Vulnerability in Tensorflow (CVE-2020-15198)
Summary
Vulnerability in Tensorflow (CVE-2020-15198). Risk of unauthorized operations or information disclosure. Exploitable via SparseCountSparseOutput.
Original description
The description as published by the source.
In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
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-2020-15198 has been found in Tensorflow.
Attackers can target a specific entry point like SparseCountSparseOutput over the network to misuse the product.
Risk of unauthorized operations or information disclosure.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "Tensorflow CVE-2020-15198" on the vendor's site.
CVE-2020-15198 (Tensorflow)
Attack vector: remote (network-reachable) / unauthenticated / no user interaction
Attack surface: SparseCountSparseOutput / indices / values
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) exists in Tensorflow. Attackers reach the vulnerable code path via SparseCountSparseOutput without authentication.
Check the vendor advisory for the affected versions of Tensorflow. Attack surface: SparseCountSparseOutput / indices / values.
Severity: ?. Risk of unauthorized operations or information disclosure.
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. 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
-
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。 -
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 github.com
- advisory github.com
- advisory github.com
- package github.com
- web nvd.nist.gov
- web github.com
- web github.com
- web github.com