sentinelcore-ai
PulseGate's liveness check found it on 24 Sep 2026; it is registered on PyPI and has been in the index since 24 Sep 2026. How this is checked
SentinelCore AI is an open-source security control plane for LLM and agent applications. It provides detection, provenance tracking, risk assessment, authorization, policy enforcement, and guardrails for AI systems, including MCP-based workflows.
Inferred · not functionally tested
Overview
6 featuresPurpose: Securing LLM and agent applications against prompt injection, provenance risks, unauthorized actions, and policy violations.
Inferred · not functionally tested
Audience: AI developers and security engineers building LLM and agent applications
Inferred · not functionally tested
Functions: monitoring, agents
Inferred · not functionally tested
Interfaces: API: indicated (inferred, not tested) · MCP: indicated (inferred, not tested) · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)
Recorded constraints: pricing: open_source · license: MIT · platforms: CLI · deployment: cli, self_hosted, api_only
Constraint provenance is unknown; confirm requirements with the publisher.
Record sources: pypi.org. These links do not verify the individual claims.
sentinelcore-ai sits in PulseGate's AI & LLM security category. Inferred · not functionally tested: It focuses on securing LLM and agent applications against prompt injection, provenance risks, unauthorized actions, and policy violations. Inferred · not functionally tested: sentinelcore-ai is an open-source project aimed at AI developers and security engineers building LLM and agent applications. Basis unknown · not verified: sentinelcore-ai is open source under the MIT license. Basis unknown · not verified: sentinelcore-ai is available on the command line and API, and it can be self-hosted.
sentinelcore-ai first shipped in 2026. Inferred · not functionally tested: Key capabilities include threat detection, provenance tracking, and risk assessment. Inferred · not functionally tested: Catalogued interfaces include an MCP server.
Summary written by a language model from the project’s public pages.
Tasks: Inferred · not functionally tested
- Threat detection
- Provenance tracking
- Risk assessment
- Authorization controls
- Policy enforcement
- Prompt-injection defense
Topics: Inferred · not functionally tested
Built with & integrations
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
- Indexed23 Sep · 20:17 UTCsentinelcore-ai seen via PyPI Bulk EnumeratorSource: PyPI Bulk Enumerator · Open
Frequently asked questions about sentinelcore-ai
- What does sentinelcore-ai do?
- Inferred · not functionally tested: Sentinelcore-ai focuses on securing LLM and agent applications against prompt injection, provenance risks, unauthorized actions, and policy violations. It is catalogued under AI & LLM security on PulseGate.
- Who is sentinelcore-ai for?
- Inferred · not functionally tested: sentinelcore-ai is an open-source project built for AI developers and security engineers building LLM and agent applications.
- Does sentinelcore-ai have a free plan?
- Basis unknown · not verified: Yes — sentinelcore-ai is open source under the MIT license and free to use.
- What platforms does sentinelcore-ai run on?
- Basis unknown · not verified: sentinelcore-ai runs on the command line and API. It can also be self-hosted.
- Is sentinelcore-ai still active?
- PulseGate's liveness check found it on 24 Sep 2026.
- What projects are similar to sentinelcore-ai?
- Similar projects tracked by PulseGate include sentinel-ai-auditor, Sentinel, and sentinel-code.sentinel-ai-auditorSentinelsentinel-code
- When did sentinelcore-ai launch?
- sentinelcore-ai first shipped in 2026.
- Is sentinelcore-ai open source?
- Basis unknown · not verified: Yes — sentinelcore-ai is open source under the MIT license.
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