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← ExoClaw

ExoClaw — agentic threat model

8.8AIVSS 8.8 · High

ExoClaw presents a moderate-to-high risk profile due to its 24/7 autonomous operation and deep integration into collaborative messaging platforms (Slack, Discord, WhatsApp), where compromised credentials or prompt injection could lead to unauthorized actions or data exposure across corporate communication channels.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.77Factor sum 4.9/10Threat ×1.05Mitigation ×0.95
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.20
Dynamic Tool Use
0.60
Persistent Memory
0.50
Contextual Awareness
0.50
Dynamic Identity
0.30
Multi-Agent Interactions
0.20
Non-Determinism
0.60
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — The specific foundation models (e.g., GPT-4, Claude) powering the OpenClaw agent are not disclosed. Standard LLM threats like prompt injection, adversarial reprogramming, and misaligned outputs remain a baseline risk depending on the chosen backend model.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No details are provided regarding data storage, vector databases, or RAG pipelines. There is a risk of data exfiltration or memory poisoning if chat histories from connected messaging apps are stored insecurely.

L3 · Agent Frameworks✓ mapped

ExoClaw deploys OpenClaw agents, which orchestrate tasks and connect to messaging APIs (Slack, Discord, Telegram, WhatsApp). Insecure tool integration or prompt injection via messaging channels could lead to unauthorized tool execution or command hijacking.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — While 'private secure server' hosting is claimed, the underlying infrastructure, sandboxing mechanisms, and secrets management for messaging API tokens are not detailed, posing risks of container compromise or credential theft.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — The phrase 'while you stay in control' implies some monitoring or human-in-the-loop oversight, but concrete evaluation, logging, guardrails, or drift detection mechanisms are not specified.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — No formal compliance certifications (e.g., SOC2, ISO 27001) or specific identity/access management (IAM) policies are mentioned beyond the general claim of a 'private secure server'.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The platform focuses on deploying individual OpenClaw agents connected to messaging apps. It is unclear if these agents interact with other agents or third-party marketplaces, limiting immediate multi-agent cascading risks.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).