TimeClaw is an exploratory execution learning system that turns multiple valid tool-use paths into hierarchical distilled experience for improved time-series reasoning without test-time adaptation.
Clawkeeper: Comprehensive safety protection for openclaw agents through skills, plugins, and watchers.arXiv preprint arXiv:2603.24414, 2026
12 Pith papers cite this work. Polarity classification is still indexing.
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Introduces ClawTrojan benchmark achieving 95.5% ASR for multi-step trojan attacks in agentic harnesses and DASGuard defense that sanitizes control content from untrusted sources.
A3S-Bench evaluates LLM agents against temporal, spatial, and semantic evasions, raising average risk trigger rates from 28.3% to 52.6% across 2,254 trajectories and 20 scenarios.
LivePI benchmark reports indirect prompt injection success rates of 10.7-29.6% across five models on seven input surfaces and shows a two-layer defense blocking all malicious completions while preserving utility.
DeepTrap automates discovery of contextual vulnerabilities in OpenClaw agents via trajectory optimization, showing that unsafe behavior can be induced while preserving task completion and that final-response checks are insufficient.
SUDP is a three-party protocol in which an agent proposes an operation, the user issues a fresh grant, and a custodian executes it, satisfying seven security properties for bounded secret use without reusable authority transfer.
Arbiter-K is a governance-first architecture that turns probabilistic agent reasoning into discrete instructions with runtime taint propagation to block unsafe actions, reporting 76-95% interception rates and a 92.79% gain over baseline policies on two test systems.
All six evaluated OpenClaw agent frameworks exhibit substantial security vulnerabilities, with reconnaissance behaviors as the most common weakness and agent systems proving significantly riskier than isolated backbone models.
CapSeal introduces a capability-sealed broker architecture that lets AI agents perform constrained secret-using actions without ever receiving the secrets themselves.
The paper develops a unified framework that organizes computer-use agent reliability around perception-decision-execution layers and creation-deployment-operation-maintenance stages to map security and alignment interventions.
Nori Bot is a 17-DoF dual-arm mobile manipulator costing $947 with a 600 mm Z-axis lift, Raspberry Pi proactive control, and current-based servo protection.
A survey that categorizes threats to OpenClaw agents including skill poisoning and cognitive manipulation and reviews defense mechanisms.
citing papers explorer
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Nori Bot: A Sub-$1,000 Floor-to-Counter Mobile Manipulator
Nori Bot is a 17-DoF dual-arm mobile manipulator costing $947 with a 600 mm Z-axis lift, Raspberry Pi proactive control, and current-based servo protection.