Distributed Denial Of Service with Bearer Tokens

Bearer token validation is a common entry point for API traffic, and when the validation logic performs expensive operations without limits, an attacker can turn it into a denial‑of‑service vector. The most frequent patterns involve:

• CPU‑heavy signature verification. Many libraries (e.g., jsonwebtoken, node-jose) perform RSA/ECDSA verification on every request. Sending a high volume of tokens with invalid signatures forces the server to run the costly asymmetric crypto routine before rejecting the token.
• External token introspection calls. When an API delegates validation to an identity provider (IdP) via an introspection endpoint, each request triggers an outbound HTTP call. An attacker can flood the API with bogus tokens, causing the IdP to be overwhelmed and the API to exhaust outbound connections or thread pools.
• Revocation list or database lookups. Systems that check a token against a blacklist stored in a relational database, Redis set, or similar structure incur a disk or network lookup per request. A flood of unique (or randomly generated) tokens can cause cache misses and saturate the storage layer.
• Token size amplification. Some implementations decode the token payload before verifying the signature. Extremely large payloads (megabytes) can consume memory and trigger allocation failures even before crypto work begins.

These abuse patterns have been observed in real‑world incidents (e.g., excessive load on OAuth introspection endpoints reported in 2021) and map directly to OWASP API4:2023 "Lack of Resources & Rate Limiting". A related JWT‑library issue is documented as CVE-2017-15095, which shows how flaws in token handling can be leveraged for abuse.

Detecting a DoS‑prone bearer‑token flow requires looking for missing throttling, unbounded crypto work, and external calls that are not cached or rate‑limited. middleBrick performs these checks automatically when you submit an API URL:

• It probes the unauthenticated attack surface, invoking the token‑validation endpoint (if discoverable) with a variety of malformed and valid tokens.
• It measures response times and error rates under load to spot expensive verification steps that do not throttle.
• It checks for missing or insufficient rate‑limiting headers (e.g., 429 Too Many Requests) and for lack of caching of public keys or IdP responses.
• It reports findings with severity scores, pointing to the exact code path (e.g., JWT verification middleware) that needs attention.

Example of invoking the scanner from the terminal:

npx middlebrick scan https://api.example.com/orders

The resulting JSON report includes a "Rate Limiting" check, an "Authentication" check (where token validation is examined), and a "Data Exposure" check that may reveal excessive payload sizes. If any of these checks return a low score, the API is likely vulnerable to bearer‑token‑based DoS.

Mitigation focuses on limiting the work done per