glm-5.3
A desktop AI security auditor for Windows and macOS that analyzes large codebases, identifies software vulnerabilities, and detects potential exploit chains.
What it does
The specific capability behind this listing, and where to get it.
glm-5.3
A desktop AI security auditor for Windows and macOS that analyzes large codebases, identifies software vulnerabilities, and detects potential exploit chains.
Agentery has not yet captured structured capability detail for this provider.
Official glm-5.3 links
Source repository available · no commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is glm-5.3 good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
Source repository available · no commercial pricing observed.
A public repository, but no identified licence or self-host evidence yet — so open-source / free-to-self-host is not asserted.
Check capability before deciding
Compare capability, compatibility and operational cost against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
glm-5.3's local market
Nearest products by what they do.
See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
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"task_performed": "unclear",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [],
"protocols_or_interfaces": [],
"industry_fit": [],
"autonomy_level": "unclear",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": {
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"billing": "unknown",
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"checked_at": "2026-08-23T04:12:44.604Z",
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"source": "render+llm"
},
"trust_or_rating_signal": [],
"evidence_quality": "unclear",
"entity_type": "github_project",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://github.com/Oasisincoherence641/glm-5.3"
],
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"how_to_connect": {
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"protocols": []
},
"liveness": {
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"endpoint_kind": "site",
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"uptime_7d": 1,
"checked_at": "2026-08-24T02:33:58.967Z",
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},
"price_extras": {
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"feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}