Sherlock — agentic threat model
Sherlock presents a moderate-to-high risk profile primarily due to its access to real-time, sensitive audio and video streams from enterprise communication platforms, making confidentiality and privacy compliance (biometric data) its critical attack surfaces.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.50 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| 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 — likely utilizes multimodal models (audio, video, text) to detect deepfakes and coaching. Primary threats include adversarial evasion techniques by candidates to bypass detection, and model reprogramming.
Not certain from the listing — ingests real-time video/audio streams and generates evidence reports. Threats include unauthorized exfiltration of sensitive interview recordings, data leakage, and lack of clear data retention/deletion policies for candidate biometric data.
Not certain from the listing — orchestrates real-time stream analysis and report generation. Threats include insecure integration with video conferencing APIs and manipulation of the reporting logic to falsely clear or flag candidates.
Not certain from the listing — integrates directly with Zoom, Meet, and Teams, requiring high-privilege API tokens. Threats include compromise of these integration secrets, leading to unauthorized access to broader corporate communication channels.
Not certain from the listing — generates evidence reports for hiring managers. Threats include evaluation gaming where candidates exploit blind spots in the detection algorithms, and a lack of observability into false-positive rates.
While the listing claims a 'privacy-first approach', processing real-time video and audio of candidates introduces severe compliance risks under GDPR, CCPA, and AI regulations regarding biometric surveillance and automated decision-making without explicit consent.
Not certain from the listing — operates as a horizontal integration within communication platforms. No multi-agent interactions or marketplace dependencies are described.
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.