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Glossary

JSON Web Token (JWT)

A JSON Web Token (JWT) is a compact, URL-safe token format defined in RFC 7519, used to securely transmit claims between two parties as a JSON object that can be digitally signed or encrypted.
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SECURE CREDENTIAL MANAGEMENT

What is JSON Web Token (JWT)?

A JSON Web Token (JWT) is a compact, URL-safe token format defined in RFC 7519, used to securely transmit claims between two parties as a JSON object that can be digitally signed or encrypted.

A JSON Web Token (JWT) is a compact, URL-safe means of representing claims to be transferred between two parties, defined by the IETF standard RFC 7519. It is a self-contained token that encodes a header, a payload (containing the claims), and a signature in a Base64Url-encoded string, often separated by dots (e.g., xxxxx.yyyyy.zzzzz). JWTs are primarily used for authorization and information exchange, enabling stateless authentication where the server can validate the token's integrity without querying a database.

The token's integrity and authenticity are secured through digital signatures (using algorithms like HMAC SHA256 or RSA) or encryption (JWE). In the context of AI agents and secure credential management, JWTs provide a standardized method for an agent to present a short-lived, scoped credential to an API after an initial OAuth 2.0 flow. This is critical for implementing the least privilege principle, as the JWT's payload can specify precise permissions, avoiding the need for the agent to store or transmit long-lived, powerful API keys.

SECURE CREDENTIAL MANAGEMENT

Key Characteristics of JWTs

A JSON Web Token (JWT) is a compact, URL-safe token format defined in RFC 7519, used to securely transmit claims between two parties. Its design provides several foundational characteristics essential for modern API authentication and authorization.

01

Compact & URL-Safe Format

A JWT is a compact string consisting of three Base64Url-encoded segments separated by dots (.): Header.Payload.Signature. This design makes it suitable for transmission in HTTP headers (like Authorization: Bearer <token>) and URL query parameters. The use of Base64Url encoding, which replaces + and / with - and _ and omits padding, ensures the token is safe for inclusion in URLs without additional encoding.

02

Self-Contained Claims

The JWT Payload contains a set of claims—statements about an entity (typically the user) and additional metadata. These are categorized as:

  • Registered Claims: Predefined, standard claims like iss (issuer), exp (expiration time), sub (subject).
  • Public Claims: Custom claims defined in the IANA JSON Web Token Registry or using collision-resistant names (e.g., URIs).
  • Private Claims: Custom claims agreed upon by parties, like user_id or scope. Because claims are embedded, a service can verify the token and immediately access user data without a separate database lookup, reducing latency and load.
03

Digital Signatures & Integrity

JWTs use digital signatures or Message Authentication Codes (MACs) to verify that the token hasn't been tampered with. The most common signing algorithms are:

  • HMAC with SHA-256 (HS256): A symmetric algorithm using a shared secret key.
  • RSASSA-PKCS1-v1_5 with SHA-256 (RS256): An asymmetric algorithm using a private key to sign and a public key to verify.
  • ECDSA with P-256 and SHA-256 (ES256): An asymmetric algorithm using elliptic curve cryptography. The signature is computed over the concatenated Header and Payload. Any alteration invalidates the signature, ensuring data integrity.
04

Stateless Session Management

JWTs enable stateless authentication. The server does not need to maintain a session store; it simply validates the token's signature and checks its claims (like exp). This architecture is highly scalable for distributed systems and microservices, as any service with the correct verification key can independently authenticate a request. However, it requires careful design for token revocation, often handled via short-lived tokens and refresh token patterns.

05

Standardized Structure (RFC 7519)

JWTs are defined by a family of IETF standards, ensuring interoperability:

  • RFC 7519 (JWT): Defines the core token format and claim semantics.
  • RFC 7515 (JWS): JSON Web Signature standard for signed JWTs.
  • RFC 7516 (JWE): JSON Web Encryption standard for encrypted JWTs. This standardization allows for a wide ecosystem of libraries across programming languages (e.g., jsonwebtoken in Node.js, PyJWT in Python, java-jwt) that can create, parse, and validate tokens consistently.
06

Common Security Considerations

While powerful, JWTs require specific security practices:

  • Algorithm Verification: Always explicitly verify the signing algorithm (alg in header) to prevent algorithm confusion attacks where an attacker forces a service to treat a token signed with a weak algorithm (like none) as valid.
  • Claim Validation: Mandatorily validate the exp (expiration), iss (issuer), and aud (audience) claims.
  • Key Management: Securely manage signing keys. Use asymmetric cryptography (RS256/ES256) when the verifying party should not have the signing key. Never embed secrets in client-side code.
  • Token Storage: Store JWTs securely in memory or HttpOnly, Secure cookies to mitigate XSS theft. Avoid local storage for sensitive applications.
SECURE CREDENTIAL MANAGEMENT

How JSON Web Tokens Work

A technical breakdown of the JSON Web Token (JWT) format, its structure, and its role in secure API authentication and authorization.

A JSON Web Token (JWT) is a compact, URL-safe token format defined in RFC 7519, used to securely transmit claims between two parties as a JSON object that can be digitally signed or encrypted. The token consists of three Base64Url-encoded parts separated by dots: a header specifying the algorithm, a payload containing the claims, and a signature that verifies the token's integrity. JWTs enable stateless authentication, where the server can validate a token without storing session data, making them a cornerstone of modern API security and OAuth 2.0 flows.

JWTs are commonly used as bearer tokens in authorization headers (e.g., Authorization: Bearer <token>). The payload's claims, such as sub (subject) and exp (expiration time), are standardized but extensible. Signing, typically with HMAC or RSA, ensures the token hasn't been tampered with, though the payload itself is not encrypted unless using the JWE (JSON Web Encryption) specification. This design allows for efficient, scalable authentication but requires secure transmission (e.g., over HTTPS) and robust key management to prevent token theft or forgery.

SECURE CREDENTIAL MANAGEMENT

Frequently Asked Questions

A JSON Web Token (JWT) is a compact, URL-safe token format defined in RFC 7519, used to securely transmit claims between two parties as a JSON object that can be digitally signed or encrypted. These FAQs address its core mechanics, security, and role in AI agent authentication.

A JSON Web Token (JWT) is a compact, URL-safe token format defined in RFC 7519, used to securely transmit claims between two parties as a JSON object that can be digitally signed or encrypted. It works by encoding a set of claims in a three-part structure: a Header, a Payload, and a Signature.

  1. Header: Specifies the token type (JWT) and the signing algorithm (e.g., HS256 or RS256).
  2. Payload: Contains the claims—statements about an entity (typically, the user) and additional metadata like issuer (iss), subject (sub), and expiration time (exp).
  3. Signature: Created by signing the encoded header and payload with a secret or private key, ensuring the token's integrity and authenticity.

The three parts are Base64Url-encoded, concatenated with periods, forming the final token: aaaa.bbbb.cccc. A receiving party validates the signature to verify the token was issued by a trusted source and has not been tampered with, then trusts the claims within the payload.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.