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:

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

Severity Levels

Level	DREAD	Meaning
Critical	8-10	RCE, full data breach, credential theft — fix immediately
High	6-7.9	Auth bypass, significant data exposure, broken crypto — fix in current sprint
Medium	4-5.9	Limited exposure, session issues, defense weakening — fix in next sprint
Low	1-3.9	Minor info disclosure, best-practice deviations — fix opportunistically

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.

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?
Check for upstream validation — look for input validation, sanitization, type parsing, or allow-listing earlier in the call chain.
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.
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

Severity	Vulnerability	Defense	Standard Library Solution
Critical	SQL Injection	Parameterized queries separate data from code	`database/sql` with `?` placeholders
Critical	Command Injection	Pass args separately, never via shell concatenation	`exec.Command` with separate args
High	XSS	Auto-escaping renders user data as text, not HTML/JS	`html/template`, `text/template`
High	Path Traversal	Scope file access to a root, prevent `../` escapes	`os.Root` (Go 1.24+), `filepath.Clean`
Medium	Timing Attacks	Constant-time comparison avoids byte-by-byte leaks	`crypto/subtle.ConstantTimeCompare`
High	Crypto Issues	Use vetted algorithms; never roll your own	`crypto/aes`, `crypto/rand`
Medium	HTTP Security	TLS + security headers prevent downgrade attacks	`net/http`, configure TLSConfig
Low	Missing Headers	HSTS, CSP, X-Frame-Options prevent browser attacks	Security headers middleware
Medium	Rate Limiting	Rate limits prevent brute-force and resource exhaustion	`golang.org/x/time/rate`, server timeouts
High	Race Conditions	Protect shared state to prevent data corruption	`sync.Mutex`, channels, avoid shared state

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-linter skill for configuration and usage.

For deeper security-specific analysis:

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

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

Severity	Anti-Pattern	Why It Fails	Fix
High	Security through obscurity	Hidden URLs are discoverable via fuzzing, logs, or source	Authentication + authorization on all endpoints
High	Trusting client headers	`X-Forwarded-For`, `X-Is-Admin` are trivially forged	Server-side identity verification
High	Client-side authorization	JavaScript checks are bypassed by any HTTP client	Server-side permission checks on every handler
High	Shared secrets across envs	Staging breach compromises production	Per-environment secrets via secret manager
Critical	Ignoring crypto errors	`_, _ = encrypt(data)` silently proceeds unencrypted	Always check errors — fail closed, never open
Critical	Rolling your own crypto	Custom encryption hasn't been analyzed by cryptographers	Use `crypto/aes` GCM, `golang.org/x/crypto/argon2`

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.

golang-security