrails, or drift detection for automated hiring decisions.
Handling employee and candidate data subjects the agent to strict compliance frameworks (GDPR, CCPA, and local labor laws). The listing does not detail access controls, encryption, or compliance certifications.
The listing references multiple 'AI Agents' working together to orchestrate workforce requirements. This multi-agent setup introduces risks of cascading failures or trust abuse if one agent in the pipeline is compromised.
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.