When evaluating third-party vendors for a migration, what technical standard should be prioritized to safeguard data and establish a foundation of trust?
Hi @Utkarsh Chandel ,
Great question!
Vendor due diligence is one of the most underrated parts of any DC-to-Cloud migration.If you want a single signal to prioritize, look at how the app handles your data at the platform level. That's where Atlassian's trust framework gives you the clearest answer:
Plenty of useful apps simply can't be "Runs on Atlassian" because of what they do. External integrations, AI features calling third-party models, etc. That's not a red flag by itself. In that case:
In general every Marketplace app goes through Atlassian's approval process before listing, but that's a quality and policy review not a deep security audit.
The best security signals are Runs on Atlassian, Cloud Fortified, Bug Bounty participation, and vendor attestations like SOC 2 or ISO 27001.Hope this helps! If it did, please mark it as the accepted answer so others with the same question can find it more easily.
Great breakdown, @Kevin Kadakas — fully agree that "Runs on Atlassian" is the strongest single trust signal, and the distinction from Cloud Fortified is one many teams get wrong.
@Utkarsh Chandel From an enterprise security / vendor due diligence perspective, I'd add a few more technical standards worth prioritizing alongside the Atlassian badges, especially for a DC-to-Cloud migration where you're often onboarding many third-party apps at once:
1. Data residency & encryptionConfirm where data is stored and processed (region pinning matters for regulated industries) and that encryption is enforced both in transit (TLS 1.2+) and at rest (AES-256).
2. Authentication & access controlsLook for SAML/SSO, SCIM provisioning, enforced MFA, and least-privilege OAuth scopes. For Forge/Connect apps, review the declared scopes in the manifest — over-scoped apps are a common, under-discussed risk.
3. Egress & data flow transparencyEven "Runs on Atlassian" apps can call external endpoints via Forge's declared external fetch permissions. Always review the Marketplace Security & Trust tab and the app manifest before assuming zero external data flow.
external fetch
4. Sub-processor disclosureVendors should publish a current sub-processor list — increasingly relevant when AI/LLM providers sit in the data path. This is also a GDPR Art. 28 requirement.
5. Attestations beyond SOC 2 / ISO 27001Depending on your industry: ISO 27017 (cloud), ISO 27018 (PII in cloud), HIPAA BAA availability, PCI DSS, FedRAMP, CSA STAR.
6. Vulnerability management & SDLC maturityBug Bounty is a good signal, but also ask about SAST/DAST in CI, dependency scanning, patch SLAs, and pen-test cadence (vendors should share a recent summary under NDA).
7. Incident response & breach notification SLAsContractual commitments around notification timelines (e.g., 72 hours) and a documented IR plan matter as much as technical controls.
8. Business continuityRTO/RPO commitments and DR test evidence, especially for apps in the critical path of your migration.
A practical shortlist: Runs on Atlassian → Cloud Fortified → SOC 2 Type II + ISO 27001 + clear sub-processor list + transparent egress declarations. That combination gives you both platform-enforced controls and vendor-level accountability.
💡 Scaling vendor evaluations with AI
If you're evaluating many vendors as part of a migration, manually researching 60+ security controls per tool can take 4–8 hours each. This is exactly the kind of repetitive, high-cognitive-load work that AI agents are great at accelerating.
I've been experimenting with a Rovo Agent — AI tool SecRev Agent built on Atlassian's Rovo platform. You give it a tool name and a few URLs (vendor trust center, pricing tiers, documentation), and it:
Researches the tool against minimum security requirements (SSO, MFA, encryption, audit logging)
Analyzes AI-specific data handling policies (does the vendor train on your data? does that vary by tier?)
Checks compliance posture (SOC 2, ISO 27001, GDPR, etc.)
Highlights risky features to avoid even on secure plans
Produces a structured, citable comparison report ready for review
It doesn't replace human judgment on the final approval, but it cuts review time by ~85% and ensures consistency across vendors — which is exactly what you need when migration timelines are tight and the vendor pipeline is long. Pairing this kind of agent with the trust signals above (Runs on Atlassian, Cloud Fortified, attestations) gives you both speed and rigor.
Hope this helps!
Hi @Utkarsh Chandel
When evaluating third-party vendors for a migration, organizations should prioritize strong security standards, data governance, and the principle of least privilege. The tool should clearly define what data it can access, how that data is processed, and what level of control it has over your environment. It important to identify and remove Personally Identifiable Information (PII) and other sensitive data that may exist in pages, issues, comments, attachments, or historical content. This helps reduce the risk of unnecessary data exposure in the cloud.
DLP Sensitive Data Scanner for Jira, & Confluence is designed with this security-first approach. It enables organizations to scan for sensitive data, identify PII using configurable regex patterns, and take remediation actions such as Encryption, Redaction, or Removal. The solution also helps detect dormant users, review permissions, and audit data remediation activities, giving administrators complete visibility and control.
By following a Zero Trust approach, migrating only the required and sanitized data, organizations can significantly reduce the risk of data leakage while maintaining compliance and building confidence in their migration strategy
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