SECURITY-THREAT-MODEL.md

<!--
  Licensed to the Apache Software Foundation (ASF) under one
  or more contributor license agreements.  See the NOTICE file
  distributed with this work for additional information
  regarding copyright ownership.  The ASF licenses this file
  to you under the Apache License, Version 2.0 (the
  "License"); you may not use this file except in compliance
  with the License.  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing,
  software distributed under the License is distributed on an
  "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  KIND, either express or implied.  See the License for the
  specific language governing permissions and limitations
  under the License.
-->

# Apache Iceberg Python Security Threat Model

This document describes the detailed security threat model for Apache
Iceberg Python. It is intended for maintainers and automated security triage.

## Purpose

Apache Iceberg Python is primarily a client library and implementation of the
Iceberg table format and catalog interactions for Python applications and
services. It is commonly embedded in larger systems that provide their own
authentication, authorization, and credential management. Because of that
deployment model, many bug classes that look security-relevant in the abstract
are not actually security vulnerabilities in Iceberg Python itself.

This model is intended to answer:

- what Iceberg Python generally treats as a security vulnerability
- what Iceberg Python generally treats as correctness, hardening, or
  deployment work
- which boundaries are primarily owned by Iceberg Python versus the
  surrounding catalog, application, or service
- which issue classes should be downgraded by default by scanners

## Scope

This model is scoped to the Apache Iceberg Python repository itself:

- table format and metadata handling
- catalog and REST catalog clients
- transport, credential, and configuration handling implemented in this repo
- helper tooling shipped in this repo

It is not a general threat model for every Python service that embeds Iceberg
Python.

In particular, it does not attempt to define the complete security model for:

- applications or services that embed Iceberg Python
- storage-level authorization enforced outside Iceberg Python

## Security Goals

Iceberg Python should:

- avoid exposing secrets or delegated credentials to principals that were not
  already trusted with them
- avoid creating new unauthorized capabilities in Iceberg Python-owned
  components
- avoid violating trust boundaries that Iceberg Python itself owns, such as
  leaking auth, transport, or credential-bearing state across catalog or
  client boundaries in the same process

Iceberg Python does not aim to be the primary enforcement point for:

- user-to-user authorization inside the embedding application
- storage-level authorization
- service-side credential scoping performed by an external catalog

## Roles

### Operator

The operator configures the surrounding catalog, application, service, and
storage integration around Iceberg Python. This role is trusted to choose
endpoints, warehouses, storage integrations, and credentials.

### Catalog control plane

The catalog control plane resolves tables and supplies metadata, locations,
configuration, and delegated credentials to Iceberg Python. It may be
implemented by a REST catalog server or another catalog implementation.
Iceberg Python assumes this control plane is trusted and outside its primary
security boundary.

### REST catalog client

The REST catalog client consumes catalog-provided metadata, configuration, and
credentials. Client-side bugs in routing, caching, or reuse may still be
security-relevant if they leak credential-bearing state across boundaries that
the Iceberg Python client is expected to preserve.

### Embedding application

Applications and services embedding Iceberg Python are responsible for their
own user-facing authorization boundaries unless Iceberg Python explicitly
documents otherwise.

### Table writer or maintainer

This role may already have legitimate power to write or replace table
metadata, write or delete files, choose paths under an allowed warehouse or
table location, and invoke destructive maintenance operations. If a report
only shows a new way to achieve the same effect this role can already cause
legitimately, it is usually not a security issue in Iceberg Python.

## Trust Boundaries

### Boundary 1: operator-trusted configuration

The following are generally treated as trusted operator or deployment inputs:

- catalog properties
- endpoint configuration
- warehouse and storage roots
- transport wiring and credential configuration

If a report depends on the attacker controlling those values directly, it is
usually not a vulnerability in Iceberg Python itself.

### Boundary 2: catalog-supplied metadata

Iceberg Python often accepts metadata locations, table properties, namespace
properties, and related control-plane information from a catalog. By default,
Iceberg Python treats those sources as trusted.

This means a malicious catalog supplying incorrect or malicious metadata is
usually not an Iceberg Python vulnerability by itself.

### Boundary 3: REST catalog-supplied configuration and delegated storage access

In REST deployments, Iceberg Python may also accept service endpoints,
configuration, and delegated storage access from the REST catalog server. By
default, those are treated as trusted control-plane inputs unless Iceberg
Python explicitly documents a stronger guarantee.

This means a malicious REST catalog server sending dangerous endpoints is
usually not an Iceberg Python vulnerability by itself. It also means many
credential-selection bugs are often correctness or specification issues rather
than security boundary failures.

The major exception is secret exposure. If Iceberg Python surfaces credentials
or secrets to a new audience that was not already trusted with them, that is
security-relevant.

### Boundary 4: storage-level authorization

Object store permissions are enforced by the storage provider and the
credentials the surrounding deployment chooses to hand to Iceberg Python.
Iceberg Python is not the root authority for bucket- or object-level
authorization.

## In-Scope Security Vulnerabilities

The following categories are generally security-relevant in Iceberg Python
when the report is credible and reproducible.

### 1. Secret or credential disclosure to a new audience

Examples include:

- catalog or storage credentials exposed through a user-visible surface
- one catalog's credentials or auth state leaking into another catalog or
  client

### 2. Iceberg Python-owned trust-boundary violations

Security issues exist when Iceberg Python itself is expected to separate
catalogs, clients, or principals and fails to do so.

Examples include:

- process-global auth or transport state crossing catalog instances
- secret-bearing state from one principal reused for another principal within
  an Iceberg Python-owned boundary

## Usually Out of Scope or Non-Security by Default

These categories may still be real bugs worth fixing, but they are not usually
security vulnerabilities in Iceberg Python itself.

### 1. Correctness bugs

Examples include incorrect metadata handling, ambiguous matching semantics,
and logic bugs that do not create a new trust-boundary violation.

### 2. Parser hardening and malformed-input robustness

Malformed-input crashes, runtime exceptions, and memory amplification are
usually treated as robustness or hardening work rather than security issues in
Iceberg Python itself.

### 3. Malicious catalog or external service scenarios

Reports that require a malicious catalog or other external control-plane
service are usually outside Iceberg Python's primary security boundary.

### 4. Equivalent-harm reports

If the actor already has a legitimate capability that can cause the same harm,
the new path is usually not a security issue.

## Scanner Calibration Rules

A scanner targeting Iceberg Python should treat a finding as higher-confidence
only if it plausibly shows one of the following:

- exposure of a secret or delegated credential to a new audience
- creation of a new unauthorized capability in an Iceberg Python-owned
  component
- violation of an Iceberg Python-owned trust boundary rather than a
  surrounding catalog, application, service, or operator boundary

A finding should be downgraded or rejected by default if it instead depends
primarily on:

- malformed-input robustness or denial-of-service behavior
- a malicious catalog or external service
- a principal that already has equivalent power through legitimate write or
  maintenance capabilities