Find and fix code security with AI code assistants
Snyk Code is an AI-driven static application security testing (SAST) and developer code assistant that finds security and quality issues inline, recommends fixes, and integrates into IDEs and CI. It's best for engineering teams and security engineers who want developer-first vulnerability detection and suggested patches. Pricing starts with a free tier and scales to paid team and enterprise plans, making it accessible for evaluation and team adoption.
Snyk Code is an AI-powered static analysis and code assistant that scans source code for security, correctness, and quality issues. It provides in-IDE feedback, pull-request comments, and prioritized findings with suggested fixes to help developers remediate faster. The primary capability is developer-centric SAST powered by models originating from the DeepCode acquisition and Snyk's ML research, differentiating it through fix-oriented suggestions and integration depth. Snyk Code serves developers, security engineers, and DevOps teams inside the Code Assistants category. There is a Free tier for evaluation, with paid Team and Enterprise plans to unlock higher scan volumes and governance controls.
Snyk Code is Snyk’s developer-focused static application security testing (SAST) and code-assistant offering, launched after Snyk acquired DeepCode’s static-analysis technology. Positioned as an IDE-first security product, Snyk Code combines machine-learned detectors with rule-based checks to surface vulnerabilities, code quality issues, and potential logic flaws. Its core value proposition is to shift left: give developers actionable, fix-oriented guidance where they write code, reduce noisy alerts, and integrate findings into standard workflows rather than siloed security tools. Over time it has been folded into Snyk’s unified platform alongside Snyk Open Source and Snyk Container to provide consolidated developer security tooling.
Snyk Code’s key features focus on detection, remediation, and workflow integration. The product performs ML-trained static analysis (DeepCode lineage) across many languages and frameworks, and outputs categorized findings with CWE and severity mappings. It offers IDE plugins for VS Code and JetBrains IDEs that show inline issue highlights and one-click suggested fixes; those fixes often include code patches or suggested replacements. In CI/CD and repo contexts, Snyk Code runs scans in pull requests on GitHub, GitLab, and Bitbucket, leaving PR comments and gating merges based on configured severity policies. There’s also SARIF export and a CLI for local and pipeline scans, plus dataflow/taint analysis to catch high-risk source-to-sink issues.
Pricing for Snyk Code starts with a Free tier that includes limited scans and basic Snyk Code feedback for individual developers or small projects. Paid plans are offered as Team/Developer subscriptions billed per user and Enterprise plans with custom pricing, additional concurrent scan capacity, single sign-on, audit logging, and governance features. Snyk publishes enterprise-level add-ons for larger organisations needing higher scan throughput, SSO, and bespoke support. Note: exact per-user prices vary by contract and region; Snyk often lists Team-level pricing publicly while enterprise-level pricing is quoted.
Snyk Code is used by application developers to catch and fix vulnerabilities earlier, and by security engineers to prioritize developer remediation. For example, a Senior Backend Engineer uses Snyk Code in VS Code to reduce fix time by addressing prioritized findings before code review, while a Security Engineer uses repo and PR scanning to enforce severity-based break-the-build policies across microservices. It’s commonly compared to Semgrep and CodeQL; choose Snyk Code when you want integrated fix suggestions and developer IDE workflows rather than policy-only scanning.
Three capabilities that set Snyk Code apart from its nearest competitors.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Limited Snyk Code scans, basic IDE feedback, single-user evaluation | Individual developers evaluating Snyk Code |
| Team / Developer | $59/user/month (approx) | Expanded scan quotas, PR scanning, IDE plugins, priority support | Small engineering teams needing regular scans |
| Enterprise | Custom | Unlimited/large quotas, SSO, audit logs, custom SLAs | Large orgs needing governance and scale |
Copy these into Snyk Code as-is. Each targets a different high-value workflow.
Role: You are Snyk Code, an AI-powered static analysis assistant integrated into developer workflows. Task: Given a single PR diff or pasted file, return the top 3 highest-priority actionable findings only. Constraints: 1) Limit output to at most 3 findings. 2) For each finding include: finding_id or rule name, severity (Critical/High/Medium/Low), one-sentence description, exact file:path:line reference, a concrete suggested code fix snippet of at most 6 lines, and confidence (High/Medium/Low). 3) No generic policy or long explanations. Output format: JSON array named findings. Example element: {finding_id: SQL_INJECTION, severity: High, description: ..., file: src/user.js:42, suggested_fix: "use parameterized query", confidence: High}.
Role: You are Snyk Code, a developer-focused static analyzer. Task: Analyze the single source file I paste and list all actionable security and correctness issues. Constraints: 1) For each issue include rule id, CWE if applicable, severity, exact line numbers, short reproducible example of the unsafe code, and a one-paragraph concrete fix with a <=8-line code replacement. 2) Prioritize by severity, then exploitability. 3) Exclude style-only issues. Output format: numbered bullet list where each bullet contains the fields rule_id, cwe, severity, lines, unsafe_snippet, and suggested_fix. Example bullet: 1) rule_id: PATH_TRAVERSAL, cwe: CWE-22, severity: High, lines: 34-38, unsafe_snippet: require(userInput), suggested_fix: sanitize path using path.resolve.
Role: You are Snyk Code producing a machine-readable SARIF/CI policy for enforcement. Task: Given severity thresholds I provide, produce a JSON policy mapping Snyk Code finding severities to CI actions. Constraints: 1) Accept a variable severity_thresholds object (example: critical: block, high: warn, medium: allow) and apply default fallback to allow. 2) Include explicit rule exceptions by rule_id with justification. 3) Provide a compact policy and a human-readable summary. Output format: JSON object with keys: policy_version, severity_mapping, exceptions (array of objects rule_id, rationale), and summary_text. Example severity_mapping entry: High => block.
Role: You are Snyk Code acting as a security lead prioritizing remediation across repositories. Task: Given a list of repository names and scan summaries I paste, return a prioritized remediation plan. Constraints: 1) Rank issues across repos by impact (severity * exposure) and provide an estimated remediation effort as Small/Medium/Large. 2) For each top repo include top 3 findings with file references, recommended owner (team or role), and a proposed 3-week sprint plan with tasks. 3) Limit output to top 5 repositories. Output format: JSON array of repository objects with fields repo, priority_score, top_findings (array), remediation_effort, owner, sprint_plan (weeks and tasks).
Role: You are a Snyk Code senior security engineer authoring enforceable PR-blocking rules. Multi-step task: 1) Inspect example mappings below and generalize into a reusable YAML policy that can be applied in CI. 2) For each rule include severity threshold, rule_id or regex, action (block|warn|allow), justification, and allowed exceptions with expiry timestamps. Constraints: produce parsable YAML plus a short rationale section that defends each blocking rule. Few-shot examples: Example 1 mapping: rule_id: SQL_INJECTION => action: block, justification: exploitable raw query concatenation. Example 2 mapping: rule_id: SENSITIVE_LOGGING => action: warn, justification: review context. Output format: YAML policy followed by rationale comments.
Role: You are Snyk Code acting as a senior backend engineer who produces ready-to-apply fixes. Multi-step task: 1) For the top N findings I paste, produce unified diff patches that apply minimal, secure fixes (use git unified diff format). 2) For each patch include a new or updated unit test that reproduces the vulnerable behavior and asserts the fix; provide test commands and expected results. Constraints: 1) Keep changes minimal and backward-compatible. 2) For each patch include a one-paragraph rationale referencing the specific Snyk rule and CWE. Output format: JSON array of patch objects with fields file_path, diff_patch, test_file_path, test_code, test_command, and rationale. Example diff snippet: --- a/src/user.js +++ b/src/user.js @@ -41,7 +41,8 @@ - vulnerable line + fixed line.
Choose Snyk Code over Semgrep if you prioritize IDE inline fixes and unified Snyk platform visibility across SAST and SCA.
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