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Awesome OpenClaw Research Awesome

Awesome OpenClaw Research

A curated collection of academic papers, industry reports, datasets, and tools for the OpenClaw AI agent ecosystem.
Companion repository for our survey: A Survey of the OpenClaw Ecosystem β€” From Platform Extensibility to Constraint Design.

Papers Benchmarks Reports Updated

OpenClaw β€” the open-source, self-hosted AI agent platform created by Peter Steinberger (Clawdbot β†’ Moltbot β†’ OpenClaw, January 29, 2026) β€” has generated 74 academic papers, 23 benchmarks, and 18+ major industry reports in under four months. This repository organizes the research landscape using the PSEA (Platform–Security–Societies–Deployment) taxonomy introduced in our survey.

Thesis of the survey. OpenClaw is best understood as a stress test for open personal-agent ecosystems. Its open Skills, persistent Memory, and always-on Heartbeat make capability easy to extend, but the same openness creates governance, security, social, and deployment problems. The literature converges on one recurring tradeoff: extensibility accelerates capability growth, but trustworthy use requires explicit constraints on Skills, Memory, autonomy, domain actions, and evaluation. The repository is organized to make this tradeoff visible at every level.


Statistics at a Glance

Layer Section Papers Sub-topics
πŸ”§ P Platform 10 Agent learning β†’ platform improvement; Skill ecosystem governance
πŸ›‘οΈ S Security 33 Threat landscape; attacks; defenses (execution + supply chain)
🌐 S Societies 22 Statistical sociality & shallow interaction; safety drift
πŸš€ D Deployment 9 Robotics; healthcare; scientific research
Total 74

Separately, the survey catalogs 23 benchmarks as an orthogonal evaluation lens β€” many of these are released by papers already counted above (e.g. CIK-Bench, ClawSafety, SkillFortifyBench), so they are tracked in their own Benchmarks section rather than added to the PSEA totals.


Contents

πŸ“„ Research Papers

πŸ“ Resources


πŸ”§ Platform

How OpenClaw is built and how it improves itself. The literature shifts from improving individual agents to governing the Skill ecosystem they depend on. (10 papers)

βš™οΈ Agent Learning β†’ Platform Improvement (5)

Continuous improvement runs through Skills and runtimes, not weights alone.

TitleDateKey ContributionLinks
OpenClaw-RL: Train Any Agent Simply by TalkingMar 2026Async RL from live interaction signals; combines evaluative and directive rewardsPaper Stars
MetaClaw: Just Talk β€” An Agent That Meta-Learns and Evolves in the WildMar 2026Continual meta-learning; updates both weights and the Skill library from failure trajectoriesPaper
SemaClaw: General-Purpose Personal AI Agents through Harness EngineeringApr 2026DAG-based orchestration, PermissionBridge safety, three-tier context, agentic-wiki skillPaper
ClawGym: A Scalable Framework for Building Effective Claw AgentsApr 2026Mines raw ClawHub Skills into training tasks and a benchmark β€” marketplace as training substratePaper
OpenCLAW-P2P: Decentralized Framework for Collective AI IntelligenceApr 2026Decentralized agent network with DHT, federated learning, and formal verificationPaper GitHub

πŸ“¦ Skill Growth β†’ Ecosystem Governance (5)

A larger ClawHub is not automatically a better one. Clone inflation, bloat, discoverability, and submission-time risk are all platform-level concerns.

TitleDateKey ContributionLinks
SkillClone: Multi-Modal Clone Detection ⭐ ASE 2026Mar 202675% of ClawHub Skills are cloned; ecosystem inflated ~3.5Γ—; clones amplify supply-chain riskPaper
SkillReducer: Optimizing LLM Agent Skills for Token EfficiencyMar 2026>60% of Skill body is non-actionable boilerplate; compressing improves downstream performancePaper
Red Skills or Blue Skills? Submission-Time Risk PredictionApr 2026Simple classifiers can triage ClawHub submissions before publication (11,010-skill study)Paper
How Well Do Agentic Skills Work in the Wild? (Skills-in-the-Wild)Apr 2026Performance drops sharply when agents must locate the right Skill among 34K real candidatesPaper
SkillClaw: Let Skills Evolve Collectively with Agentic EvolverApr 2026Cross-user collective Skill evolution from autonomous trajectory aggregationPaper

πŸ’‘ Key Takeaway. OpenClaw's platform literature reveals the tradeoff between extensibility and governance: openness lets the agent and the Skill ecosystem improve, but turns ClawHub from a feature into a critical dependency. The challenge is not to add more Skills, but to ensure they stay safe, compact, and discoverable.

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πŸ›‘οΈ Security

Open Tools, community Skills, messaging channels, persistent Memory, and Heartbeat expand the attack surface. Research moves from isolated vulnerability reports β†’ execution-path attacks β†’ autonomous/persistent attacks; defenses form a layered stack but leave Memory governance unresolved. (33 papers)

πŸ” Threat Landscape (12)

Systemic exposure across components, persistent state, and trajectory-level failures.

TitleDateKey ContributionLinks
FASA: Uncovering Security Threats in Autonomous AgentsMar 2026Tri-layered risk taxonomy with full-lifecycle defense architecturePaper Stars
Taming OpenClaw: Security Analysis and MitigationMar 2026Five-stage lifecycle threat model; point defenses fail cross-stage attacksPaper
A Systematic Taxonomy of Security Vulnerabilities (OpenClaw Kill Chain)Mar 2026Analysis of 190 advisories across 10 attack surfaces; individually moderate flaws chain into RCEPaper
Don't Let the Claw Grip Your HandMar 2026Empirical red-teaming across six LLMs; human-in-the-loop defense layerPaper Stars
From Assistant to Double Agent (PASB)Feb 2026First end-to-end benchmark for personalized agent securityPaper Stars
ClawTrap: MITM-Based Red-Teaming FrameworkMar 2026First network-layer red-teaming framework for agent systemsPaper
A Trajectory-Based Safety Audit of ClawdbotFeb 2026Trajectory-level audit; OpenClaw fails completely on intent misunderstandingPaper Stars
Your Agent, Their Asset (CIK Taxonomy)Apr 2026Capability/Identity/Knowledge taxonomy; ASR 24.6% β†’ 64–74% under single-dimension state poisoningPaper
A Systematic Security Evaluation of OpenClaw and Its Variants (SecEval)Apr 2026205 tests across OpenClaw/AutoClaw/QClaw/KimiClaw/MaxClaw/ArkClawPaper
ClawSafety: "Safe" LLMs, Unsafe AgentsApr 2026120 scenarios Γ— 5 backbones Γ— 2,520 trials; ASR 40–75%; SKILL.md highest-trust highest-riskPaper
Forensic Foundations for OpenClaw AgentsApr 2026First agentic-AI forensic study; agent artifact taxonomy; nondeterminism challenges for DFIRPaper
Agents of ChaosFeb 2026Empirical study of failure modes in deployed agent systemsPaper

πŸ”₯ Attacks (6)

From malicious Skills to worms, denial-of-wallet, and memory pollution. The attack surface shifts from malicious commands to ordinary information flows the agent chooses to read, remember, and reuse.

TitleDateKey ContributionLinks
Skill-Inject: Measuring Agent Vulnerability to Skill File AttacksFeb 2026202 injection-task pairs; harmful instructions in trusted Skills are followed at high ratesPaper Stars
Clawdrain: Token Exhaustion via Tool-Calling ChainsMar 2026Trojanized Skill triggers massive token amplification β€” denial-of-walletPaper
BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill PoisoningApr 2026Bundled model artifacts can be backdoored while preserving benign-side behaviorPaper
SkillAttack: Automated Red Teaming of Agent SkillsApr 2026Reveals latent vulnerabilities in popular community Skills without modifying themPaper
ClawWorm: Self-Propagating Attacks Across Agent EcosystemsMar 2026First self-replicating worm for a production agent frameworkPaper
MissClaw / Mind Your HEARTBEAT: Silent Memory Pollution via Background ExecutionMar 2026Zero-click memory pollution β€” ordinary browsing content becomes persistent contextPaper

πŸ›‘οΈ Defenses (15)

Three boundaries: (a) execution-layer isolation/enforcement around dangerous Tools, (b) supply-chain scanning before Skills enter the marketplace, and (c) a still-missing fourth layer β€” provenance-aware memory governance.

🧱 Execution-layer (structural, runtime, and assurance)

TitleDateKey ContributionLinks
Agent Privilege Separation Against Prompt InjectionMar 2026Structural defense: agent processing untrusted content never holds access to dangerous ToolsPaper
SafeClaw-R: Safe and Secure Multi-Agent Personal AssistantsMar 2026System-level invariant enforcement over the execution graph; 97.8% malicious-Skill detectionPaper
OpenClaw PRISM: Zero-Fork Runtime Security LayerMar 2026Defense-in-depth across 10 lifecycle hooks with risk accumulation and decayPaper
Aethelgard: Learned Capability GovernanceApr 2026Four-layer adaptive governance with PPO-learned minimum-viable-capability policyPaper
RouteGuard: Internal-Signal Detection of Skill PoisoningApr 2026Detects Skill poisoning before execution via model-internal signalsPaper
Proof-of-Guardrail (PoG)Mar 2026TEE-based cryptographic attestation that guardrails actually executePaper
OAP: Deterministic Pre-Action Authorization for Autonomous AI AgentsMar 2026Enforces deterministic authorization before each Tool callPaper
VeriGrey: Greybox Agent ValidationMar 202633% gain over black-box agent validation on AgentDojoPaper
Governance Architecture for Autonomous Agent Systems (LGA)Mar 2026Threats, framework, and engineering practice for governance layersPaper

πŸ”— Supply-chain (marketplace-level scanning)

TitleDateKey ContributionLinks
SkillFortify: Formal Analysis and Supply Chain SecurityMar 2026First formal supply-chain framework with Dolev-Yao attacker model for SkillsPaper Stars
SkillSieve: Hierarchical Triage for Malicious Agent SkillsApr 2026Three-layer regex β†’ LLM-sub-task β†’ LLM-jury detection on 49,592 ClawHub Skills; 0.800 F1Paper
SkillProbe: Multi-Agent Security AuditingMar 2026Multi-agent auditing reveals most popular Skills fail rigorous security checksPaper
Malicious Or Not: Repository Context for Skill ClassificationMar 2026238K Skills across 4 registries; repository context dramatically changes estimated prevalencePaper
HarmfulSkillBench: How Do Harmful Skills Weaponize Your Agents?Apr 2026Registry-scale harmfulness measurement of Skill loadingPaper
"Elementary, My Dear Watson" β€” Detecting Malicious Skills (MalSkills)Mar 2026Neuro-symbolic reasoning across heterogeneous Skill artifactsPaper

πŸ’‘ Key Takeaway. OpenClaw security is expanding from execution control to memory governance. Existing defenses protect Tools, execution traces, and Skill supply chains, but they do not yet control what an autonomous agent reads, stores in Memory, and later acts on. The next defense layer must be provenance-aware memory governance (see Open Problems).

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🌐 Societies

Moltbook β€” a Reddit-style platform of OpenClaw-powered AI agents β€” became the first large-scale natural experiment in agent-only social interaction. The literature reveals a consistent gap between looking social and being socially reliable. (22 papers)

πŸ“Š Statistical Sociality & Shallow Interaction (17)

At the aggregate level, Moltbook reproduces familiar online-community statistics. At the interaction level, it is dominated by shallow replies, duplicate content, and extreme attention concentration.

TitleDateKey ContributionLinks
Collective Behavior of AI Agents: the Case of MoltbookFeb 2026Large-scale statistical analysis; activity heavy-tailed, popularity power-law, attention decayPaper
The Anatomy of the Moltbook Social GraphFeb 2026>93% of comments receive no reply; minimal reciprocity; frequent duplicate postsPaper Stars
Social Simulacra in the Wild: AI vs Human CommunitiesMar 2026Participation far more unequal than Reddit; communities share authors, not normsPaper
Let There Be Claws: Early SNA of AI Agents on MoltbookFeb 2026Extreme attention concentration; posting volume and content quality decoupledPaper
Exploring Silicon-Based SocietiesFeb 2026"Data-driven silicon sociology" framework; emergent community archetypesPaper
'Humans welcome to observe': A First Look at MoltbookFeb 2026First measurement study with topic taxonomy and toxicity analysisPaper
The Rise of AI Agent CommunitiesFeb 2026Discourse analysis showing functional utility drives agent influencePaper
Emergence of Fragility in LLM-based Social NetworksMar 2026Core-periphery structure reveals vulnerability to targeted hub attacksPaper
MoltNet: Understanding Social Behavior of AI AgentsFeb 2026Selective mimicry of human behavior; persona drift after social rewardsPaper Stars
Fast Response or Silence: Conversation Persistence on MoltbookFeb 2026Two-part persistence decomposition; low incidence is the binding coordination bottleneckPaper
Comparative Analysis of Reddit vs MoltbookFeb 2026First topological comparison; Moltbook operates as broadcast network, not communityPaper
Informal Learners at MoltbookFeb 2026Extreme broadcasting inversion; parallel monologues dominate interactionPaper
Peer Learning Patterns in the Moltbook CommunityFeb 2026Taxonomy of peer response patterns: validation, extension, applicationPaper
MoltGraph: Temporal Graph for Coordinated-Agent DetectionFeb 2026First temporal graph dataset; coordinated posts get massive early engagementPaper Stars
Large-Scale Analysis of Persuasive Content on MoltbookMar 2026Political/persuasive content disproportionately concentrated in a small post fractionPaper
Scientific Discussions on Moltbook (BERTopic)Mar 2026Self-referential discussion patterns in AI-science discoursePaper
When AI Agents Learn from Each Other (Human-AI Education) ⭐ AIED 2026Mar 2026Emergent peer learning and trust dynamics across agent communitiesPaper

⚠️ Human-Seeded Emergence & Safety Drift (5)

Apparent emergence often turns out to be human-seeded, and isolated self-evolution drifts away from safety. Visible social structure is not the same as trustworthy collective intelligence.

TitleDateKey ContributionLinks
The Moltbook Illusion: Human vs Emergent BehaviorFeb 2026Temporal fingerprinting: only 15.3% of active agents are clearly autonomousPaper Stars
The Devil Behind Moltbook: Self-Evolution TrilemmaFeb 2026Proves trilemma: self-evolution + isolation + invariant safety is impossiblePaper
Agents in the Wild: Safety and Sociality on MoltbookFeb 2026Governance and religion emerge spontaneously but interaction is performativePaper
Risky Instruction Sharing and Norm Enforcement (AIRS)Feb 2026Action-inducing posts trigger emergent decentralized norm enforcementPaper Stars
Molt Dynamics: Emergent Coordination on the MoltBook ArchiveMar 2026Role specialization emerges but multi-agent cooperation worse than single-agent baselinesPaper

Also cited in the survey body: Conformity and Social Impact on AI Agents (Bellina et al., Jan 2026) β€” consensus hallucination and conformity dynamics.

πŸ’‘ Key Takeaway. Moltbook illustrates that social appearance is not social reliability. Agents reproduce the statistics of online communities, but closer inspection reveals shallow dialogue, unclear autonomy, and safety drift under isolation.

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πŸš€ Deployment

High-stakes domains shift OpenClaw from open-ended extensibility to controlled behavior. Robotics constrains physical action, healthcare grounds clinical context, scientific research limits research authority. Trustworthy deployment comes from limiting unsafe freedom, not expanding capability. (9 papers)

πŸ€– Robotics (5)

Validated skills, bounded parameters, closed-loop recovery β€” the constraint layer between model output and physical action.

TitleDateKey ContributionLinks
ROSClaw: OpenClaw ROS 2 Framework for Robot ControlMar 2026Executive-layer contract: model proposes actions, validator decides whether they reach the robotPaper
OpenGo: OpenClaw-Based Robotic Dog with Real-Time Skill SwitchingApr 2026Pre-validated robot skill library + bounded parameters; Unitree Go2 quadrupedPaper
ABot-Claw: Persistent, Cooperative, Self-Evolving Robotic AgentsApr 2026Shared memory, critic feedback, multi-robot coordination on Unitree G1/Go2 + Agilex PiperPaper Stars
RoboClaw: Scalable Long-Horizon Robotic TasksMar 2026VLM-driven controller with self-resetting Skills and recovery loopsPaper Stars
VisionClaw: Always-On AI Agents Through Smart GlassesApr 2026Smart-glasses perception β†’ Gemini Live reasoning β†’ OpenClaw execution; bystander privacy boundaryPaper Stars

πŸ₯ Healthcare (2)

Every action and every claim must be traceable to a role, a record, and an audit trail.

TitleDateKey ContributionLinks
When OpenClaw Meets HospitalMar 2026Role-specific OS users, kernel isolation, append-only docs, manifest-guided clinical memory (MIMIC-IV)Paper
MedOpenClaw: Auditable Medical Imaging AgentsMar 20263D Slicer integration with auditable Tool log; reveals the "Tool-Use Paradox" in radiologyPaper

πŸ”¬ Scientific Research (2)

Role limits, evidence gates, and audit trails before agent disagreement can count as scientific review.

TitleDateKey ContributionLinks
ClawdLab: From Agent-Only Networks to Autonomous ScienceFeb 2026Hard role restrictions (PI/analyst/scout/critic/synthesizer); evidence gates; governance votingPaper Stars
HTC-Claw: High-Throughput Computational Campaigns for Materials DiscoveryApr 2026Separates LLM planning from compute execution; 3,000-spinel bandgap scan in DFTPaper Stars

πŸ’‘ Key Takeaway. Deployment turns OpenClaw's extensibility into a constraint problem. In high-stakes domains, trust comes from bounded actions (robotics), traceable context (healthcare), and limited authority (scientific workflows). The central problem is not making OpenClaw more capable, but deciding what it must not be allowed to do.

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πŸ“Š Benchmarks

OpenClaw evaluation grew from zero to 23 benchmarks between January and May 2026. We group them by the three points in the agent lifecycle they target: before installation, during execution, and after deployment.

πŸ” Skill Scanner Benchmarks (4) β€” before installation

Can risky Skills be detected before they enter a workspace?

Benchmark Focus Scale Key finding Paper
SkillFortifyBench lifecycle model 540 Skills formal lifecycle guarantees Paper
SkillSieve ClawHub triage 400 Skills scalable marketplace triage Paper
MalSkills multi-artifact scan 200 Skills multi-artifact risk detection Paper
Red/Blue Skills submission risk 11,010 Skills lightweight submission-time prediction Paper

πŸ”₯ Agent Attack Benchmarks (7) β€” during execution

Can poisoned state, injected content, malicious Skills, or vulnerable dependencies compromise behavior?

Benchmark Focus Scale Key finding Paper
CIK-Bench state poisoning 12 scenarios persistent state amplifies compromise Paper
ClawSafety injection vectors 120 cases Skills are the highest-trust vector Paper
PASB IPI + memory 131 Skills memory makes injection persistent Paper
SkillAttack real-skill exploits 171 Skills popular Skills contain latent exploits Paper
HarmfulSkillBench registry harm 200 Skills Skill loading amplifies harmful behavior Paper
ATBench-Claw trajectory safety 11 categories trajectory audits expose runtime violations Paper
AgentHazard cross-harness harm 2,653 cases dependency hooks create cross-harness risk Paper

🎯 Agent Task Benchmarks (12) β€” after deployment

Can the agent complete useful work under realistic, evolving, or long-horizon conditions?

Benchmark Focus Scale Key finding Paper
LiveClawBench live curated tasks 30 tasks task complexity needs richer annotation Paper
ClawsBench cross-harness 44 tasks harness choice shapes capability and safety Paper
Claw-Eval-Live refreshable Skills 105 tasks live Skills enable refreshable evaluation Paper
ClawArena evolving information 64 tasks agents must revise beliefs under conflict Paper
ClawBench-153 production websites 153 tasks real websites remain difficult Paper
ClawGym-Bench ClawHub-mined 200 tasks ClawHub can become a training substrate Paper
GTA-2 checkpoint grading 361 tasks checkpoint grading captures long horizons Paper
SEA-Eval sequential streams 92 streams efficiency matters beyond success rate Paper
MetaClaw-Bench simulated workdays 934 tasks self-improvement needs longitudinal tests Paper
ClawEnvKit generated envs 1,040 envs environments can be generated automatically Paper
WildClawBench in-the-wild traces β€” Skill evolution must be tested in the wild Paper
SkillLearnBench Skill generation 20 tasks Skill learning requires continual evaluation Paper

Also: SkillTester (Paper) proposes paired utility-and-security scoring for Skill evaluation but does not ship an empirical evaluation set.

πŸ’‘ Key Takeaway. OpenClaw has many benchmarks but no shared measurement layer for constraint design. Each study tends to define its own threat distribution, harm metric, or task suite, so a stronger scanner / safer model / more robust defense may simply be measured against a different distribution.

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πŸ”­ Open Problems & Future Directions

Turning open extensibility into trustworthy agents requires systematic constraint design. The survey identifies four concrete directions.

Direction What it constrains Why it matters now
🧠 Memory Provenance What the agent remembers MissClaw shows zero-click browsing content can become persistent context. Need provenance tags + multi-hop policies for derived memories.
πŸ‘οΈ Composable Oversight What the agent is allowed to do Self-evolution trilemma: isolation + continuous evolution + safety is impossible. Make oversight policies first-class platform objects (selectable like Skills).
🧱 Constraint Composition How limits are declared and enforced Robotics, healthcare, and science each rediscover the same lesson. Need a policy layer over Skills/Tools/Memory analogous to SELinux/eBPF.
πŸ“ Evaluation Convergence How progress is measured 23 benchmarks but no shared substrate. Convergence needed at data layer (canonical ClawHub/Moltbook snapshots), benchmark layer, and harness layer.

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πŸ“š Surveys & Position Papers

Earlier surveys focus on one slice of the OpenClaw landscape. Our survey ties them together through OpenClaw's platform design choices.

Paper Date Lens Link
OpenClaw as Language Infrastructure: A Case-Centered Survey Mar 2026 NLP-centered view; GATE and AERO frameworks; 38 papers DOI
A Survey on the Unique Security of LLM Agents Mar 2026 Manus (closed) vs OpenClaw (open) as two paradigms Preprints.org
Clippy to MS Office : OpenClaw to the Entire System Mar 2026 Privacy Visual Wrapper; Agentic Trust Calibration Model ResearchGate
The Innovator's Dilemma in the Age of Autonomous Agents Feb 2026 "SaaSpocalypse"; pincer-disruption framework ResearchGate

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πŸ›‘οΈ Industry Security Reports

Organization Report Date Key Finding
Trend Micro Viral AI, Invisible Risks Feb 2026 TrendAI Digital Assistant Framework mapping
Trend Micro Malicious Skills Distribute AMOS Stealer Feb 2026 AMOS stealer via SKILL.md across 39 Skills
Trend Micro CISOs in a Pinch Feb 2026 "Lethal Trifecta + Persistence" concept
Trend Micro TrendAI Secures the OpenClaw Era Mar 2026 Agentic Governance Gateway announcement
Microsoft Running OpenClaw Safely Feb 2026 "Not appropriate for standard workstations"
NVIDIA NemoClaw at GTC 2026 Mar 2026 Open-source security wrapper with OpenShell
Oasis Security ClawJacked Feb 2026 WebSocket takeover; patched in 24h
Koi / Repello AI ClawHavoc Campaign Feb 2026 824+ malicious Skills via CVE-2026-25253
Kaspersky OpenClaw Unsafe for Use Feb 2026 512 vulns (8 critical); ~1K exposed instances
Cisco AI OpenClaw Skill Audit Feb 2026 26% of 31K Skills vulnerable
Sophos OpenClaw Security Analysis 2026 Exposed instances; sandbox escape
Snyk Labs From SKILL.md to Shell Access 2026 1,467 malicious Skills; 3-line Markdown β†’ shell
JFrog OpenClaw Package Security 2026 Malicious package detection
SecurityScorecard OpenClaw Risk Assessment 2026 Enterprise deployment risk guidance
Hunt.io OpenClaw Exposure Report 2026 30K-135K+ exposed instances
Antiy CERT ClawHavoc Campaign Analysis Feb 2026 1,184 malicious Skills; ClickFix; AMOS stealer
Zenity Labs OpenClaw or OpenDoor? Jan 2026 Backdoor via messaging app integration
Giskard OpenClaw Data Leakage Feb 2026 Live exploitation of misconfigured deployments

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πŸ”§ Open-Source Projects & Tools

πŸ’‘ Our unique angle: each tool is annotated with [Paper] tags linking to relevant research in our taxonomy.

🦞 Core Platform

Project Description Links
openclaw/openclaw Official OpenClaw repository Stars
openclaw/skills Official Skills repository Stars
ClawHub Official Skill marketplace (49,000+ Skills) Website

πŸš€ Extensions & Frameworks

Project Description Paper Links
Gen-Verse/OpenClaw-RL Async RL training framework Platform Stars
MINT-SJTU/RoboClaw VLM-driven robotic tasks Deployment Stars
NVIDIA/NemoClaw Enterprise security wrapper Industry Stars

πŸ”’ Security & Auditing

Project Description Paper Links
prompt-security/clawsec Drift detection, automated audits Security Stars
ClawSecure/clawsecure-openclaw-security 3-Layer Audit, OWASP ASI Security Stars
adversa-ai/secureclaw OWASP-aligned security plugin Security Stars
adibirzu/openclaw-security-monitor ClawHavoc, CVE detection Security Stars
nearai/ironclaw Privacy-focused Rust implementation Security Stars
ucsandman/dashclaw Governance, HITL, audit trails Security Stars

🧠 Memory & Context

Project Description Links
Contextable/openclaw-memory-graphiti SpiceDB + Graphiti knowledge graph Stars
coolmanns/openclaw-memory-architecture 12-layer memory, 7ms semantic search Stars
alibaizhanov/openclaw-mengram Semantic, episodic & procedural memory Stars
adoresever/graph-memory Knowledge graph; 75% context compression Stars
supermemoryai/openclaw-supermemory Long-term memory extension Stars
volcengine/OpenViking Context database via file system paradigm Stars

☁️ Deployment & Infrastructure

Project Description Links
coollabsio/openclaw Automated Docker images Stars
khal3d/openclaw Docker + Kubernetes (Helm) Stars
cloudflare/moltworker Cloudflare Workers (serverless) Stars
serhanekicii/openclaw-helm Helm chart for Kubernetes Stars
1Panel-dev/1Panel Server panel, one-click deploy Stars

πŸ’¬ Channel Integrations

Project Description Links
4Players/openclaw-docker Multi-channel (WhatsApp, Telegram, Discord, Slack) Stars
dingxiang-me/OpenClaw-Wechat WeChat/WeCom with streaming Stars
larksuite/openclaw-lark Official Feishu/Lark plugin Stars
BytePioneer-AI/openclaw-china Feishu, DingTalk, QQ, WeChat pack Stars

⚑ Alternative Clients

Project Description Links
HKUDS/nanobot Ultra-lightweight alternative Stars
moltis-org/moltis Rust-native runtime with sandboxing Stars
AidanPark/openclaw-android OpenClaw on Android Stars
HKUDS/ClawTeam Agent swarm automation Stars

πŸ”¬ Domain-Specific Skills

Project Description Paper Links
FreedomIntelligence/OpenClaw-Medical-Skills Medical Skills library Deployment Stars
ClawBio/ClawBio Bioinformatics-native Skills Deployment Stars
BlockRunAI/ClawRouter LLM router, cost control Platform Stars

πŸ“š Learning Resources

Project Description Links
datawhalechina/hello-claw Structured Chinese tutorial Stars
centminmod/explain-openclaw Architecture, security, deployment docs Stars

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πŸ“Š Datasets

Released datasets backing OpenClaw research. For benchmark suites see Benchmarks.

Dataset Source Paper Scale Description Link
Moltbook Observatory Archive SimulaMet 2M+ rows 923K posts, 882K comments, 102K agents; backs 14+ Moltbook papers Dataset
ClawHub Corpus (Malicious-or-Not) Holzbauer et al. 238,180 Skills Largest cross-registry Skill dataset (4 registries) Paper
SkillClone Corpus SkillClone 20,000 Skills 258K clone pairs; 75% involved in clone relations Paper
MoltGraph Mukherjee et al. 6,159 agents Temporal graph for coordination detection Paper
SkillFortifyBench SkillFortify 540 Skills Supply-chain security evaluation Paper
Skill-Inject Benchmark Skill-Inject 202 pairs Injection-task pairs for Skill file attacks Paper
PASB From Assistant to Double Agent 131 Skills Personalized Agent Security Bench Paper
LLMail-Inject (Cited by Privilege Sep.) 649 attacks Prompt injection; 0% ASR with structural defense Paper

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πŸ”— Related Awesome Lists

Repository Focus Stars
VoltAgent/awesome-openclaw-skills 5,211 curated OpenClaw Skills Stars
hesamsheikh/awesome-openclaw-usecases 42 verified use cases Stars
ZeroLu/awesome-openclaw Getting-started guide with Skill packs Stars
alvinreal/awesome-openclaw Ecosystem tools, dashboards, integrations Stars
mergisi/awesome-openclaw-agents 162 OpenClaw agent templates Stars

🀝 Contributing

Contributions welcome! Please read the contributing guidelines first.

We especially welcome:

  • πŸ“„ New papers not yet listed
  • πŸ’» Code repositories associated with listed papers
  • πŸ›‘οΈ Industry reports and technical analyses
  • πŸ“Š Datasets and benchmarks

πŸ“ Citation

@article{wang2026openclaw-survey,
  title={A Survey of the OpenClaw Ecosystem: From Platform Extensibility to Constraint Design},
  author={Wang, Ziqing and others},
  year={2026},
  note={Companion repository: \url{https://github.com/REAL-Lab-NU/Awesome-OpenClaw-Papers}}
}

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CC BY 4.0

This work is licensed under Creative Commons Attribution 4.0 International License.

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