CVE-2021-29605 is a medium-severity (CVSS 5.5) CWE-190 vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.
Integer overflow in TFLite memory allocation
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
CVE-2021-29605 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.
Where this sits among everything scored
Of 385,987 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.
Real-World Exposure
tensorflow🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu+4 moreReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Impact
The TFLite code for allocating TFLiteIntArrays is vulnerable to an integer overflow issue:
int TfLiteIntArrayGetSizeInBytes(int size) {
static TfLiteIntArray dummy;
return sizeof(dummy) + sizeof(dummy.data[0]) * size;
}
An attacker can craft a model such that the size multiplier is so large that the return value overflows the int datatype and becomes negative. In turn, this results in invalid value being given to malloc:
TfLiteIntArray* TfLiteIntArrayCreate(int size) {
TfLiteIntArray* ret = (TfLiteIntArray*)malloc(TfLiteIntArrayGetSizeInBytes(size));
ret->size = size;
return ret;
}
In this case, ret->size would dereference an invalid pointer.
Patches
We have patched the issue in GitHub commit 7c8cc4ec69cd348e44ad6a2699057ca88faad3e5.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
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
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | tensorflow | all versions | 2.1.4pip install --upgrade 'tensorflow==2.1.4' |
| 🐍PyPI | tensorflow | ≥ 2.2.0&&< 2.2.3 | 2.2.3pip install --upgrade 'tensorflow==2.2.3' |
| 🐍PyPI | tensorflow | ≥ 2.3.0&&< 2.3.3 | 2.3.3pip install --upgrade 'tensorflow==2.3.3' |
| 🐍PyPI | tensorflow | ≥ 2.4.0&&< 2.4.2 | 2.4.2pip install --upgrade 'tensorflow==2.4.2' |
| 🐍PyPI | tensorflow-cpu | all versions | 2.1.4pip install --upgrade 'tensorflow-cpu==2.1.4' |
| 🐍PyPI | tensorflow-cpu | ≥ 2.2.0&&< 2.2.3 | 2.2.3pip install --upgrade 'tensorflow-cpu==2.2.3' |
Affected Products
tensorflowgoogleResearch use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update tensorflow to 2.1.4 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2021-29605 is resolved across your whole dependency graph.
Workarounds
Stop feeding it untrusted input: reject or quarantine files and payloads from unverified sources until you can upgrade, restrict accepted formats to the ones you actually need, and run the parsing or decoding step in a least-privileged sandbox or short-lived worker so a crash or corrupted read cannot reach the rest of the process.
Frequently Asked Questions
Is CVE-2021-29605 in your dependencies?
Find it across PyPI, including transitive dependencies.