Regex Dos in Buffalo

In Buffalo web applications, Regex DoS vulnerabilities often occur when user-controlled input is passed directly into regular expression matching functions without proper validation or timeout controls. Buffalo's routing and parameter handling can inadvertently expose these risks, especially in middleware or handlers that use Go's regexp package for input validation, path matching, or sanitization.

A common pattern involves Buffalo's Param function retrieving route parameters that are then used in regexp.MatchString or similar calls. For example, a handler validating a user-provided username against a complex regex for 'security' purposes might be vulnerable if the regex exhibits catastrophic backtracking. An attacker could supply a carefully crafted input like a repeated many times followed by !@# to force exponential time complexity in patterns such as ^(a+)+$ or ^([a-zA-Z]+)*$.

This is particularly dangerous in Buffalo applications that use custom validation middleware. Consider a scenario where a developer creates a reusable validation function for form inputs using user-supplied patterns (perhaps from a configuration file or admin interface). If that pattern is not vetted for ReDoS risk and is applied to large inputs, it can lead to high CPU consumption, effectively denying service. Real-world analogues include CVEs like CVE-2019-16235 in Ruby's URI parser and CVE-2022-24765 in Go's net/url, though the latter is path-specific; the principle applies to any regex engine processing untrusted input.

Buffalo's strength in rapid development can sometimes lead to overlooked validation logic, especially when developers prioritize functionality over security hardening in input processing pipelines. Without built-in regex timeout mechanisms in Go's standard regexp package (prior to Go 1.20), applications are inherently vulnerable unless mitigations are applied at the code level.

Identifying Regex DoS risks in Buffalo applications requires looking for specific code patterns where user input flows into regex evaluation. middleBrick detects these issues during its black-box scan by analyzing responses to specially crafted payloads designed to trigger excessive backtracking, without needing source code access.

During a scan, middleBrick sends a series of increasing-length payloads to endpoints that reflect user input in responses or behavior. For instance, if an endpoint returns different response times based on input length in a non-linear way (e.g., doubling input size more than doubles response time), it may indicate a ReDoS vulnerability. middleBrick correlates this with the 12 security checks, particularly under 'Input Validation' and 'Rate Limiting', where abnormal processing times can signal potential denial-of-service conditions.

Consider a Buffalo handler that validates a token parameter:

func TokenHandler(c buffalo.Context) error {
    token := c.Param("token")
    matched, _ := regexp.MatchString(`^([a-zA-Z0-9]+)+$`, token)
    if !matched {
        return c.Error(400, errors.New("invalid token"))
    }
    // ... continue processing
    return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}

The regex ^([a-zA-Z0-9]+)+$ is vulnerable to ReDoS with input like aaaaaaaaaaaaaaaaaaaa!. middleBrick would detect this by observing disproportionate response times when sending payloads of varying lengths containing many a characters followed by a non-matching character.

Additionally, middleBrick's OpenAPI/Swagger spec analysis (if available) can identify endpoints where parameters are used in validation contexts, helping prioritize scanning efforts. Even without a spec, its active probing of the unauthenticated attack surface ensures that publicly accessible endpoints with regex-based validation are tested for this class of vulnerability.

Fixing Regex DoS in Buffalo applications involves eliminating risky regex patterns, implementing timeouts, or refactoring validation logic to avoid exponential backtracking. Since Go's regexp package gained built-in timeout support in Go 1.20 via regexp.CompilePOSIX and regexp.Compile with context, Buffalo developers should leverage this when possible.

For the vulnerable token handler example, the fix depends on the Go version:

• Go 1.20+: Use context-aware compilation with a timeout:

func TokenHandler(c buffalo.Context) error {
    token := c.Param("token")
    ctx, cancel := context.WithTimeout(context.Background(), 100*time.Millisecond)
    defer cancel()
    re, err := regexp.Compile(`^([a-zA-Z0-9]+)+$`)
    if err != nil {
        return c.Error(500, err)
    }
    matched := re.MatchContext(ctx, []byte(token))
    if !matched {
        return c.Error(400, errors.New("invalid token"))
    }
    return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}

• Pre-Go 1.20: Rewrite the regex to avoid nested quantifiers or use length checks:

func TokenHandler(c buffalo.Context) error {
    token := c.Param("token")
    // First, reject excessively long tokens to limit attack surface
    if len(token) > 50 {
        return c.Error(400, errors.New("token too long"))
    }
    // Use a non-vulnerable pattern: simple character class with length constraint
    matched, _ := regexp.MatchString(`^[a-zA-Z0-9]+$`, token)
    if !matched {
        return c.Error(400, errors.New("invalid token"))
    }
    return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}

Another Buffalo-specific approach is to use the framework's built-in validation tags if using github.com/gobuffalo/validate or similar. Instead of custom regex, define struct validators:

type TokenRequest struct {
    Token string `validate:"required,alphanum,max=50"`
}

func TokenHandler(c buffalo.Context) error {
    var req TokenRequest
    if err := c.Bind(&req); err != nil {
        return c.Error(400, err)
    }
    if err := validate.Validate(&req); err != nil {
        return c.Error(400, err)
    }
    return c.Render(200, r.JSON(map[string]string{"status": "ok"}))
}

This avoids regex entirely for common validation tasks. middleBrick's remediation guidance would recommend these patterns, emphasizing that the goal is to eliminate unbounded regex evaluation on user input while maintaining functionality. Developers should also consider implementing global request size limits via Buffalo middleware to reduce the impact of any potential ReDoS attempts.