Canonical: https://dokima.net/insights/dokima-alongside-semgrep-codeql-snyk/ Updated: 2026-11-04T23:30:51+00:00 [← All insights](https://dokima.net/insights/) Security Tooling # Where Dokima fits alongside Semgrep, CodeQL and Snyk Combine Dokima with Semgrep, CodeQL and Snyk: keep automated checks, investigate application behaviour and carry findings through to verified fixes. Security Tooling4 November 20266 minute read ## Key takeaways * Keep useful source, dependency and secret checks in your development pipeline. * Modern static analysis can follow data across functions and files; compare the actual products and configuration. * Use Dokima for ongoing investigation with retained codebase context, challenged findings and a team review history. If you already use Semgrep, CodeQL or Snyk, keep the checks that help your team ship safely. Dokima adds an ongoing investigation workflow: it builds and retains an architectural model of your codebase, investigates weaknesses, challenges candidate findings and gives the team evidence and practical fix recommendations. The useful buying question is which review jobs you need covered, how the tools will share your team’s attention, and what happens after a finding appears. ## Start with the job you need done A security workflow usually has several jobs: catch known unsafe code patterns, track vulnerable dependencies, detect exposed credentials, investigate application-specific permission rules, and verify repairs. Those jobs overlap, but they do not all have the same inputs or release timing. **Static application security testing**, or SAST, examines source code without needing to exercise the running application. It includes more than text matching: modern tools can model control flow and follow untrusted data through functions and files. Dependency analysis separately checks the third-party packages an application uses. Dokima also examines source. Its focus is sustained investigation grounded in the application’s architecture and security assumptions, with skeptical peer review and validation before a candidate becomes a reported finding. It continues reviewing both changes and existing code as the repository evolves. ## What Semgrep, CodeQL and Snyk cover ### Semgrep [Semgrep Code](https://docs.semgrep.dev/semgrep-code/overview) provides rule-based source analysis, including cross-function and cross-file capabilities. The Community Edition and commercial product have different analysis capabilities. Semgrep also offers supply-chain and secrets products, plus AI-assisted investigation and remediation features. A practical use is to enforce repeatable checks during development and in CI, including rules specific to your own frameworks. Review the engine, language support and enabled rules when assessing coverage. ### CodeQL [GitHub’s CodeQL](https://docs.github.com/en/code-security/concepts/code-scanning/codeql/codeql-code-scanning) models code as a queryable database and uses queries to identify potential vulnerabilities. It supports analysis of data flow and can be extended to model custom frameworks. Results can appear as GitHub code-scanning alerts. It can provide a consistent automated check on supported repositories. Setup, queries, framework models and build configuration influence what it sees. It would be inaccurate to describe CodeQL as a scanner limited to isolated lines or simple string patterns. ### Snyk [Snyk Code](https://docs.snyk.io/scan-fix-and-prevent/scan-with-snyk/snyk-code) provides source analysis, including data-flow analysis and remediation guidance. [Snyk Open Source](https://docs.snyk.io/scan-with-snyk/snyk-open-source) addresses third-party dependency risk. Other Snyk products cover additional parts of the application and infrastructure. Distinguish the particular product when comparing results. A dependency scan and a source-code investigation answer different questions, even when both sit under the same vendor name. ### Dokima [Dokima](https://dokima.net/product/) maps control and data flows, attack surfaces and component interactions, then uses that retained context to investigate security weaknesses. It challenges candidate findings through skeptical review and validation, reporting evidence, impact, preconditions and practical remediation. Teams can discuss findings, add context and record decisions. Dokima runs with your chosen Claude, Codex or OpenCode setup, including private local models through OpenCode. That gives a team control over its review environment and model choice while keeping an ongoing investigation history. ## A worked example: an invoice export Consider an application where customers belong to organisations and may export only their own invoices. A new export route accepts an invoice ID. A shared database helper loads the invoice, and a background worker writes the downloadable file. This is an **illustrative review scenario**, not a comparison benchmark or a claim that a named tool missed a defect. Several different checks are useful here: * Dependency analysis can flag a known vulnerability in the archive library used by the exporter. * Source-analysis queries or rules can flag unsafe file handling or trace untrusted input, depending on their models and configuration. * An architectural investigation can ask where organisation membership is enforced, whether the worker retains the correct owner, and who can fetch the final file. For Dokima, provide the ownership rule in `DOKIMA.md` and include the request handler, helper and worker in the workspace. A useful finding would identify the path where that rule fails, the caller’s required access and the data exposed. Validation should also consider any shared permission check that could invalidate the claim. Any of the tools may find overlapping issues. Assess the evidence rather than assuming a particular issue belongs exclusively to one analysis method. ## Combine the workflows around a single repair Keep fast automated checks in the development pipeline and run Dokima against an up-to-date review workspace. When findings arrive, give each confirmed issue a clear owner and link related reports to the same repair in your issue tracker. That avoids making developers solve the same problem several times. For a cross-customer invoice export, a complete repair includes the permission check, a test that blocks the other customer’s request, and a test that preserves the legitimate export. Rerun the relevant tools and inspect subsequent Dokima evidence. Its own deduplication maintains finding history within Dokima; coordinate reports from other products through your team’s normal workflow. Use [Claude Code or Codex with the Agent API](https://dokima.net/insights/fix-dokima-findings-with-claude-code-or-codex/) to help investigate and implement the patch, then follow the [security-fix checklist](https://dokima.net/insights/what-to-check-after-a-security-fix/) before closing it. ## Choose using your own code and constraints Compare tools on a representative repository: relevant findings, evidence quality, developer time spent investigating, supported languages and frameworks, data handling, and operating cost. Include existing code and cross-component behaviour in the evaluation, alongside recent changes. Inspect a [Dokima sample report](https://dokima.net/sample-report/) and [start a review](https://dokima.net/docs/agent-setup/) to see how its investigation workflow fits your current checks. Dokima is free for small teams, including private repositories. The strongest combination is the one your team can keep running, understand and carry through to verified fixes. Next step ## Evaluate this workflow on your own codebase. Dokima runs locally on Linux and macOS using Claude, Codex or OpenCode, with staged architecture mapping, adversarial challenge, deterministic deduplication and developer-ready HTML reports. The 21-day free trial starts on first activation and requires no payment card. [Start 21-day free trial](https://dokima.net/account/?view=register)[View sample report](https://dokima.net/sample-report/)[Browse all insights →](https://dokima.net/insights/) Try Dokima on your repositories ## Give your engineering team a repeatable AI source-review workflow. Start a full-product 21-day trial with no payment card required, or inspect the complete sample report. [Start free trial](https://dokima.net/account/?view=register)[Buy Dokima](https://dokima.net/buy/)[View sample report →](https://dokima.net/sample-report/)