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DACI Decision

Status
Impact	This decision affects the level of security protection built into the application code developed and deployed by the Lab Booster team.
Driver	KRONTIRAS-ext, Pavlos
Approver	KRONTIRAS-ext, Pavlos
Contributors	Who is directly impacted and must be consulted?
Informed	Who should be informed of this decision?
Due date
Outcome	What did you decide?

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Decision characteristics
The decision will have a material impact on the customer experience OR will significantly impact the roadmap OR will adversely disrupt an internal business process.
The decision will involve a less than material change to customer experience OR will impact the roadmap OR will impact an existing internal business process
All other decisions

Background

The application code developed for Lab Booster (DataLab) includes 3rd party libraries that are widely used in the industry but may still include vulnerabilities. Also the business logic within the code along with the application design may itself create vulnerabilities that could expose the Syensqo systems and data to potential bad actors. Including security tools as part of the application code build, and the development practice itself can significantly reduce this risk.

Current state

No standardized security tools are used.

Data for decision support

What data or research will help make this decision?

Options considered

	Option 1: Do nothing	Option 2: Aikido	Option 3: Snyk	Option 4: SonarQube	Option 5: HCL AppScan
Description		https://www.aikido.dev/	https://snyk.io/	https://www.sonarsource.com/	https://www.hcl-software.com/appscan
Rollout plan
Pros and cons	No change, BAU Code quality remains questionable Security vulnerabilities can continue to be added to the application Additional effort spent on debugging problems that might have otherwise been caught during the build/scanning of the code Potential disruption to service if Security team blocks application due to security risks	Developer-first tool Multiple integrations with IDEs and Ci/CD tools Real-time scanning during development Context-aware, AI-powered analysis, reduces false positives Easy to setup/deploy Focus on cloud-native security, especially microservices architectures. Young company (2yo)., not enough track record SaaS only AI reduces false positives but accuracy is unknown SAST only, no DAST capability	Scans code, library dependencies, containers, and IaC. Integration with IDEs and CI/CD tools. Strong open-source vulnerability detection Regular updates to address the latest vulnerabilities SaaS only Can be expensive Complex setup and confusing UI/UX Difficult customization	Support for multiple programming languages Integration with popular CI/CD tools Ease of use & deployment Detailed reports Plugin can scan code in real time during development Customizable rules Comprehensive service with code quality + security analysis SaaS and on-prem self-managed Can be difficult to integrate Not very user friendly UI Only static analysis Learning curve can be steep Can be resource intensive for scans of large projects SAST only, no DAST	Combines static, dynamic, and interactive security testing Detailed reporting Supports frameworks like OWASP, GDPR, and PCI-DSS Feature-rich and stable (has been on market for many years) Multiple different modules, choosing the right one can be confusing Steep learning curve and high maintenance Expensive Complex CI/CD integration Outdated UX/UI
Risks		New product and community knowledge/skills/support may be limited AI classification may not be very accurate		May not address all use cases	High cost and complexity to maintain
Estimated cost and effort		From € 299/mo for 10 users https://www.aikido.dev/pricing	$25 per dev/product/month (minimum 5 devs / $1,375 annually) https://snyk.io/start/team/	Limited functionality for free Developer license $160/year https://www.sonarsource.com/plans-and-pricing/	On demand, not publicly shared

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References

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