Out-of-Bounds Read in tensorflow (CVE-2020-15265)
Summary
Vulnerability in tensorflow (CVE-2020-15265). Risk of unauthorized operations or information disclosure. Exploitable via axis. Mitigation: upgrade to 2.4.0 or later.
Original description
The description as published by the source.
In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantize_and_dequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, DCHECK-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
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-2020-15265 has been found in tensorflow.
Attackers can target a specific entry point like axis over the network to misuse the product.
Risk of unauthorized operations or information disclosure.
What to do: upgrade tensorflow to 2.4.0 or later.
If unsure, ask your IT team or search "tensorflow CVE-2020-15265" on the vendor's site.
CVE-2020-15265 (tensorflow) — CWE-125
Attack vector: remote (network-reachable) / unauthenticated / no user interaction
Attack surface: axis / tf.quantization.quantize_and_dequantize / DCHECK
Patched: 2.4.0 — apply immediately
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.
Out-of-bounds read (CWE-125) exists in tensorflow. Attackers reach the vulnerable code path via axis without authentication.
Check the vendor advisory for the affected versions of tensorflow. Attack surface: axis / tf.quantization.quantize_and_dequantize / DCHECK.
Severity: ?. Risk of unauthorized operations or information disclosure.
Update to 2.4.0.
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. Run grep -r 'tensorflow' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
grep -r 'tensorflow' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
tensorflowを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade tensorflow to 2.4.0ステージング環境で 2.4.0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
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3Post-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 github.com
- advisory github.com
- advisory github.com
- package github.com
- web nvd.nist.gov
- web github.com
- web github.com
- web github.com