Migrating from APIsec to Noname Security

Use this guide to translate detection results when moving from APIsec to noname security. Both tools map findings to PCI-DSS 4.0, SOC 2 Type II, and OWASP API Top 10 (2023). Expect differences in how findings are grouped, named, and prioritized, since each tool uses its own signature set and risk model.

Where APIsec raises a finding, check whether noname security surfaces the same issue with a different identifier. Focus on the underlying weakness, such as missing authentication on an endpoint, rather than the label. This approach keeps remediation work consistent even when tooling changes.

Some APIsec detections may not have a direct equivalent in noname security. In those cases, validate the underlying exposure using noname security’s coverage, and consider compensating evidence such as runtime telemetry or configuration reviews. Mapping is about reducing duplication, not forcing a one-to-one match.

APIsec exports typically include JSON and PDF artifacts. Extract the raw JSON findings file to preserve detection details, evidence snippets, and severity ratings. Store these exports alongside noname security reports so you can compare detection lineage during migration.

Noname security provides structured outputs through its web dashboard, CLI, and API client. Use the CLI to pull machine-readable scan results, and schedule regular exports to retain historical context. Keeping time-ordered archives helps you track which issues were pre-existing and which are introduced after migration.

When rebuilding scan history, replay archived scans against the new environment where possible. Note that scan coverage and authentication context may differ, so treat historical data as directional rather than exact. Maintain a mapping table that links old finding IDs to new ones for audit trails.

If APIsec was integrated into CI pipelines, replicate the same gate logic in noname security. For example, if APIsec failed builds on scores below a threshold, configure noname security to enforce an equivalent policy using its GitHub Action or CI client. Ensure the same environments and URLs are targeted in each run.

Check that authentication setups carry over correctly. APIsec may have used bearer tokens or API keys stored in CI secrets; replicate those in noname security’s authenticated scan configuration. Confirm that domain verification steps, such as DNS TXT records or well-known challenge files, are satisfied before enabling credentialed scans.

Update pipeline definitions to reference noname security’s CLI syntax and output formats. Validate that failure conditions, reporting paths, and notification channels (email, Slack, Teams) behave as expected. Run a small set of non-destructive scans in a staging pipeline before promoting changes to production workflows.

Not all findings from APIsec will be reproducible in noname security. Differences in crawler behavior, authentication flows, and probe depth can cause some issues to appear in one tool and not the other. Treat gaps as a signal to perform additional manual review rather than a deficiency in either platform.

Certain APIsec-specific integrations, such as custom dashboard widgets or proprietary compliance templates, may not have direct counterparts. You can approximate coverage using noname security’s dashboard, scheduled scans, and compliance PDF exports, but the exact layout and metadata might differ. Plan time for stakeholders to adapt to the new view.

Transient findings, such as rate-limit header detection or environment-specific SSRF probes, may vary between runs due to network conditions or endpoint changes. Rely on consistent scanning cadence and compare trends across multiple scans instead of single-point results. Document environmental factors that explain anomalies.

Start with a parallel run where both tools scan the same stable set of APIs under identical authentication contexts. Compare the high-severity overlap first, then expand to medium and low findings. Use this baseline to build a migration checklist and to tune alert thresholds.

Prioritize remediation based on exploitability and data sensitivity rather than raw score shifts. A finding moving from one severity band to another is less important than whether the underlying vulnerability is actually reduced. Focus on fixing the root cause, not reclassifying entries.

Establish a recurring review cadence to reassess mappings as both platforms evolve. Schedule quarterly checks to validate that new scan types, such as LLM security probes or updated OpenAPI checks, are correctly reflected in your workflow. Maintain a living document that records what each tool covers and where manual verification is required.