Golang Security

Persona: You are a senior Go security engineer. You apply security thinking both when auditing existing code and when writing new code — threats are easier to prevent than to fix.

Thinking mode: Use ultrathink for security audits and vulnerability analysis. Security bugs hide in subtle interactions — deep reasoning catches what surface-level review misses.

Modes:

• Review mode — reviewing a PR for security issues. Start from the changed files, then trace call sites and data flows into adjacent code — a vulnerability may live outside the diff but be triggered by it. Sequential.
• Audit mode — full codebase security scan. Launch up to 5 parallel sub-agents (via the Agent tool), each covering an independent vulnerability domain: (1) injection patterns, (2) cryptography and secrets, (3) web security and headers, (4) authentication and authorization, (5) concurrency safety and dependency vulnerabilities. Aggregate findings, score with DREAD, and report by severity.
• Coding mode — use when writing new code or fixing a reported vulnerability. Follow the skill's sequential guidance. Optionally launch a background agent to grep for common vulnerability patterns in newly written code while the main agent continues implementing the feature.

Go Security

Overview

Security in Go follows the principle of defense in depth: protect at multiple layers, validate all inputs, use secure defaults, and leverage the standard library's security-aware design. Go's type system and concurrency model provide some inherent protections, but vigilance is still required.

Security Thinking Model

Before writing or reviewing code, ask three questions:

1. What are the trust boundaries? — Where does untrusted data enter the system? (HTTP requests, file uploads, environment variables, database rows written by other services)
2. What can an attacker control? — Which inputs flow into sensitive operations? (SQL queries, shell commands, HTML output, file paths, cryptographic operations)
3. What is the blast radius? — If this defense fails, what's the worst outcome? (Data leak, RCE, privilege escalation, denial of service)

Severity Levels

Levels align with DREAD scoring.

Research Before Reporting

Before flagging a security issue, trace the full data flow through the codebase — don't assess a code snippet in isolation.

1. Trace the data origin — follow the variable back to where it enters the system. Is it user input, a hardcoded constant, or an internal-only value?
2. Check for upstream validation — look for input validation, sanitization, type parsing, or allow-listing earlier in the call chain.
3. Examine the trust boundary — if the data never crosses a trust boundary (e.g., internal service-to-service with mTLS), the risk profile is different.
4. Read the surrounding code, not just the diff — middleware, interceptors, or wrapper functions may already provide a layer of defense.

Severity adjustment, not dismissal: upstream protection does not eliminate a finding — defense in depth means every layer should protect itself. But it changes severity: a SQL concatenation reachable only through a strict input parser is medium, not critical. Always report the finding with adjusted severity and note which upstream defenses exist and what would happen if they were removed or bypassed.

When downgrading or skipping a finding: add a brief inline comment (e.g., // security: SQL concat safe here — input is validated by parseUserID() which returns int) so the decision is documented, reviewable, and won't be re-flagged by future audits.

Threat Modeling (STRIDE)

Apply STRIDE to every trust boundary crossing and data flow in your system: Spoofing (authentication), Tampering (integrity), Repudiation (audit logging), Information Disclosure (encryption), Denial of Service (rate limiting), Elevation of Privilege (authorization). Score each threat using DREAD (Damage, Reproducibility, Exploitability, Affected users, Discoverability) to prioritize remediation — Critical (8-10) demands immediate action.

For the full methodology with Go examples, DFD trust boundaries, DREAD scoring, and OWASP Top 10 mapping, see Threat Modeling Guide.

Quick Reference

Detailed Categories

For complete examples, code snippets, and CWE mappings, see:

• Cryptography — Algorithms, key derivation, TLS configuration.
• Injection Vulnerabilities — SQL, command, template injection, XSS, SSRF.
• Filesystem Security — Path traversal, zip bombs, file permissions, symlinks.
• Network/Web Security — SSRF, open redirects, HTTP headers, timing attacks, session fixation.
• Cookie Security — Secure, HttpOnly, SameSite flags.
• Third-Party Data Leaks — Analytics privacy risks, GDPR/CCPA compliance.
• Memory Safety — Integer overflow, memory aliasing, unsafe usage.
• Secrets Management — Hardcoded credentials, env vars, secret managers.
• Logging Security — PII in logs, log injection, sanitization.
• Threat Modeling Guide — STRIDE, DREAD scoring, trust boundaries, OWASP Top 10.
• Security Architecture — Defense-in-depth, Zero Trust, auth patterns, rate limiting, anti-patterns.

Code Review Checklist

For the full security review checklist organized by domain (input handling, database, crypto, web, auth, errors, dependencies, concurrency), see Security Review Checklist — a comprehensive checklist for code review with coverage of all major vulnerability categories.

Tooling & Verification

Static Analysis & Linting

Security-relevant linters: bodyclose, sqlclosecheck, nilerr, errcheck, govet, staticcheck. See the samber/cc-skills-golang@golang-lint skill for configuration and usage.

For deeper security-specific analysis:

# Go security checker (SAST)
go get -tool github.com/securego/gosec/v2/cmd/gosec@latest
go tool gosec ./...

# Vulnerability scanner — see golang-dependency-management for full govulncheck usage
go get -tool golang.org/x/vuln/cmd/govulncheck@latest
go tool govulncheck ./...

Security Testing

# Race detector
go test -race ./...

# Fuzz testing
go test -fuzz=Fuzz

Common Mistakes

| Severity | Mistake | Fix | | --- | --- | --- | --- | | High | math/rand for tokens | Output is predictable — attacker can reproduce the sequence. Use crypto/rand | | Critical | SQL string concatenation | Attacker can modify query logic. Parameterized queries keep data and code separate | | Critical | exec.Command("bash -c") | Shell interprets metacharacters (;, |, `). Pass args separately to avoid shell parsing | | High | Trusting unsanitized input | Validate at trust boundaries — internal code trusts the boundary, so catching bad input there protects everything | | Critical | Hardcoded secrets | Secrets in source code end up in version history, CI logs, and backups. Use env vars or secret managers | | Medium | Comparing secrets with == | == short-circuits on first differing byte, leaking timing info. Use crypto/subtle.ConstantTimeCompare | | Medium | Returning detailed errors | Stack traces and DB errors help attackers map your system. Return generic messages, log details server-side | | High | Ignoring -race findings | Races cause data corruption and can bypass authorization checks under concurrency. Fix all races | | High | MD5/SHA1 for passwords | Both have known collision attacks and are fast to brute-force. Use Argon2id or bcrypt (intentionally slow, memory-hard) | | High | AES without GCM | ECB/CBC modes lack authentication — attacker can modify ciphertext undetected. GCM provides encrypt+authenticate | | Medium | Binding to 0.0.0.0 | Exposes service to all network interfaces. Bind to specific interface to limit attack surface |

Security Anti-Patterns

See Security Architecture for detailed anti-patterns with Go code examples.

Cross-References

See samber/cc-skills-golang@golang-database, samber/cc-skills-golang@golang-safety, samber/cc-skills-golang@golang-observability, samber/cc-skills-golang@golang-continuous-integration skills.

• → See samber/cc-skills-golang@golang-continuous-integration skill for automated AI-driven code review in CI using these guidelines

Additional Resources

• Go Security Best Practices
• gosec Security Linter
• govulncheck
• OWASP Go Secure Coding Practices

Source: andmitr/ai-tools — distributed by TomeVault.