Step 10 - Data flow and taint tracking analysis

[github-learning-lab[bot]]

Step 10: Data flow and taint tracking analysis

Great! You made it to the final step!

In step 9 we found expressions in the source code that are likely to have integers supplied from remote input, because they are being processed with invocations of ntoh, ntohll, or ntohs. These can be considered sources of remote input.

In step 6 we found calls to memcpy. These calls can be unsafe when their length arguments are controlled by a remote user. Their length arguments can be considered sinks: they should not receive user-controlled values without further validation.

Combining these pieces of information, we know that code is vulnerable if tainted data flows from a network integer source to a sink in the length argument of a memcpy call.

However, how do we know whether data from a particular source might reach a particular sink? This is known as data flow or taint tracking analysis. Given the number of results (hundreds of memcpy calls and a large number of macro invocations), it would be quite a lot of work to triage all these cases manually.

To make our triaging job easier, we will have CodeQL do this analysis for us.

You will now write a query to track the flow of tainted data from network-controlled integers to the memcpy length argument. As a result you will find 9 real vulnerabilities!

To achieve this, we’ll use the CodeQL taint tracking library. This library allows you to describe sources and sinks, and its predicate hasFlowPath holds true when tainted data from a given source flows to a sink.

[github-learning-lab[bot]]

:keyboard: Activity: Write a taint tracking query

1. Edit the file 10_taint_tracking.ql with the template below. Note the annotation path-problem and the pattern used in the select section. This pattern allows CodeQL to interpret these results as a "path" through the code, and display the path in your IDE.
2. Copy and paste your definition of the NetworkByteSwap class from step 9.
3. Write the isSource predicate. This should recognize an expression in an invocation of ntohl, ntohs or ntohll.
   • You already described these expressions in the NetworkByteSwap class from step 9. Here we need to check that the source corresponds to a value that belongs to this class.
   • To check if a value belongs to CodeQL class, use the <value> instanceof <myclass> construct.
   • Note that the source variable is of type DataFlow::Node, while your NetworkByteSwap class is a subclass of Expr, so we cannot just write source instanceof NetworkByteSwap. (Try this and the compiler will give you an error.) Use auto-completion on source to discover the predicate that lets us view it as an Expr.
4. Write the isSink predicate: The sink should be the size argument of calls to memcpy.
   • Use auto-completion to find the predicate that returns the nth argument of a function call.
   • Use the predicate you discovered when writing isSource to view the sink as an Expr.
5. Run your query. Note that the first run will take a little longer than the previous queries, since data flow analysis is more complex.

Submit your query when you're happy with the results.

Tip: For a complete example, read this article.

/**
 * @kind path-problem
 */

import cpp
import semmle.code.cpp.dataflow.TaintTracking
import DataFlow::PathGraph

class NetworkByteSwap extends Expr {
  // TODO: copy from previous step
}

class Config extends TaintTracking::Configuration {
  Config() { this = "NetworkToMemFuncLength" }

  override predicate isSource(DataFlow::Node source) {
    // TODO
  }
  override predicate isSink(DataFlow::Node sink) {
    // TODO
  }
}

from Config cfg, DataFlow::PathNode source, DataFlow::PathNode sink
where cfg.hasFlowPath(source, sink)
select sink, source, sink, "Network byte swap flows to memcpy"

[github-learning-lab[bot]]

Ooops! The query you submitted in 910fdcc684fa3856f278bf843ef4d940ce2ca31f didn't find the right results. Please take a look at the comment and try again.

To submit a new iteration of your query, you just have to push a new commit to the same branch (main or the PR branch).

[github-learning-lab[bot]]

Congratulations, you have finished the course! You can merge your last outstanding Pull Request if you have one. Don't hesitate to give us feedback; find us at https://securitylab.github.com/get-involved. And recommend this course to your friends if it was useful!