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sectum-ai

PyPI·Infrastructure

Sectum AI is an open-source platform designed to verify and provide evidence of tenant isolation in multi-tenant AI systems. It addresses the challenge of ensuring that data from one customer (tenant) cannot be accessed by another within environments such as vector databases, retrieval-augmented generation (RAG) pipelines, agent frameworks, semantic caches, fine-tuned models, and managed compute providers. The platform generates tamper-evident attestations, including a PDF and a machine-readable evidence pack, which can be independently verified by auditors, security teams, and data protection officers without requiring trust in Sectum AI itself.

The tool operates by seeding synthetic tenants with cryptographic canary markers and a hashed ground-truth manifest, enabling deterministic and reproducible verification with zero false positives. Sectum AI tests across thirteen surfaces, including vector databases, RAG pipelines, semantic and key-value caches, agent memory, tool calls, fine-tunes or adapters, evaluation sets, backups, search indexes, tracing pipelines, prompt/completion logs, and APIs. It supports live adapters for common backend systems. The platform is equipped to detect eleven classes of cross-tenant attacks, such as direct tenant-boundary fetches, organic entity-bleed in RAG, semantic-cache contamination, timing side channels in key-value caches, embedding inversion, confused-deputy bugs, persistent memory contamination, LoRA cross-tenant influence, benign extraction, RAG poisoning, and GDPR Article 17 erasure verification.

Sectum AI outputs are canonicalized, hashed, RFC 3161 timestamped, logged with Sigstore Rekor, and wrapped in an in-toto attestation envelope. The resulting evidence can be rendered as an auditor-ready PDF, and the verification process can be independently run using the sectum-ai verify tool, which does not require a Sectum AI installation. The platform is particularly suited for roles such as CISOs, sales engineers, compliance teams, platform engineers, application security professionals, legal teams, and DPOs, supporting use cases like vendor security questionnaires, SOC 2 audit evidence, pre-launch verification, CI regression baselines, GDPR erasure response, and compliance with the EU AI Act.

0 license, with its marker substrate, attack catalog, adapters, evidence chain, and verification tool available as open source. The platform is designed to be integrated into audit and compliance workflows, enabling partners such as audit firms to white-label its evidence packs for standards like SOC 2, ISO 27001, and GDPR. Sectum AI distinguishes itself by enabling real tenant provisioning to measure cross-tenant leakage and by producing independently verifiable evidence, addressing a gap not filled by LLM red-team frameworks, runtime guardrails, governance platforms, or data security tools.

Open SourceApache-2.0
WebCLISelf-hosted
S
sectum-ai preview
Visit PyPI↗
⭐2
stars
✓5
features
📅2026
since

Overview

5 features

sectum-ai sits in PulseGate's LLM eval & observability category. It focuses on verifying and evaluating multi-tenant AI and RAG systems efficiently via CLI. It is built as an open-source project for AI engineers. sectum-ai is open source under the Apache-2.0 license. It runs on the web and the command line, and it can be self-hosted.

It is developed by sectum-ai, and the product first shipped in 2026. Development happens publicly on GitHub with 301 commits in the last 90 days. Key capabilities include AI verification, multi-tenant support, and CLI interface.

  • ✓AI verification
  • ✓Multi-tenant support
  • ✓CLI interface
  • ✓RAG evaluation
  • ✓Substrate runner

Tags

ai-verificationrag-evaluationcli-toolmulti-tenant-ai

AI capabilities

TextWeights: Open

Built with & integrations

Framework
astro
Hosting
aws
Runs on
BrowserCLISelf-hosted

Trust & compliance

LicenseApache-2.0
Verified signals
✓ HTTPS✓ Open Source✓ Free tier✓ GitHub · ★ 2✓ Active maintenance

Recent events

Latest indexed changes and source events

  1. IndexedJun 30, 11:26 PM

    sectum-ai verified by the PulseGate indexer

    Source: PulseGate indexerOpen ↗

Frequently asked questions about sectum-ai

What does sectum-ai do?
Sectum-ai focuses on verifying and evaluating multi-tenant AI and RAG systems efficiently via CLI. It is catalogued under LLM eval & observability on PulseGate.
Who is sectum-ai for?
sectum-ai is an open-source project built for AI engineers.
Is sectum-ai free?
Yes — sectum-ai is open source under the Apache-2.0 license and free to use.
What platforms does sectum-ai run on?
sectum-ai runs on the web and the command line. It can also be self-hosted.
Is sectum-ai still maintained?
PulseGate's automated liveness checks currently classify sectum-ai as active. The GitHub repository shows 301 commits in the last 90 days.
What are alternatives to sectum-ai?
Similar tools tracked by PulseGate include secably, specora-verify, and Sector8.secablyspecora-verifySector8
Who makes sectum-ai?
sectum-ai is developed by sectum-ai.
When did sectum-ai launch?
sectum-ai first shipped in 2026.

At a glance

Platforms
Cli · Web
Languages
English
Open source
Yes · ★ 2
License
Apache-2.0
First seen
Jun 6, 2026
Activity
🟢 Active
Status
🟢 Active
Built for
AI engineers
Model
Open source
Solves
Verifying and evaluating multi-tenant AI and RAG systems efficiently via CLI.

Developer

sectum-ai
Small team
↗ GitHub

Open source

View on GitHub →
⭐ Stars
2
🍴 Forks
0
Open issues
5
Last commit
2w ago
Commits 90d
301
Contributors
2
Authorship
Small team
Default branch
main
Latest release
v0.1.5 · 3w ago

Live coverage

Confidence
Low · 64
Indexed
Jun 30, 2026
Lifecycle
Alive
Activity
Active
First seen
Jun 2026
Last seen
2w ago
Identity audit (9)
Entity ID
cmr1a1d1m0f0ho3vycq7eo0ql
Slug
sectum-ai-pypi-org
Verification state
Indexed for public listing
Claim / listing state
Unclaimed · listed: yes
Index status
Included in index
Latest evidence snapshot
Jun 30, 2026
Timeline basis
Indexed-at chronology (no inferred launch/funding milestones).
Last updated
Jul 13, 2026
Canonical URL
https://sectum.ai

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