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Detect SQL injection before merge.

See how SQL injection fits local review, which evidence Code Radar produces, where coverage ends, and how trusted findings move into CI.

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radar scan . --quick

What SQL injection means here.

The SQL injection rule identifies review patterns that can create exploitable behavior or hide material maintenance risk, then returns the affected location, severity, confidence, and remediation context.

Rule reference

Evidence to inspect

Verify the input scope, finding detail, workflow handoff, and product boundary before you install or buy.

CriterionEvidence to inspectBoundary
Input scopeSelected files, configuration, scan mode, and enabled rules.Only included paths and configured checks are evaluated.
Finding detailFile, line, rule ID, severity, explanation, and repair direction.Illustrative output is not a result from your repository.
Workflow handoffLocal result, report format, agent context, and optional CI signal.Enable exports or CI only when the workflow needs them.
Decision fitUse the same criteria on a real repository before choosing a plan or tool.No universal winner or guaranteed outcome is claimed.
Rule reference

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Verify the input scope, finding detail, workflow handoff, and product boundary before you install or buy.

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The problem this page helps clarify

The useful question is where SQL injection changes the review loop: what enters the scan, who acts on a finding, and which evidence moves forward. Detect untrusted input reaching SQL construction instead of a parameterized query.

  • Audience: Developers and reviewers deciding how to handle SQL injection findings before merge.
  • Focus: Detect untrusted input reaching SQL construction instead of a parameterized query.
  • Review question: What does SQL injection cover in practice?

Coverage and concrete signals

For SQL injection, inspect the concrete scope below instead of relying on a category label. Follow input into query construction, record the query location, and verify that the safer example binds parameters instead of interpolating text.

  • Focus: Detect untrusted input reaching SQL construction instead of a parameterized query.
  • Workflow: Rule ID: RADAR-SEC-SQLI
  • Coverage and concrete signals: RADAR-SEC-SQLI, unsafe pattern, safer pattern, Source security
FocusExact file location, rule context, severity, confidence, and remediation guidance.Boundary
Detect untrusted input reaching SQL construction instead of a parameterized query.Follow input into query construction, record the query location, and verify that the safer example binds parameters instead of interpolating text.A constant query or a parameterized query builder can be a false positive; confirm the data flow and exercise the repaired query with hostile input.

Risky pattern / Safer pattern

SQL injection: A useful result must be explainable to a developer and portable to the next review surface. Inspect the concrete evidence below before changing team policy.

Risky patternSafer pattern
db.query(`SELECT * FROM users WHERE id = ${id}`);db.query("SELECT * FROM users WHERE id = ?", [id]);

From local signal to shared gate.

SQL injection: Use the smallest workflow that proves value. Each later step should reuse evidence the team already understands. Detect untrusted input reaching SQL construction instead of a parameterized query.

StepCommand or actionDecision
1Run a quick local scanIs the signal useful?
2Inspect and repair findingsIs the fix specific and reproducible?
3Export portable evidenceDoes the reviewer need SARIF, JSON, or HTML?
4Promote the trusted threshold to CIWhich severity should block a pull request?
radar scan . --quick
radar scan . --format sarif --fail-on high

Evidence to inspect before you trust the result.

SQL injection: A useful result must be explainable to a developer and portable to the next review surface. Inspect the concrete evidence below before changing team policy. Follow input into query construction, record the query location, and verify that the safer example binds parameters instead of interpolating text.

  • Rule ID: RADAR-SEC-SQLI
  • Exact file location, rule context, severity, confidence, and remediation guidance.
  • Terminal output, SARIF, JSON, or HTML artifacts generated from the same finding set.
  • Source stays in the workspace or CI runner where the scan executes.

Good fit and limits

Use SQL injection when Developers and reviewers deciding how to handle SQL injection findings before merge. Keep the boundary explicit: A constant query or a parameterized query builder can be a false positive; confirm the data flow and exercise the repaired query with hostile input.

Run the local proof before adopting a shared gate.

  • Good fit: Developers and reviewers deciding how to handle SQL injection findings before merge.
  • Not a fit / do not overreach: A constant query or a parameterized query builder can be a false positive; confirm the data flow and exercise the repaired query with hostile input.

Questions to verify before rollout

These questions keep the decision tied to observable evidence rather than a broad product promise.

What does SQL injection cover in practice?

SQL injection: The practical scope is Detect untrusted input reaching SQL construction instead of a parameterized query.. Start with the listed entities or files and confirm the result on representative code.

Which evidence should I inspect for SQL injection?

SQL injection: Inspect Follow input into query construction, record the query location, and verify that the safer example binds parameters instead of interpolating text. Keep the source location, rule or comparison context, and exported artifact together.

What should I not infer from SQL injection?

SQL injection: Do not infer universal coverage. A constant query or a parameterized query builder can be a false positive; confirm the data flow and exercise the repaired query with hostile input. Use the relevant comparison or workflow page to test the boundary before changing policy.

What should I try first for SQL injection?

SQL injection: Start with a local run, review one real finding, then choose the linked report, agent, CI, or trust workflow that matches the next decision.

Feature: security scannerChoose the next page that matches the remaining implementation or evaluation step.Feature: sastChoose the next page that matches the remaining implementation or evaluation step.Docs: rulesChoose the next page that matches the remaining implementation or evaluation step.
Rule reference

Start with the problem you need to solve.

Open page →
Local SASTLocal SAST for Developers and CI

Developer-first static application security testing that scans source locally, emits SARIF for GitHub code scanning, and gives coding agents deterministic fix context.

ProofSee sample report

Inspect the fields and formats in a sample finding.

InstallInstall Radar

Run a local scan on a real repository.

Validate the workflow on your own code.

Start with one local scan, inspect the evidence, and expand to reports, agents, or CI only when the signal is useful.

Check this risk locallyReview detection evidence