CVE-2020-26269

TensorFlow vulnerable to heap out of bounds read in filesystem glob matching

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Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

The general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories:

if (!fs->Match(child_path, dirs[dir_index])) { ... }

Since dir_index is unconditionaly incremented outside of the lambda function where the vulnerable pattern occurs, this results in an access out of bounds issue under certain scenarios. For example, if /tmp/x is a directory that only contains a single file y, then the following scenario will cause a crash due to the out of bounds read:

>>> tf.io.gfile.glob('/tmp/x/')
Segmentation fault

There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these.

A read operation accesses a memory location beyond the intended buffer boundary. Typical impact: sensitive data disclosure or crash.

CVE-2020-26269 has a CVSS score of 9.1 (High). The vector is network-reachable, no privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (2.4.0); upgrading removes the vulnerable code path.

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We have patched the issue in GitHub commit 8b5b9dc96666a3a5d27fad7179ff215e3b74b67c and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.

1. What is CVE-2020-26269? CVE-2020-26269 is a high-severity out-of-bounds read vulnerability in tensorflow (pip), affecting versions >= 2.4.0rc0, < 2.4.0. It is fixed in 2.4.0. A read operation accesses a memory location beyond the intended buffer boundary.
2. How severe is CVE-2020-26269? CVE-2020-26269 has a CVSS score of 9.1 (High). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
3. Which packages are affected by CVE-2020-26269?
   • tensorflow (pip) (versions >= 2.4.0rc0, < 2.4.0)
   • tensorflow-cpu (pip) (versions >= 2.4.0rc0, < 2.4.0)
   • tensorflow-gpu (pip) (versions >= 2.4.0rc0, < 2.4.0)
4. Is there a fix for CVE-2020-26269? Yes. CVE-2020-26269 is fixed in 2.4.0. Upgrade to this version or later.
5. Is CVE-2020-26269 exploitable, and should I be worried? Whether CVE-2020-26269 is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
6. What actually determines whether CVE-2020-26269 is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
7. How do I fix CVE-2020-26269?
   • Upgrade tensorflow to 2.4.0 or later
   • Upgrade tensorflow-cpu to 2.4.0 or later
   • Upgrade tensorflow-gpu to 2.4.0 or later

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