Semantic Kernel
Website
Integrate cutting-edge LLM technology quickly and easily into your apps
Is Semantic Kernel safe? Promising trust profile, but some evidence still deserves review.
Compare Semantic Kernel
How does it stack up against its Agent Frameworks neighbours?
Pick any agent to compare →In detail: Semantic Kernel scores 65.7/100 (Grade B), ranked #459 of 1371 tracked open-source AI agent projects, on evidence coverage A (4 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 5.6/10; 100% of recent commits are signed; no published advisory affects its latest release (semantic-kernel); last pushed 2026-10-07. Every point is earned from checkable signals — never paid placement. How scoring works →
How Semantic Kernel could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Publish build provenance for its packagesPyPI Trusted Publishing attestations +14.7 → 80.4 A · #14 of 129
- Raise the OSSF Scorecard from 5.6 to 9.0lowest checks: Dangerous-Workflow 0, Fuzzing 0, Signed-Releases 0 +7.0 → 72.7 B · #19 of 129
Chain of custody
Scanners check what the code says. This traces who ships Semantic Kernel and whether that has changed: from the source repository, through how changes are reviewed and released, to the package you install. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities.
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Source Signed
github.com/microsoft/semantic-kernel, MIT, last pushed 2026-10-07. 100% of the last 100 commits carry a verified signature, so changes trace to a verified account.
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Review and release Mixed
OpenSSF Scorecard rates the repository's practices 5.6/10 (scanned Oct 8, 2026). The checks that decide who can get a change released:
- Code Review9
- Branch Protection8
- Signed Releases0
- Dangerous Workflow0
- Token Permissions0
- Pinned Dependencies8
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 8CI-Tests 10CII-Best-Practices 2Code-Review 9Contributors 10Dangerous-Workflow 0Dependency-Update-Tool 10Fuzzing 0License 10Maintained 10Packaging -1Pinned-Dependencies 8SAST 7Security-Policy 10Signed-Releases 0Token-Permissions 0Vulnerabilities 0 -
Published packages Not linked
- PyPI semantic-kernel Source link isn't a GitHub repo No build attestation
Without a build attestation, nothing proves the published files were built from this repository.
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What you install today No known advisories
Latest release checked: semantic-kernel 1.45.0. No published advisory affects it (OSV, checked 2026-10-09).
Changes to this chain
No change to package provenance, package source links, Scorecard coverage or license in HVTracker's daily snapshots of Semantic Kernel.
Evidence behind this score
Coverage A: 4 of 5 independent evidence types found.
- GitHub repository data
- Package downloads
- Supply-chain checks
- Public actions (missing)
- Community mentions
Verify this score yourself
Every build re-issues Semantic Kernel’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read tool descriptions or prompts for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you connect it, such as Cisco MCP Scanner or Snyk Agent Scan.
How Semantic Kernel compares in Agent Frameworks
- #37 Marvin 66.0 +0.3
- #38 AutoGPT 65.9 +0.2
- #39 Semantic Kernel 65.7 this agent
- #40 Mastra 65.6 −0.1
- #41 TrueForge 65.5 −0.2
Bars show each HVTrust score; the tick marks Semantic Kernel’s 65.7.
Where the 65.7 comes from
HVTrust dimensions vs the Agent Frameworks average
65.7 / 100 · 100.0% confidenceSemantic Kernel Agent Frameworks average (129 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage A is separate — it grades how many independent signal types back the score (4 of 5), so a high score on thin evidence stays visible. Full methodology →
Rank Trend
Activity & Reach
Analysis
Activity Inputs
84.9 / 100Common questions about Semantic Kernel
Does Semantic Kernel publish package provenance?
Does Semantic Kernel have an OpenSSF Scorecard?
Is Semantic Kernel actively maintained?
What license does Semantic Kernel use?
Are Semantic Kernel's commits signed?
Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.
AI agent surface
MCP, providers, tool surface
These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →
- Amazon Bedrock
- Anthropic
- Azure OpenAI
- Google Gemini
- Mistral AI
- OpenAI
- Pinecone
- Postgres
- Qdrant
- Redis
- Weaviate
- database
- MCP signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Maintain Semantic Kernel?
For maintainers
HVTrust scores Semantic Kernel from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/semantic-kernel)
<a href="https://hvtracker.net/agents/semantic-kernel"><img src="https://hvtracker.net/badge/semantic-kernel.svg" alt="HVTrust"></a>
Other agents in Agent Frameworks
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI · Algolia HN Search API
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON