Prototype Pollution in Buffalo with Jwt Tokens

Prototype pollution in JavaScript frameworks such as Buffalo can interact dangerously with JWT token handling when user-controlled data modifies object prototypes that later influence token verification or claims processing. In Buffalo, routes and handlers often construct objects from request parameters, query strings, or JSON payloads before passing data into JWT parsing or validation logic. If an attacker can inject properties like __proto__, constructor.prototype, or other inherited keys into these objects, they may alter shared prototypes used elsewhere, including objects that participate in JWT decoding, claim extraction, or session derivation.

Consider a scenario where Buffalo deserializes JSON body into a map and later uses that map to build JWT claims without isolating or sanitizing keys. A payload such as {"role": "user", "__proto__": {"isAdmin": true}} could pollute the prototype of objects used downstream. If the JWT handling code relies on inherited properties for defaults or permissions, the injected isAdmin may become visible during claim inspection, effectively elevating privileges without a valid token signature. This becomes an authentication bypass when the polluted prototype affects how tokens are parsed, verified, or transformed into internal session objects.

The risk is compounded when Buffalo applications use shared mutable objects or extend prototypes to add helper methods for token utilities. An attacker does not need to compromise the signing key; they exploit the runtime object model to change behavior that JWT verification code inherits. For example, if a utility function checks obj.isAdmin and obj inherits isAdmin from a polluted prototype, the authorization logic may incorrectly treat an unauthenticated context as privileged. Because JWT tokens often carry authorization decisions, any change to how claims are read can undermine the integrity of access control, even when the token itself remains cryptographically intact.

Tools like middleBrick detect such issues by scanning the unauthenticated attack surface and identifying where user input traverses into object construction paths that touch JWT-related libraries. The scanner does not assume internal architecture but flags patterns where dynamic key assignment could reach prototype-sensitive code. By correlating input validation checks with JWT token parsing flows, findings highlight whether pollution vectors intersect with token handling and whether remediation should focus on input sanitization, property hiding, or isolation of token logic from mutable prototypes.

Remediation focuses on preventing user-controlled data from reaching prototype-sensitive code paths and ensuring JWT token handling remains isolated from dynamic object extension. In Buffalo, use strict parsing and avoid merging raw request maps directly into structures used for JWT claims. Prefer explicit field extraction and validation libraries that do not rely on prototype chain lookups.

Example of unsafe code that should be avoided:

// Unsafe: directly using a raw map that may contain __proto__
func (ctrl MyController) Login(c buffalo.Context) error {
    var data map[string]interface{}
    if err := c.Bind(&data); err != nil {
        return err
    }
    // data may contain injected prototype keys
    claims := extractClaims(data) // uses data in a way that traverses prototypes
    token := issueJWT(claims)
    return c.Render(200, r.JSON(token))
}

Safer approach with explicit extraction and rejection of disallowed keys:

// Safe: explicit field access and prototype-safe handling
func (ctrl MyController) Login(c buffalo.Context) error {
    var payload struct {
        Role  string `json:"role"`
        Email string `json:"email"`
        // only expected fields
    }
    if err := c.Bind(&payload); err != nil {
        return err
    }
    // Build claims from concrete struct, not from raw map
    claims := map[string]interface{}{
        "role":  payload.Role,
        "email": payload.Email,
    }
    token := issueJWT(claims)
    return c.Render(200, r.JSON(token))
}

When using JWT libraries, ensure decoding utilities do not rely on object property lookups that traverse __proto__. For instance, when converting claims to a map, prefer library functions that create plain objects without linking to shared prototypes. If you maintain utility functions that inspect claims, guard against inherited properties by using Object.prototype.hasOwnProperty semantics or language-specific checks that ignore the prototype chain.

In a Go-based Buffalo application, you typically handle JSON binding into concrete structs, which naturally avoids prototype pollution because Go does not have mutable prototypes in the JavaScript sense. However, if you interface with JavaScript services or use embedded V8 via plugins, treat all external data as hostile. Validate and sanitize any data that will cross language boundaries before it influences JWT construction or verification. middleBrick can be used in CI/CD with the GitHub Action to enforce that no scan fails due to high-risk findings, and the Pro plan provides continuous monitoring so changes to token handling logic are re-evaluated automatically.