GHSA-h6gw-r52c-724r
NULL Pointer Dereference and Access of Uninitialized Pointer in TensorFlow
- Severity
- 9.3 / 10
- Critical · CVSS 3.1
- Exploit chance (EPSS)
- —
- No score published
- Known exploited
- No
- Not in CISA's catalog
- Fix
- Available
- 3 packages have a fixed version
Description
Impact
The code for boosted trees in TensorFlow is still missing validation. This allows malicious users to read and write outside of bounds of heap allocated data as well as trigger denial of service (via dereferencing nullptrs or via CHECK-failures).
This follows after CVE-2021-41208 where these APIs were still vulnerable to multiple security issues.
Note: Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. Instead, please use the downstream TensorFlow Decision Forests project which is newer and supports more features.
These APIs are now deprecated in TensorFlow 2.8. We will remove TensorFlow's boosted trees APIs in subsequent releases.
Patches
We have patched the known issues in multiple GitHub commits.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
This should allow users to use existing boosted trees APIs for a while until they migrate to TensorFlow Decision Forests, while guaranteeing that known vulnerabilities are fixed.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
These vulnerabilities have been reported by Yu Tian of Qihoo 360 AIVul Team and Faysal Hossain Shezan from University of Virginia. Some of the issues have been discovered internally after a careful audit of the APIs.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| tensorflow | < 2.5.3 |
2.5.3 |
| tensorflow | >= 2.6.0, < 2.6.3 |
2.6.3 |
| tensorflow | >= 2.7.0, < 2.7.1 |
2.7.1 |
| tensorflow-cpu | < 2.5.3 |
2.5.3 |
| tensorflow-cpu | >= 2.6.0, < 2.6.3 |
2.6.3 |
| tensorflow-cpu | >= 2.7.0, < 2.7.1 |
2.7.1 |
| tensorflow-gpu | < 2.5.3 |
2.5.3 |
| tensorflow-gpu | >= 2.6.0, < 2.6.3 |
2.6.3 |
| tensorflow-gpu | >= 2.7.0, < 2.7.1 |
2.7.1 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
tensorflow PyPI → 2.5.3
- pip
pip install --upgrade "tensorflow>=2.5.3"- poetry
poetry add "tensorflow>=2.5.3"- uv
uv add "tensorflow>=2.5.3"
tensorflow-cpu PyPI → 2.5.3
- pip
pip install --upgrade "tensorflow-cpu>=2.5.3"- poetry
poetry add "tensorflow-cpu>=2.5.3"- uv
uv add "tensorflow-cpu>=2.5.3"
tensorflow-gpu PyPI → 2.5.3
- pip
pip install --upgrade "tensorflow-gpu>=2.5.3"- poetry
poetry add "tensorflow-gpu>=2.5.3"- uv
uv add "tensorflow-gpu>=2.5.3"
Severity breakdown
CVSS 3.1 9.3
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
- Attack vector
- Local
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Changed
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Weakness
CWE-476: NULL Pointer Dereference
The product dereferences a pointer that it expects to be valid but is NULL.
How to prevent it
- Implementation: For any pointers that could have been modified or provided from a function that can return NULL, check the pointer for NULL before use. When working with a multithreaded or otherwise asynchronous environment, ensure that proper locking APIs are used to lock before the check, and unlock when it has finished [REF-1484].
- Requirements: Select a programming language that is not susceptible to these issues.
- Implementation: Check the results of all functions that return a value and verify that the value is non-null before acting upon it.
- Architecture and Design: Identify all variables and data stores that receive information from external sources, and apply input validation to make sure that they are only initialized to expected values.
- Implementation: Explicitly initialize all variables and other data stores, either during declaration or just before the first usage.
CWE-824: Access of Uninitialized Pointer
The product accesses or uses a pointer that has not been initialized.
References
Packages
Other links
Timeline
- Published
- Last updated by the source
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-gjh7-xx4r-x345 TensorFlow has segfault in array_ops.upper_bound | High | Also affects tensorflow |
| GHSA-fxgc-95xx-grvq TensorFlow Denial of Service vulnerability | Medium | Also affects tensorflow |
| GHSA-93vr-9q9m-pj8p TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch | High | Also affects tensorflow |
| GHSA-qjqc-vqcf-5qvj TensorFlow vulnerable to seg fault in `tf.raw_ops.Print` | High | Also affects tensorflow |
| GHSA-7jvm-xxmr-v5cw TensorFlow vulnerable to integer overflow in EditDistance | High | Also affects tensorflow |
| GHSA-64jg-wjww-7c5w TensorFlow has Null Pointer Error in TensorArrayConcatV2 | High | Also affects tensorflow |
| GHSA-6hg6-5c2q-7rcr TensorFlow has Heap-buffer-overflow in AvgPoolGrad | High | Also affects tensorflow |
| GHSA-558h-mq8x-7q9g TensorFlow has Null Pointer Error in SparseSparseMaximum | High | Also affects tensorflow |
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