Fix SQL Injection (Legacy & Modern) in Buffalo
Buffalo's pop ORM is a solid abstraction, but developers frequently bypass its safety features by resorting to raw SQL or improper string formatting. If you're using fmt.Sprintf or string concatenation to build queries, you're inviting a blind SQLi or data exfiltration. In the Buffalo ecosystem, safety is achieved through parameter binding—no exceptions.
The Vulnerable Pattern
func (v UsersResource) Show(c buffalo.Context) error {
query := fmt.Sprintf("SELECT * FROM users WHERE id = '%s'", c.Param("id"))
user := models.User{}
err := models.DB.RawQuery(query).First(&user)
if err != nil {
return c.Error(404, err)
}
return c.Render(200, r.JSON(user))
}
The Secure Implementation
The vulnerability stems from treating user-controlled input as executable SQL code. By using fmt.Sprintf, the input is concatenated directly into the query string, allowing an attacker to break out of the quote context. The fix utilizes Pop's built-in parameterization. When you pass arguments to .Where() or .RawQuery() after the string template, the underlying database driver (pgx, mysql, etc.) handles the sanitization and ensures the input is treated strictly as a literal value, neutralizing the injection vector.
func (v UsersResource) Show(c buffalo.Context) error { user := models.User{} // Modern Buffalo/Pop approach: Use internal QueryBuilder with placeholders err := models.DB.Where("id = ?", c.Param("id")).First(&user)// Legacy Raw approach: Still secure using positional arguments // err := models.DB.RawQuery("SELECT * FROM users WHERE id = ?", c.Param("id")).First(&user) if err != nil { return c.Error(404, err) } return c.Render(200, r.JSON(user))
}
Your Buffalo API
might be exposed to SQL Injection (Legacy & Modern)
74% of Buffalo apps fail this check. Hackers use automated scanners to find this specific flaw. Check your codebase before they do.
Free Tier • No Credit Card • Instant Report
Verified by Ghost Labs Security Team
This content is continuously validated by our automated security engine and reviewed by our research team. Ghost Labs analyzes over 500+ vulnerability patterns across 40+ frameworks to provide up-to-date remediation strategies.