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CVE-2026-1462 high CVSS 7.8

Unsafe Deserialization in keras (CVE-2026-1462)

Summary

Vulnerability in keras (CVE-2026-1462). Successful exploitation can lead to full system takeover. Exploitable via TFSMLayer. Mitigation: upgrade to 3.13.2 or later.

Original description

The description as published by the source.

A vulnerability in the TFSMLayer class of the keras package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of .keras models, even when safe_mode=True. This bypasses the security guarantees of safe_mode and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file paths, and the lack of validation in the from_config() method.

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-2026-1462 has been found in keras.
Attackers can target a specific entry point like TFSMLayer over the network to misuse the product.
Successful exploitation can lead to full system takeover. CVSS score: 7.8/10.
What to do: upgrade keras to 3.13.2 or later.
If unsure, ask your IT team or search "keras CVE-2026-1462" on the vendor's site.

CVE-2026-1462 (keras) — CWE-502 / CVSS v3 7.8
Attack vector: local / unauthenticated
Attack surface: TFSMLayer / keras / safe_mode
Patched: 3.13.2 — 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.

❓ What is the problem

Unsafe deserialization (CWE-502) exists in keras. Attackers reach the vulnerable code path via TFSMLayer without authentication.

📍 Affected scope

Check the vendor advisory for the affected versions of keras. Attack surface: TFSMLayer / keras / safe_mode.

🔥 Severity

Severity: High (CVSS 7.8/10). Successful exploitation can lead to full system takeover.

🔧 How to fix

Update to 3.13.2.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'keras' . 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

  1. 1
    Identify exposure identify 
    grep -r 'keras' . | 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 keras を grep し、稼働しているサービス・バージョンを把握する。

  2. 2
    Apply patch patch 
    Upgrade keras to 3.13.2

    ステージング環境で 3.13.2 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。

  3. 3
    Post-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

PyPI keras
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.13.2"}]}]

Fix status by distribution

Fixed packages published by each distribution for this CVE

References

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