TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in…
Summary
Vulnerability reported (CVE-2021-29537). Successful exploitation can lead to full system takeover. Exploitable via QuantizedResizeBilinear.
Original description
The description as published by the source.
Impact
An attacker can cause a heap buffer overflow in QuantizedResizeBilinear by passing in invalid thresholds for the quantization:
import tensorflow as tf
images = tf.constant([], shape=[0], dtype=tf.qint32)
size = tf.constant([], shape=[0], dtype=tf.int32)
min = tf.constant([], dtype=tf.float32)
max = tf.constant([], dtype=tf.float32)
tf.raw_ops.QuantizedResizeBilinear(images=images, size=size, min=min, max=max, align_corners=False, half_pixel_centers=False)
This is because the implementation assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly:
const float in_min = context->input(2).flat()(0);
const float in_max = context->input(3).flat()(0);
However, if any of these tensors is empty, then .flat() is an empty buffer and accessing the element at position 0 results in overflow.
Patches
We have patched the issue in GitHub commit f6c40f0c6cbf00d46c7717a26419f2062f2f8694.
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 g…
Source: OSV.dev (Open Source Vulnerabilities) NVD GitHub Advisory OSV
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2021-29537 has been found.
Attackers can target a specific entry point like QuantizedResizeBilinear over the network to misuse the product.
Successful exploitation can lead to full system takeover.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "CVE-2021-29537" on the vendor's site.
CVE-2021-29537
Attack vector: local / no user interaction
Attack surface: QuantizedResizeBilinear
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
A vulnerability (unclassified) has been reported. Attackers reach the vulnerable code path via QuantizedResizeBilinear.
Check the vendor advisory for the affected versions. Attack surface: QuantizedResizeBilinear.
Severity: ?. Successful exploitation can lead to full system takeover.
Update to the patched release per vendor advisory.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Audit SBOM/dependencies to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
-
1Identify exposure identify
Audit SBOM/dependencies for affected components.資産台帳・SBOM・依存マニフェストで影響コンポーネントを特定する。
-
2Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
References
- advisory nvd.nist.gov
- package github.com
- web github.com
- web github.com
- web github.com
- web github.com
- web github.com