Out Of Bounds Read in Aspnet with Bearer Tokens

An Out Of Bounds Read in an ASP.NET API occurs when the application reads memory beyond the intended buffer or collection boundaries. When Bearer Tokens are used for authentication, the token itself is often deserialized and parsed to extract claims. If the token payload is processed with unchecked indices or lengths—such as reading a claim at a position derived from attacker-controlled data without validating bounds—an out-of-bounds read can occur.

Consider an endpoint that decodes a JWT Bearer Token and directly indexes into the claims array using a value supplied by the client, such as an index parameter. Because the token is sent in the Authorization header, the attacker does not need to authenticate to trigger this behavior during unauthenticated scanning. The ASP.NET runtime does not inherently prevent reading outside the array; if the index is not constrained to [0, claims.Count - 1], the runtime may read adjacent memory, potentially exposing internal structures or causing unstable behavior that can be observed through error messages or timing differences.

In the context of middleBrick’s 12 security checks, this vulnerability can surface during the Input Validation and Authentication checks when the scanner sends manipulated Bearer Tokens with edge-case claim structures or extreme index values. The scanner does not require credentials; it probes the unauthenticated attack surface. Because ASP.NET pipelines often bind claims to parameters automatically, an insecure implementation—such as iterating over claims with a loop driven by unchecked external input—can expose an Out Of Bounds Read. Real-world patterns include using ClaimTypes.NameIdentifier or custom roles where an attacker-supplied numeric position leads to reading beyond the claims buffer.

Real frameworks and libraries do not guarantee bounds safety when developers perform manual indexing. For example, reading claims[suppliedIndex] without verifying suppliedIndex >= 0 && suppliedIndex < claims.Count is unsafe. This becomes critical when token metadata is parsed into arrays or lists and later accessed via parameters that influence iteration or selection. The scanner’s tests for Input Validation will flag cases where negative or excessively large indices are accepted, as these can trigger out-of-bounds behavior.

Additionally, malformed or oversized tokens may exacerbate the issue. If the token deserialization logic uses fixed-size buffers or assumes a bounded number of claims, an attacker providing a token with many claims or nested structures might move the read pointer outside intended memory regions. Because middleBrick evaluates the unauthenticated surface, it can detect endpoints that accept Bearer Tokens but do not enforce strict bounds when processing claims, highlighting the need for explicit validation before any index-based access.

To summarize, the combination of ASP.NET’s flexible token handling and unchecked index operations on claims derived from Bearer Tokens creates a scenario where an Out Of Bounds Read can occur. The scanner identifies this by sending tokens with manipulated structures and observing responses, focusing on validation gaps rather than relying on authenticated sessions.

Remediation centers on validating any external index used to access claims or token-derived collections and avoiding direct indexing based on client input. Always treat data from Bearer Tokens as untrusted and enforce bounds before accessing arrays or lists.

First, validate the index against the collection length. Instead of directly indexing, check range and handle invalid cases explicitly:

var identity = User.Identity as ClaimsIdentity;
if (identity != null)
{
    var claims = identity.Claims.ToList();
    if (int.TryParse(Request.QueryString["index"], out int index))
    {
        if (index >= 0 && index < claims.Count)
        {
            var targetClaim = claims[index];
            // Use targetClaim safely
        }
        else
        {
            return BadRequest("Invalid index");
        }
    }
}

This pattern ensures that the index is within valid bounds before accessing the claims list, preventing out-of-bounds reads regardless of token content.

Second, avoid deriving collection positions from token metadata unless strictly necessary. If you must map a token claim to a position, use a dictionary or predefined mapping rather than raw numeric indices. For example, if you need to extract a role by name, search by claim type instead of position:

var roleClaim = User.Claims.FirstOrDefault(c => c.Type == ClaimTypes.Role);
if (roleClaim != null)
{
    string role = roleClaim.Value;
    // Process role safely
}

This approach removes the risk of index-based errors entirely because it does not rely on a numeric position that could be manipulated via the token or request parameters.

Third, when deserializing tokens, enforce schema validation and reject tokens with unexpected structures. Use the built-in JWT Bearer handler configuration to set constraints on the number of claims or the format of specific claims. For instance, configure token validation parameters to limit the maximum claim count:

services.AddAuthentication(JwtBearerDefaults.AuthenticationScheme)
    .AddJwtBearer(options =>
    {
        options.TokenValidationParameters = new TokenValidationParameters
        {
            ValidateIssuer = true,
            ValidateAudience = true,
            ValidateLifetime = true,
            ValidateIssuerSigningKey = true,
            // Additional constraints reduce the risk of malformed token processing
            NameClaimType = ClaimTypes.Name,
            RoleClaimType = ClaimTypes.Role
        };
    });

While this configuration does not directly bound index access, it reduces the attack surface by ensuring tokens conform to expected formats before claims are extracted and indexed.

Finally, apply defense in depth: combine input validation with logging and monitoring for anomalous token structures. If an out-of-bounds condition is attempted, the application should return a generic error and log the event. middleBrick’s scans will highlight endpoints where Bearer Token processing lacks these safeguards, and the Pro plan’s continuous monitoring can alert you when new endpoints introduce unchecked index patterns.