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JS: Update flow label tutorial

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docs/codeql/codeql-language-guides/using-flow-labels-for-precise-data-flow-analysis.rst
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@@ -1,9 +1,9 @@
.. _using-flow-labels-for-precise-data-flow-analysis:
Using flow labels for precise data flow analysis
Using flow state for precise data flow analysis
================================================
You can associate flow labels with each value tracked by the flow analysis to determine whether the flow contains potential vulnerabilities.
You can associate a flow state with each value tracked by the flow analysis to determine whether the flow contains potential vulnerabilities.
Overview
--------
@@ -16,9 +16,9 @@ program, and associates a flag with every data value telling us whether it might
source node.
In some cases, you may want to track more detailed information about data values. This can be done
by associating flow labels with data values, as shown in this tutorial. We will first discuss the
general idea behind flow labels and then show how to use them in practice. Finally, we will give an
overview of the API involved and provide some pointers to standard queries that use flow labels.
by associating flow states with data values, as shown in this tutorial. We will first discuss the
general idea behind flow states and then show how to use them in practice. Finally, we will give an
overview of the API involved and provide some pointers to standard queries that use flow states.
Limitations of basic data-flow analysis
---------------------------------------
@@ -47,22 +47,21 @@ contain ``..`` components. Untrusted user input has both bits set initially, ind
off individual bits, and if a value that has at least one bit set is interpreted as a path, a
potential vulnerability is flagged.
Using flow labels
Using flow states
-----------------
You can handle these cases and others like them by associating a set of `flow labels` (sometimes
also referred to as `taint kinds`) with each value being tracked by the analysis. Value-preserving
You can handle these cases and others like them by associating a set of `flow states` (sometimes
also referred to as `flow labels` or `taint kinds`) with each value being tracked by the analysis. Value-preserving
data-flow steps (such as flow steps from writes to a variable to its reads) preserve the set of flow
labels, but other steps may add or remove flow labels. Sanitizers, in particular, are simply flow
steps that remove some or all flow labels. The initial set of flow labels for a value is determined
states, but other steps may add or remove flow states. The initial set of flow states for a value is determined
by the source node that gives rise to it. Similarly, sink nodes can specify that an incoming value
needs to have a certain flow label (or one of a set of flow labels) in order for the flow to be
needs to have a certain flow state (or one of a set of flow states) in order for the flow to be
flagged as a potential vulnerability.
Example
-------
As an example of using flow labels, we will show how to write a query that flags property accesses
As an example of using flow state, we will show how to write a query that flags property accesses
on JSON values that come from user-controlled input where we have not checked whether the value is
``null``, so that the property access may cause a runtime exception.
@@ -88,8 +87,8 @@ This code, on the other hand, should not be flagged:
}
}
We will first try to write a query to find this kind of problem without flow labels, and use the
difficulties we encounter as a motivation for bringing flow labels into play, which will make the
We will first try to write a query to find this kind of problem without flow state, and use the
difficulties we encounter as a motivation for bringing flow state into play, which will make the
query much easier to implement.
To get started, let's write a query that simply flags any flow from ``JSON.parse`` into the base of
@@ -99,24 +98,24 @@ a property access:
import javascript
class JsonTrackingConfig extends DataFlow::Configuration {
JsonTrackingConfig() { this = "JsonTrackingConfig" }
override predicate isSource(DataFlow::Node nd) {
module JsonTrackingConfig implements DataFlow::ConfigSig {
predicate isSource(DataFlow::Node nd) {
exists(JsonParserCall jpc |
nd = jpc.getOutput()
)
}
override predicate isSink(DataFlow::Node nd) {
predicate isSink(DataFlow::Node nd) {
exists(DataFlow::PropRef pr |
nd = pr.getBase()
)
}
}
from JsonTrackingConfig cfg, DataFlow::Node source, DataFlow::Node sink
where cfg.hasFlow(source, sink)
module JsonTrackingFlow = DataFlow::Global<JsonTrackingConfig>;
from DataFlow::Node source, DataFlow::Node sink
where JsonTrackingFlow::flow(source, sink)
select sink, "Property access on JSON value originating $@.", source, "here"
Note that we use the ``JsonParserCall`` class from the standard library to model various JSON
@@ -139,29 +138,29 @@ is a barrier guard blocking flow through the use of ``data`` on the right-hand s
At this point we know that ``data`` has evaluated to a truthy value, so it cannot be ``null``
anymore.
Implementing this additional condition is easy. We implement a subclass of ``DataFlow::BarrierGuardNode``:
Implementing this additional condition is easy. We implement a class with a predicate called ``blocksExpr``:
.. code-block:: ql
class TruthinessCheck extends DataFlow::BarrierGuardNode, DataFlow::ValueNode {
class TruthinessCheck extends DataFlow::Node, DataFlow::ValueNode {
SsaVariable v;
TruthinessCheck() {
astNode = v.getAUse()
}
override predicate blocks(boolean outcome, Expr e) {
predicate blocksExpr(boolean outcome, Expr e) {
outcome = true and
e = astNode
}
}
and then use it to override predicate ``isBarrierGuard`` in our configuration class:
and then use it to implement the predicate ``isBarrier`` in our configuration module:
.. code-block:: ql
override predicate isBarrierGuard(DataFlow::BarrierGuardNode guard) {
guard instanceof TruthinessCheck
predicate isBarrier(DataFlow::Node node) {
node = DataFlow::MakeBarrierGuard<TruthinessCheck>::getABarrierNode()
}
With this change, we now flag the problematic case and don't flag the unproblematic case above.
@@ -182,11 +181,11 @@ checked for null-guardedness:
}
}
We could try to remedy the situation by overriding ``isAdditionalFlowStep`` in our configuration class to track values through property reads:
We could try to remedy the situation by adding ``isAdditionalFlowStep`` in our configuration module to track values through property reads:
.. code-block:: ql
override predicate isAdditionalFlowStep(DataFlow::Node pred, DataFlow::Node succ) {
predicate isAdditionalFlowStep(DataFlow::Node pred, DataFlow::Node succ) {
succ.(DataFlow::PropRead).getBase() = pred
}
@@ -199,79 +198,86 @@ altogether, it should simply record the fact that ``root`` itself is known to be
Any property read from ``root``, on the other hand, may well be null and needs to be checked
separately.
We can achieve this by introducing two different flow labels, ``json`` and ``maybe-null``. The former
We can achieve this by introducing two different flow states, ``json`` and ``maybe-null``. The former
means that the value we are dealing with comes from a JSON object, the latter that it may be
``null``. The result of any call to ``JSON.parse`` has both labels. A property read from a value
with label ``json`` also has both labels. Checking truthiness removes the ``maybe-null`` label.
Accessing a property on a value that has the ``maybe-null`` label should be flagged.
``null``. The result of any call to ``JSON.parse`` has both states. A property read from a value
with state ``json`` also results in a value with both states. Checking truthiness removes the ``maybe-null`` state.
Accessing a property on a value that has the ``maybe-null`` state should be flagged.
To implement this, we start by defining two new subclasses of the class ``DataFlow::FlowLabel``:
To implement this, we first change the signature of our configuration module to ``DataFlow::StateConfigSig``, and
replace ``DataFlow::Global<...>`` with ``DataFlow::GlobalWithState<...>``:
.. code-block:: ql
class JsonLabel extends DataFlow::FlowLabel {
JsonLabel() {
this = "json"
}
module JsonTrackingConfig implements DataFlow::StateConfigSig {
/* ... */
}
class MaybeNullLabel extends DataFlow::FlowLabel {
MaybeNullLabel() {
this = "maybe-null"
}
}
module JsonTrackingFlow = DataFlow::GlobalWithState<JsonTrackingConfig>;
Then we extend our ``isSource`` predicate from above to track flow labels by overriding the two-argument version instead of the one-argument version:
We then add a class called ``FlowState`` which has one value for each flow state:
.. code-block:: ql
override predicate isSource(DataFlow::Node nd, DataFlow::FlowLabel lbl) {
module JsonTrackingConfig implements DataFlow::StateConfigSig {
class FlowState extends string {
FlowState() {
this = ["json", "maybe-null"]
}
}
/* ... */
}
Then we extend our ``isSource`` predicate with an additional parameter to specify the flow state:
.. code-block:: ql
predicate isSource(DataFlow::Node nd, FlowState state) {
exists(JsonParserCall jpc |
nd = jpc.getOutput() and
(lbl instanceof JsonLabel or lbl instanceof MaybeNullLabel)
state = ["json", "maybe-null"] // start in either state
)
}
Similarly, we make ``isSink`` flow-label aware and require the base of the property read to have the ``maybe-null`` label:
Similarly, we update ``isSink`` and require the base of the property read to have the ``maybe-null`` state:
.. code-block:: ql
override predicate isSink(DataFlow::Node nd, DataFlow::FlowLabel lbl) {
predicate isSink(DataFlow::Node nd, FlowState state) {
exists(DataFlow::PropRef pr |
nd = pr.getBase() and
lbl instanceof MaybeNullLabel
state = "maybe-null"
)
}
Our overriding definition of ``isAdditionalFlowStep`` now needs to specify two flow labels, a
predecessor label ``predlbl`` and a successor label ``succlbl``. In addition to specifying flow from
the predecessor node ``pred`` to the successor node ``succ``, it requires that ``pred`` has label
``predlbl``, and adds label ``succlbl`` to ``succ``. In our case, we use this to add both the
``json`` label and the ``maybe-null`` label to any property read from a value labeled with ``json``
(no matter whether it has the ``maybe-null`` label):
Our definition of ``isAdditionalFlowStep`` now needs to specify two flow state, a
predecessor state ``predState`` and a successor state ``succState``. In addition to specifying flow from
the predecessor node ``pred`` to the successor node ``succ``, it requires that ``pred`` has state
``state1``, and adds state ``succState`` to ``succ``. In our case, we use this to add both the
``json`` state and the ``maybe-null`` state to any property read from a value in the ``json`` state
(no matter whether it has the ``maybe-null`` state):
.. code-block:: ql
override predicate isAdditionalFlowStep(DataFlow::Node pred, DataFlow::Node succ,
DataFlow::FlowLabel predlbl, DataFlow::FlowLabel succlbl) {
predicate isAdditionalFlowStep(DataFlow::Node pred, FlowState predState,
DataFlow::Node succ, FlowState succState) {
succ.(DataFlow::PropRead).getBase() = pred and
predlbl instanceof JsonLabel and
(succlbl instanceof JsonLabel or succlbl instanceof MaybeNullLabel)
predState = "json" and
succState = ["json", "maybe-null"]
}
Finally, we turn ``TruthinessCheck`` from a ``BarrierGuardNode`` into a ``LabeledBarrierGuardNode``,
specifying that it only removes the ``maybe-null`` label (but not the ``json`` label) from the
sanitized value:
Finally, we add an additional parameter to the ``isBarrier`` predicate to specify the flow state
to block at the ``TruthinessCheck`` barrier.
.. code-block:: ql
class TruthinessCheck extends DataFlow::LabeledBarrierGuardNode, DataFlow::ValueNode {
...
module JsonTrackingConfig implements DataFlow::StateConfigSig {
/* ... */
override predicate blocks(boolean outcome, Expr e, DataFlow::FlowLabel lbl) {
outcome = true and
e = astNode and
lbl instanceof MaybeNullLabel
predicate isBarrier(DataFlow::Node node, FlowState state) {
node = DataFlow::MakeBarrierGuard<TruthinessCheck>::getABarrierNode() and
state = "maybe-null"
}
}
@@ -283,66 +289,60 @@ step by step in the UI:
/** @kind path-problem */
import javascript
import DataFlow::PathGraph
class JsonLabel extends DataFlow::FlowLabel {
JsonLabel() {
this = "json"
}
}
class MaybeNullLabel extends DataFlow::FlowLabel {
MaybeNullLabel() {
this = "maybe-null"
}
}
class TruthinessCheck extends DataFlow::LabeledBarrierGuardNode, DataFlow::ValueNode {
class TruthinessCheck extends DataFlow::Node, DataFlow::ValueNode {
SsaVariable v;
TruthinessCheck() {
astNode = v.getAUse()
}
override predicate blocks(boolean outcome, Expr e, DataFlow::FlowLabel lbl) {
predicate blocksExpr(boolean outcome, Expr e, JsonTrackingConfig::FlowState state) {
outcome = true and
e = astNode and
lbl instanceof MaybeNullLabel
state = "maybe-null"
}
}
class JsonTrackingConfig extends DataFlow::Configuration {
JsonTrackingConfig() { this = "JsonTrackingConfig" }
module JsonTrackingConfig implements DataFlow::StateConfigSig {
class FlowState extends string {
FlowState() {
this = ["json", "maybe-null"]
}
}
override predicate isSource(DataFlow::Node nd, DataFlow::FlowLabel lbl) {
predicate isSource(DataFlow::Node nd, FlowState state) {
exists(JsonParserCall jpc |
nd = jpc.getOutput() and
(lbl instanceof JsonLabel or lbl instanceof MaybeNullLabel)
state = ["json", "maybe-null"] // start in either state
)
}
override predicate isSink(DataFlow::Node nd, DataFlow::FlowLabel lbl) {
predicate isSink(DataFlow::Node nd, FlowState state) {
exists(DataFlow::PropRef pr |
nd = pr.getBase() and
lbl instanceof MaybeNullLabel
state = "maybe-null"
)
}
override predicate isAdditionalFlowStep(DataFlow::Node pred, DataFlow::Node succ,
DataFlow::FlowLabel predlbl, DataFlow::FlowLabel succlbl) {
predicate isAdditionalFlowStep(DataFlow::Node pred, FlowState predState,
DataFlow::Node succ, FlowState succState) {
succ.(DataFlow::PropRead).getBase() = pred and
predlbl instanceof JsonLabel and
(succlbl instanceof JsonLabel or succlbl instanceof MaybeNullLabel)
predState = "json" and
succState = ["json", "maybe-null"]
}
override predicate isBarrierGuard(DataFlow::BarrierGuardNode guard) {
guard instanceof TruthinessCheck
predicate isBarrier(DataFlow::Node node, FlowState state) {
node = DataFlow::MakeBarrierGuard<TruthinessCheck>::getABarrierNode() and
state = "maybe-null"
}
}
from JsonTrackingConfig cfg, DataFlow::PathNode source, DataFlow::PathNode sink
where cfg.hasFlowPath(source, sink)
select sink, source, sink, "Property access on JSON value originating $@.", source, "here"
module JsonTrackingFlow = DataFlow::GlobalWithState<JsonTrackingConfig>;
from DataFlow::Node source, DataFlow::Node sink
where JsonTrackingFlow::flow(source, sink)
select sink, "Property access on JSON value originating $@.", source, "here"
We ran this query on the https://github.com/finos/plexus-interop repository. Many of the
results were false positives since the query does not currently model many ways in which we can check
@@ -354,52 +354,30 @@ this tutorial.
API
---
Plain data-flow configurations implicitly use a single flow label "data", which indicates that a
data value originated from a source. You can use the predicate ``DataFlow::FlowLabel::data()``,
which returns this flow label, as a symbolic name for it.
Flow state can be used in modules implementing the ``DataFlow::StateConfigSig`` signature. Compared to a ``DataFlow::ConfigSig`` the main differences are:
Taint-tracking configurations add a second flow label "taint" (``DataFlow::FlowLabel::taint()``),
which is similar to "data", but includes values that have passed through non-value preserving steps
such as string operations.
- The module must be passed to ``DataFlow::GlobalWithState<...>`` or ``TaintTracking::GlobalWithState<...>``.
instead of ``DataFlow::Global<...>`` or ``TaintTracking::Global<...>``.
- The module must contain a type named ``FlowState``.
- ``isSource`` expects an additional parameter specifying the flow state.
- ``isSink`` optionally can take an additional parameter specifying the flow state.
If omitted, the sinks are in effect for all flow states.
- ``isAdditionalFlowStep`` optionally can take two additional parameters specifying the predecessor and successor flow states.
If omitted, the generated steps apply for any flow state and preserve the current flow state.
- ``isBarrier`` optionally can take an additional parameter specifying the flow state to block.
If omitted, the barriers block all flow states.
Each of the three member predicates ``isSource``, ``isSink`` and
``isAdditionalFlowStep``/``isAdditionalTaintStep`` has one version that uses the default flow
labels, and one version that allows specifying custom flow labels through additional arguments.
For ``isSource``, there is one additional argument specifying which flow label(s) should be
associated with values originating from this source. If multiple flow labels are specified, each
value is associated with `all` of them.
For ``isSink``, the additional argument specifies which flow label(s) a value that flows into this
source may be associated with. If multiple flow labels are specified, then any value that is
associated with `at least one` of them will be considered by the configuration.
For ``isAdditionalFlowStep`` there are two additional arguments ``predlbl`` and ``succlbl``, which
allow flow steps to act as flow label transformers. If a value associated with ``predlbl`` arrives
at the start node of the additional step, it is propagated to the end node and associated with
``succlbl``. Of course, ``predlbl`` and ``succlbl`` may be the same, indicating that the flow step
preserves this label. There can also be multiple values of ``succlbl`` for a single ``predlbl`` or
vice versa.
Note that if you do not restrict ``succlbl`` then it will be allowed to range over all flow labels.
This may cause labels that were previously blocked on a path to reappear, which is not usually what
you want.
The flow label-aware version of ``isBarrier`` is called ``isLabeledBarrier``: unlike ``isBarrier``,
which prevents any flow past the given node, it only blocks flow of values associated with one of
the specified flow labels.
Standard queries using flow labels
Standard queries using flow state
----------------------------------
Some of our standard security queries use flow labels. You can look at their implementation
to get a feeling for how to use flow labels in practice.
Some of our standard security queries use flow state. You can look at their implementation
to get a feeling for how to use flow state in practice.
In particular, both of the examples mentioned in the section on limitations of basic data flow above
are from standard security queries that use flow labels. The `Prototype-polluting merge call
<https://codeql.github.com/codeql-query-help/javascript/js-prototype-pollution/>`_ query uses two flow labels to distinguish completely
are from standard security queries that use flow state. The `Prototype-polluting merge call
<https://codeql.github.com/codeql-query-help/javascript/js-prototype-pollution/>`_ query uses two flow states to distinguish completely
tainted objects from partially tainted objects. The `Uncontrolled data used in path expression
<https://codeql.github.com/codeql-query-help/javascript/js-path-injection/>`_ query uses four flow labels to track whether a user-controlled
<https://codeql.github.com/codeql-query-help/javascript/js-path-injection/>`_ query uses four flow states to track whether a user-controlled
string may be an absolute path and whether it may contain ``..`` components.
Further reading