docs: rebrand Certifai → Prüfwerk (user-facing name) (#243)
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This commit was merged in pull request #243.
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2026-09-02 08:00:12 +00:00
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# Tools & Scanners
Certifai uses a combination of open-source scanners and AI-powered analysis to provide comprehensive security coverage. This page describes each tool and how it contributes to the scan pipeline.
Prüfwerk uses a combination of open-source scanners and AI-powered analysis to provide comprehensive security coverage. This page describes each tool and how it contributes to the scan pipeline.
## Semgrep -- Static Analysis (SAST)
[Semgrep](https://semgrep.dev/) is an open-source static analysis tool that finds vulnerabilities by matching patterns in source code. It supports many languages and has an extensive rule library.
Certifai runs Semgrep with rules covering:
Prüfwerk runs Semgrep with rules covering:
- **OWASP Top 10** -- injection, broken authentication, XSS, insecure deserialization, and more
- **General security** -- insecure cryptography, hardcoded credentials, path traversal
@@ -26,7 +26,7 @@ Syft output feeds into both the SBOM feature and the vulnerability scanning pipe
## OSV.dev + NVD -- Vulnerability Matching
Certifai matches every SBOM component directly against two public vulnerability sources (no separate scanner binary):
Prüfwerk matches every SBOM component directly against two public vulnerability sources (no separate scanner binary):
- [OSV.dev](https://osv.dev/) -- batch queried by package URL (purl) for ecosystem advisories (npm, PyPI, crates.io, Go, Maven, ...)
- [NVD](https://nvd.nist.gov/) -- queried per CVE for the CVSS v3.1 base score, and by CPE for CODESYS runtime versions found in PLC projects
@@ -63,7 +63,7 @@ Detects hardcoded secrets and credentials in source code:
## LLM-Powered Code Review
Beyond rule-based scanning, Certifai uses an LLM to perform architectural and security code review. The AI reviews code patterns that are too nuanced for static rules, such as:
Beyond rule-based scanning, Prüfwerk uses an LLM to perform architectural and security code review. The AI reviews code patterns that are too nuanced for static rules, such as:
- Business logic flaws
- Race conditions