Customizing library models for Java and Kotlin¶

You can model the methods and callables that control data flow in any framework or library. This is especially useful for custom frameworks or niche libraries, that are not supported by the standard CodeQL libraries.

Beta Notice - Unstable API

Library customization using data extensions is currently in beta and subject to change.

Breaking changes to this format may occur while in beta.

About this article¶

This article contains reference material about how to define custom models for sources, sinks and flow summaries for Java dependencies in data extension files.

The best way to create your own models is using the CodeQL model editor in the CodeQL extension for Visual Studio Code. The model editor automatically guides you through the process of defining models, displaying the properties you need to define and the options available. You can save the resulting models as data extension files in CodeQL model packs and use them without worrying about the syntax.

For more information, see Using the CodeQL model editor in the GitHub documentation.

About data extensions¶

You can customize analysis by defining models (summaries, sinks, and sources) of your code’s dependencies in data extension files. Each model defines the behavior of one or more elements of your library or framework, such as methods and callables. When you run dataflow analysis, these models expand the potential sources and sinks tracked by dataflow analysis and improve the precision of results.

Most of the security queries search for paths from a source of untrusted input to a sink that represents a vulnerability. This is known as taint tracking. Each source is a starting point for dataflow analysis to track tainted data and each sink is an end point.

Taint tracking queries also need to know how data can flow through elements that are not included in the source code. These are modeled as summaries. A summary model enables queries to synthesize the flow behavior through elements in dependency code that is not stored in your repository.

Syntax used to define an element in an extension file¶

Each model of an element is defined using a data extension where each tuple constitutes a model. A data extension file to extend the standard Java queries included with CodeQL is a YAML file with the form:

extensions:
  - addsTo:
      pack: codeql/java-all
      extensible: <name of extensible predicate>
    data:
      - <tuple1>
      - <tuple2>
      - ...

Each YAML file may contain one or more top-level extensions.

addsTo defines the CodeQL pack name and extensible predicate that the extension is injected into.
data defines one or more rows of tuples that are injected as values into the extensible predicate. The number of columns and their types must match the definition of the extensible predicate.

Data extensions use union semantics, which means that the tuples of all extensions for a single extensible predicate are combined, duplicates are removed, and all of the remaining tuples are queryable by referencing the extensible predicate.

Extensible predicates used to create custom models in Java and Kotlin¶

The CodeQL library for Java and Kotlin analysis exposes the following extensible predicates:

sourceModel(package, type, subtypes, name, signature, ext, output, kind, provenance). This is used to model sources of potentially tainted data. The kind of the sources defined using this predicate determine which threat model they are associated with. Different threat models can be used to customize the sources used in an analysis. For more information, see “Threat models.”
sinkModel(package, type, subtypes, name, signature, ext, input, kind, provenance). This is used to model sinks where tainted data maybe used in a way that makes the code vulnerable.
summaryModel(package, type, subtypes, name, signature, ext, input, output, kind, provenance). This is used to model flow through elements.
neutralModel(package, type, name, signature, kind, provenance). This is similar to a summary model but used to model the flow of values that have only a minor impact on the dataflow analysis. Manual neutral models (those with a provenance such as manual or ai-manual) override generated summary models (those with a provenance such as df-generated) so that the summary will be ignored. Other than that, neutral models have a slight impact on the dataflow dispatch logic, which is out of scope for this documentation.

The extensible predicates are populated using the models defined in data extension files.

Examples of custom model definitions¶

The examples in this section are taken from the standard CodeQL Java query pack published by GitHub. They demonstrate how to add tuples to extend extensible predicates that are used by the standard queries.

Example: Taint sink in the `java.sql` package¶

This example shows how the Java query pack models the argument of the execute method as a SQL injection sink. This is the execute method in the Statement class, which is located in the java.sql package.

public static void taintsink(Connection conn, String query) throws SQLException {
    Statement stmt = conn.createStatement();
    stmt.execute(query); // The argument to this method is a SQL injection sink.
}

We need to add a tuple to the sinkModel(package, type, subtypes, name, signature, ext, input, kind, provenance) extensible predicate by updating a data extension file.

extensions:
  - addsTo:
      pack: codeql/java-all
      extensible: sinkModel
    data:
      - ["java.sql", "Statement", True, "execute", "(String)", "", "Argument[0]", "sql-injection", "manual"]

Since we want to add a new sink, we need to add a tuple to the sinkModel extensible predicate. The first five values identify the callable (in this case a method) to be modeled as a sink.

The first value java.sql is the package name.
The second value Statement is the name of the class (type) that contains the method.
The third value True is a flag that indicates whether or not the sink also applies to all overrides of the method.
The fourth value execute is the method name.
The fifth value (String) is the method input type signature.

The sixth value should be left empty and is out of scope for this documentation. The remaining values are used to define the access path, the kind, and the provenance (origin) of the sink.

The seventh value Argument[0] is the access path to the first argument passed to the method, which means that this is the location of the sink.
The eighth value sql-injection is the kind of the sink. The sink kind is used to define the queries where the sink is in scope. In this case - the SQL injection queries.
The ninth value manual is the provenance of the sink, which is used to identify the origin of the sink.

Example: Taint source from the `java.net` package¶

This example shows how the Java query pack models the return value from the getInputStream method as a remote source. This is the getInputStream method in the Socket class, which is located in the java.net package.

public static void tainted(Socket socket) throws IOException {
    InputStream stream = socket.getInputStream(); // The return value of this method is a remote source of taint.
    ...
}

We need to add a tuple to the sourceModel(package, type, subtypes, name, signature, ext, output, kind, provenance) extensible predicate by updating a data extension file.

extensions:
  - addsTo:
      pack: codeql/java-all
      extensible: sourceModel
    data:
      - ["java.net", "Socket", False, "getInputStream", "()", "", "ReturnValue", "remote", "manual"]

Since we are adding a new source, we need to add a tuple to the sourceModel extensible predicate. The first five values identify the callable (in this case a method) to be modeled as a source.

The first value java.net is the package name.
The second value Socket is the name of the class (type) that contains the source.
The third value False is a flag that indicates whether or not the source also applies to all overrides of the method.
The fourth value getInputStream is the method name.
The fifth value () is the method input type signature.

The sixth value should be left empty and is out of scope for this documentation. The remaining values are used to define the access path, the kind, and the provenance (origin) of the source.

The seventh value ReturnValue is the access path to the return of the method, which means that it is the return value that should be considered a source of tainted input.
The eighth value remote is the kind of the source. The source kind is used to define the threat model where the source is in scope. remote applies to many of the security related queries as it means a remote source of untrusted data. As an example the SQL injection query uses remote sources. For more information, see “Threat models.”
The ninth value manual is the provenance of the source, which is used to identify the origin of the source.

Example: Add flow through the `concat` method¶

This example shows how the Java query pack models flow through a method for a simple case. This pattern covers many of the cases where we need to summarize flow through a method that is stored in a library or framework outside the repository.

public static void taintflow(String s1, String s2) {
    String t = s1.concat(s2); // There is taint flow from s1 and s2 to t.
    ...
}

We need to add tuples to the summaryModel(package, type, subtypes, name, signature, ext, input, output, kind, provenance) extensible predicate by updating a data extension file:

extensions:
  - addsTo:
      pack: codeql/java-all
      extensible: summaryModel
    data:
      - ["java.lang", "String", False, "concat", "(String)", "", "Argument[this]", "ReturnValue", "taint", "manual"]
      - ["java.lang", "String", False, "concat", "(String)", "", "Argument[0]", "ReturnValue", "taint", "manual"]

Since we are adding flow through a method, we need to add tuples to the summaryModel extensible predicate. Each tuple defines flow from one argument to the return value. The first row defines flow from the qualifier (s1 in the example) to the return value (t in the example) and the second row defines flow from the first argument (s2 in the example) to the return value (t in the example).

The first five values identify the callable (in this case a method) to be modeled as a summary. These are the same for both of the rows above as we are adding two summaries for the same method.

The first value java.lang is the package name.
The second value String is the class (type) name.
The third value False is a flag that indicates whether or not the summary also applies to all overrides of the method.
The fourth value concat is the method name.
The fifth value (String) is the method input type signature.

The sixth value should be left empty and is out of scope for this documentation. The remaining values are used to define the access path, the kind, and the provenance (origin) of the summary.

The seventh value is the access path to the input (where data flows from). Argument[this] is the access path to the qualifier (s1 in the example) and Argument[0] is the access path to the first argument (s2 in the example).
The eighth value ReturnValue is the access path to the output (where data flows to), in this case ReturnValue, which means that the input flows to the return value.
The ninth value taint is the kind of the flow. taint means that taint is propagated through the call.
The tenth value manual is the provenance of the summary, which is used to identify the origin of the summary.

Example: Add flow through the `map` method¶

This example shows how the Java query pack models a more complex flow through a method. Here we model flow through higher order methods and collection types.

public static void taintflow(Stream<String> s) {
  Stream<String> l = s.map(e -> e.concat("\n"));
  ...
}

We need to add tuples to the summaryModel(package, type, subtypes, name, signature, ext, input, output, kind, provenance) extensible predicate by updating a data extension file:

extensions:
  - addsTo:
      pack: codeql/java-all
      extensible: summaryModel
    data:
      - ["java.util.stream", "Stream", True, "map", "(Function)", "", "Argument[this].Element", "Argument[0].Parameter[0]", "value", "manual"]
      - ["java.util.stream", "Stream", True, "map", "(Function)", "", "Argument[0].ReturnValue", "ReturnValue.Element", "value", "manual"]

Since we are adding flow through a method, we need to add tuples to the summaryModel extensible predicate. Each tuple defines part of the flow that comprises the total flow through the map method. The first five values identify the callable (in this case a method) to be modeled as a summary. These are the same for both of the rows above as we are adding two summaries for the same method.

The first value java.util.stream is the package name.
The second value Stream is the class (type) name.
The third value True is a flag that indicates whether or not the summary also applies to all overrides of the method.
The fourth value map is the method name.
The fifth value Function is the method input type signature.

The sixth value should be left empty and is out of scope for this documentation. The remaining values are used to define the access path, the kind, and the provenance (origin) of the summary definition.

The seventh value is the access path to the input (where data flows from).
The eighth value is the access path to the output (where data flows to).

For the first row:

The seventh value is Argument[this].Element, which is the access path to the elements of the qualifier (the elements of the stream s in the example).
The eight value is Argument[0].Parameter[0], which is the access path to the first parameter of the Function argument of map (the lambda parameter e in the example).

For the second row:

The seventh value is Argument[0].ReturnValue, which is the access path to the return value of the Function argument of map (the return value of the lambda in the example).
The eighth value is ReturnValue.Element, which is the access path to the elements of the return value of map (the elements of the stream l in the example).

For the remaining values for both rows:

The ninth value value is the kind of the flow. value means that the value is preserved.
The tenth value manual is the provenance of the summary, which is used to identify the origin of the summary.

That is, the first row specifies that values can flow from the elements of the qualifier stream into the first argument of the function provided to map. The second row specifies that values can flow from the return value of the function to the elements of the stream returned from map.

Example: Add a `neutral` method¶

This example shows how the Java query pack models the now method as being neutral with respect to flow. A neutral model is used to define that there is no flow through a method.

public static void taintflow() {
    Instant t = Instant.now(); // There is no flow from now to t.
    ...
}

We need to add a tuple to the neutralModel(package, type, name, signature, kind, provenance) extensible predicate by updating a data extension file.

extensions:
- addsTo:
    pack: codeql/java-all
    extensible: neutralModel
  data:
    - ["java.time", "Instant", "now", "()", "summary", "manual"]

Since we are adding a neutral model, we need to add tuples to the neutralModel extensible predicate. The first four values identify the callable (in this case a method) to be modeled as a neutral, the fifth value is the kind, and the sixth value is the provenance (origin) of the neutral.

The first value java.time is the package name.
The second value Instant is the class (type) name.
The third value now is the method name.
The fourth value () is the method input type signature.
The fifth value summary is the kind of the neutral.
The sixth value manual is the provenance of the neutral.

Threat models¶

Note

Threat models are currently in beta and subject to change. During the beta, threat models are supported only by Java, C#, Python and JavaScript/TypeScript analysis.

A threat model is a named class of dataflow sources that can be enabled or disabled independently. Threat models allow you to control the set of dataflow sources that you want to consider unsafe. For example, one codebase may only consider remote HTTP requests to be tainted, whereas another may also consider data from local files to be unsafe. You can use threat models to ensure that the relevant taint sources are used in a CodeQL analysis.

The kind property of the sourceModel determines which threat model a source is associated with. There are two main categories:

remote which represents requests and responses from the network.
local which represents data from local files (file), command-line arguments (commandargs), database reads (database), environment variables(environment), standard input (stdin) and Windows registry values (“windows-registry”). Currently, Windows registry values are used by C# only.

Note that subcategories can be turned included or excluded separately, so you can specify local without database, or just commandargs and environment without the rest of local.

The less commonly used categories are:

android which represents reads from external files in Android (android-external-storage-dir) and parameter of an entry-point method declared in a ContentProvider class (contentprovider). Currently only used by Java/Kotlin.
database-access-result which represents a database access. Currently only used by JavaScript.
file-write which represents opening a file in write mode. Currently only used in C#.
reverse-dns which represents reverse DNS lookups. Currently only used in Java.
view-component-input which represents inputs to a React, Vue, or Angular component (also known as “props”). Currently only used by JavaScript/TypeScript.

When running a CodeQL analysis, the remote threat model is included by default. You can optionally include other threat models as appropriate when using the CodeQL CLI and in GitHub code scanning. For more information, see Analyzing your code with CodeQL queries and Customizing your advanced setup for code scanning.

Customizing library models for Java and Kotlin¶

About this article¶

About data extensions¶

Syntax used to define an element in an extension file¶

Publish data extension files in a CodeQL model pack to share¶

Extensible predicates used to create custom models in Java and Kotlin¶

Examples of custom model definitions¶

Example: Taint sink in the java.sql package¶

Example: Taint source from the java.net package¶

Example: Add flow through the concat method¶

Example: Add flow through the map method¶

Example: Add a neutral method¶