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Fix docs: "acceptingvalue" -> "acceptingValue"
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docs/codeql/codeql-language-guides/customizing-library-models-for-cpp.rst

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -59,7 +59,7 @@ The CodeQL library for CPP analysis exposes the following extensible predicates:
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- ``sinkModel(namespace, type, subtypes, name, signature, ext, input, kind, provenance)``. This is used to model sinks where tainted data may be used in a way that makes the code vulnerable.
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- ``summaryModel(namespace, type, subtypes, name, signature, ext, input, output, kind, provenance)``. This is used to model flow through elements.
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- ``barrierModel(namespace, type, subtypes, name, signature, ext, output, kind, provenance)``. This is used to model barriers, which are elements that stop the flow of taint.
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- ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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The extensible predicates are populated using the models defined in data extension files.
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@@ -232,7 +232,7 @@ Consider a function called ``is_safe`` which returns ``true`` when the data is c
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mysql_query(user_input); // This is safe.
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}
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We need to add a tuple to the ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)`` extensible predicate by updating a data extension file.
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We need to add a tuple to the ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)`` extensible predicate by updating a data extension file.
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.. code-block:: yaml
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docs/codeql/codeql-language-guides/customizing-library-models-for-csharp.rst

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -59,7 +59,7 @@ The CodeQL library for C# analysis exposes the following extensible predicates:
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- ``sinkModel(namespace, type, subtypes, name, signature, ext, input, kind, provenance)``. This is used to model sinks where tainted data may be used in a way that makes the code vulnerable.
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- ``summaryModel(namespace, type, subtypes, name, signature, ext, input, output, kind, provenance)``. This is used to model flow through elements.
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- ``barrierModel(namespace, type, subtypes, name, signature, ext, output, kind, provenance)``. This is used to model barriers, which are elements that stop the flow of taint.
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- ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``neutralModel(namespace, 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``) can be used to override generated summary models (those with a provenance such as ``df-generated``), so that the summary model will be ignored. Other than that, neutral models have no effect.
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The extensible predicates are populated using the models defined in data extension files.
@@ -365,7 +365,7 @@ When the ``IsAbsoluteUri`` property returns ``false``, the URL is relative and t
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}
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}
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We need to add a tuple to the ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)`` extensible predicate by updating a data extension file.
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We need to add a tuple to the ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)`` extensible predicate by updating a data extension file.
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.. code-block:: yaml
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docs/codeql/codeql-language-guides/customizing-library-models-for-go.rst

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -59,7 +59,7 @@ The CodeQL library for Go analysis exposes the following extensible predicates:
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- ``sinkModel(package, type, subtypes, name, signature, ext, input, kind, provenance)``. This is used to model sinks where tainted data may be used in a way that makes the code vulnerable.
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- ``summaryModel(package, type, subtypes, name, signature, ext, input, output, kind, provenance)``. This is used to model flow through elements.
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- ``barrierModel(package, type, subtypes, name, signature, ext, output, kind, provenance)``. This is used to model barriers, which are elements that stop the flow of taint.
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- ``barrierGuardModel(package, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``barrierGuardModel(package, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``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``) can be used to override generated summary models (those with a provenance such as ``df-generated``), so that the summary model will be ignored. Other than that, neutral models have no effect.
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The extensible predicates are populated using the models defined in data extension files.
@@ -395,7 +395,7 @@ Consider a function called ``IsSafe`` which returns ``true`` when the data is co
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}
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}
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We need to add a tuple to the ``barrierGuardModel(package, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)`` extensible predicate by updating a data extension file.
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We need to add a tuple to the ``barrierGuardModel(package, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)`` extensible predicate by updating a data extension file.
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.. code-block:: yaml
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docs/codeql/codeql-language-guides/customizing-library-models-for-java-and-kotlin.rst

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -64,7 +64,7 @@ The CodeQL library for Java and Kotlin analysis exposes the following extensible
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- ``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.
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- ``summaryModel(package, type, subtypes, name, signature, ext, input, output, kind, provenance)``. This is used to model flow through elements.
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- ``barrierModel(namespace, type, subtypes, name, signature, ext, output, kind, provenance)``. This is used to model barriers, which are elements that stop the flow of taint.
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- ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``barrierGuardModel(namespace, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)``. This is used to model barrier guards, which are elements that can stop the flow of taint depending on a conditional check.
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- ``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.
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The extensible predicates are populated using the models defined in data extension files.
@@ -315,7 +315,7 @@ When the ``isAbsolute`` method returns ``false``, the URI is relative and theref
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}
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}
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We need to add a tuple to the ``barrierGuardModel(package, type, subtypes, name, signature, ext, input, acceptingvalue, kind, provenance)`` extensible predicate by updating a data extension file.
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We need to add a tuple to the ``barrierGuardModel(package, type, subtypes, name, signature, ext, input, acceptingValue, kind, provenance)`` extensible predicate by updating a data extension file.
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.. code-block:: yaml
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