CVE-2020-15212 – This vulnerability in TensorFlow Lite allows at... (How to Fix)

Q: What is the severity of CVE-2020-15212?

CVE-2020-15212 has a CVSS score of 8.1 (HIGH). This vulnerability in TensorFlow Lite allows attackers with access to segment_ids_data to trigger out-of-bounds writes to heap-allocated buffers by inserting negative elements in segment ids. This can cause segmentation faults, memory corruption, or be chained with other vulnerabilities for advanced exploits. Users of TensorFlow Lite before versions 2.2.1 and 2.3.1 are affected.

📋 TL;DR

This vulnerability in TensorFlow Lite allows attackers with access to segment_ids_data to trigger out-of-bounds writes to heap-allocated buffers by inserting negative elements in segment ids. This can cause segmentation faults, memory corruption, or be chained with other vulnerabilities for advanced exploits. Users of TensorFlow Lite before versions 2.2.1 and 2.3.1 are affected.

💻 Affected Systems

Products:

TensorFlow Lite

Versions: All versions before 2.2.1 and 2.3.1

Operating Systems: All operating systems running TensorFlow Lite

Default Config Vulnerable: ⚠️ Yes

Notes: Vulnerability exists in models using segment sum operations. Exploitation requires control over segment_ids_data.

📦 What is this software?

Tensorflow by Google

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Tensorflow by Google

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⚠️ Risk & Real-World Impact

🔴

Worst Case

Memory corruption leading to remote code execution, privilege escalation, or system compromise when chained with other vulnerabilities.

🟠

Likely Case

Segmentation faults causing application crashes, denial of service, or limited memory corruption.

🟢

If Mitigated

No impact if proper input validation or patched versions are used.

🌐 Internet-Facing: MEDIUM - Exploitation requires access to segment_ids_data, which may be exposed through APIs or user inputs in some deployments.

🏢 Internal Only: MEDIUM - Similar risk profile as internet-facing, but attack surface may be limited to authenticated users or internal systems.

🎯 Exploit Status

Public PoC: ✅ No

Weaponized: UNKNOWN

Unauthenticated Exploit: ✅ No

Complexity: MEDIUM

Exploitation requires control over segment_ids_data input. No public exploit code has been disclosed.

🛠️ Fix & Mitigation

✅ Official Fix

Patch Version: TensorFlow 2.2.1 or 2.3.1

Vendor Advisory: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq

Restart Required: Yes

Instructions:

1. Upgrade TensorFlow to version 2.2.1 or 2.3.1. 2. Update all dependencies. 3. Restart affected services. 4. Rebuild any custom models with updated TensorFlow version.

🔧 Temporary Workarounds

Custom Verifier for Static Segment IDs

all

Add input validation to ensure segment ids are all positive when stored statically in models.

Implement custom verifier in model loading code to validate segment_ids_data > 0

Runtime Validation for Dynamic Segment IDs

all

Validate segment ids are positive when generated at runtime between inference steps.

Add validation logic for segment_ids_data > 0 before segment sum operations

🧯 If You Can't Patch

Implement strict input validation for all segment_ids_data inputs
Isolate TensorFlow Lite processes with minimal privileges and memory restrictions

🔍 How to Verify

Check if Vulnerable:

Check TensorFlow version: if using TensorFlow Lite < 2.2.1 or < 2.3.1, you are vulnerable.

Check Version:

python -c "import tensorflow as tf; print(tf.__version__)"

Verify Fix Applied:

Verify TensorFlow version is >= 2.2.1 or >= 2.3.1 and test segment sum operations with negative segment ids.

📡 Detection & Monitoring

Log Indicators:

Segmentation fault errors
Memory access violation logs
Abnormal TensorFlow Lite process termination

Network Indicators:

Unusual API calls to TensorFlow Lite endpoints with segment sum operations

SIEM Query:

source="*tensorflow*" AND ("segmentation fault" OR "memory violation" OR "segment_sum")

📊 Metadata

CVE ID: CVE-2020-15212

CVSS v3 Score: 8.1 (HIGH)

CVSS Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H

CWE: CWE-787

Published: September 25, 2020

Last Updated: November 21, 2024

🔗 References

https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a Patch,Third Party Advisory
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq Exploit,Patch,Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a Patch,Third Party Advisory
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq Exploit,Patch,Third Party Advisory

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🔗 Related Vulnerabilities

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