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NVD / CVE Program· CNA GitHub_M

CVE-2020-15213: Denial of service in tensorflow-lite

Noroxi assessment

Priority: Monitor (action score 16/100)

  • The sources we track (CISA KEV, Exploit-DB, Metasploit, Nuclei, GitHub) show no public exploit code or exploitation in the wild.
  • Probability of exploitation in the next 30 days: 0.76% (FIRST EPSS); higher than 55.1% of all records.
  • Anyone who can reach it over the internet can trigger it. No account or password is required. No user action is required. Special conditions such as timing or configuration are required.
  • Fixed version: tensorflow (PyPI) 2.2.1, 2.3.1; tensorflow-cpu (PyPI) 2.2.1, 2.3.1; tensorflow-gpu (PyPI) 2.2.1, 2.3.1.

Low priority for now. Upgrade to tensorflow (PyPI) 2.2.1, 2.3.1; tensorflow-cpu (PyPI) 2.2.1, 2.3.1; tensorflow-gpu (PyPI) 2.2.1, 2.3.1 or later.

Generated automatically from the record's data: CVSS (NVD and CNA), CISA KEV and SSVC, FIRST EPSS, exploit sources, fixed versions. How we calculate it

Primary sources: NVD · CVE.org · FIRST EPSS

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.

MediumCVSS 4.0 · v3.1—No exploit Fix available
Published
Sep 25, 2020
Updated
Jun 16, 2026
EPSS
0.7% · 55th percentile

Report tools

JSON

Action score

16

Monitor

Low priority for now.

CVSS
16 / 40 · 4.0 / 10
CISA KEV
0 / 30 · Not listed
EPSS
0 / 30 · 0.7%

CNA vs NVD score

NVD
4.0
CNA · GitHub_M
4.0
agree

The score given by the assigning authority versus NVD’s independent score. A gap means the severity is contested.

Get told when this record changes

  • Not in KEV: no record of exploitation in the wild
  • No public exploit code on record
  • A fix has been released

If any of these changes, we'll tell you in the daily email digest.

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When you'll hear from us

  • when it enters CISA KEV
  • when exploit code appears or is weaponized
  • when the record is updated (including a fixed version)
  • when EPSS rises 20 points in a week

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Noroxi analysis

What does it mean in your environment?

The assessment above is generated automatically from the record's data; it doesn't know your environment. Our team verifies on your systems whether this vulnerability is actually exploitable and which mitigation is enough.

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Affected systems

Is your version affected?

Pick the product and type the version you run. It's compared with this record's version ranges in your browser; the version isn't sent anywhere.

VendorProduct
googletensorflow

Affected versions

NVD version ranges (for catalog products). Add the product to your stack with a version and matching uses these.

  • google tensorflow2.2.0 and later · before 2.2.1
  • google tensorflow2.3.0 and later · before 2.3.1

Versions reported by the vendor

Affected version ranges reported by the assigning authority (GitHub_M). Independent of NVD's CPE analysis and usually ahead of it.

  • tensorflow tensorflow

    • = 2.2.0, = 2.3.0affected

Package-level exposure

OSV and GitHub Advisory data: ecosystem, package and range. SBOM matching uses this table.

EcosystemPackageAffected rangeFix
PyPItensorflowfrom 2.2.0 · before 2.2.12.2.1
PyPItensorflowfrom 2.3.0 · before 2.3.12.3.1
PyPItensorflow-cpufrom 2.2.0 · before 2.2.12.2.1
PyPItensorflow-cpufrom 2.3.0 · before 2.3.12.3.1
PyPItensorflow-gpufrom 2.2.0 · before 2.2.12.2.1
PyPItensorflow-gpufrom 2.3.0 · before 2.3.12.3.1

Same product

google: all records

Other highest-scoring records for the same primary product.

  • CVE-2023-25668TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
    39Monitor
  • CVE-2023-25664TensorFlow vulnerable to Heap Buffer Overflow in AvgPoolGrad
    39Monitor
  • CVE-2022-41900FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow
    39Monitor

Published before and after this one in the same product

  • ← EarlierCVE-2020-15211Sep 25, 2020 · Out of bounds access in tensorflow-lite
    19Monitor
  • ← EarlierCVE-2020-15212Sep 25, 2020 · Out of bounds access in tensorflow-lite
    34Monitor
  • Later →CVE-2020-15214Sep 25, 2020 · Out of bounds write in tensorflow-lite
    32Monitor

Remediation

Which version to upgrade to

Fix versions compiled from the vendor, package registries and Microsoft. Verify the vendor's note before upgrading.

Product / packageFixed versionSource
PyPI:tensorflow2.2.1Package registry (OSV)
PyPI:tensorflow2.3.1Package registry (OSV)
PyPI:tensorflow-cpu2.2.1Package registry (OSV)
PyPI:tensorflow-cpu2.3.1Package registry (OSV)
PyPI:tensorflow-gpu2.2.1Package registry (OSV)
PyPI:tensorflow-gpu2.3.1Package registry (OSV)

Exploit status

No known public exploit

No public exploit has been observed yet. That doesn't mean you're safe, only that the bar is a little higher.

Research context

For pentesters and researchers: attack profile, score disagreement, timeline, patch commits, credits, variant and chain candidates, bug bounty scope. All derived from existing data; no exploit code.

Timeline

From publication to today: proof of concept, Metasploit module, CISA KEV and fix record. Dates are as reported by the sources.

No dated events beyond publication.

No history yet (it accumulates with the daily EPSS job).

Patch and commit links

Commit, PR and diff links among the references. A starting point for patch-diffing and variant hunting; fixes, not exploits.

Credits

All researchers

Finders, reporters and analysts named in the CNA record. Click a name for that researcher’s other records.

No credits in the CNA record.

Variant candidates

Same product, same weakness class, within 18 months. If the patch missed the root cause, the sibling bug is here.

No nightly-computed relations.

Chain candidates

An authentication bypass and a privilege-requiring bug in the same product, published close together: combined they may become an unauthenticated path.

—

Bug bounty scope

No known public program.

Source: bounty-targets-data (public HackerOne, Bugcrowd, Intigriti, YesWeHack listings).

Technical details

Attack conditions

  • Anyone who can reach it over the internet can trigger it.
  • No account or password is required.
  • No user action is required.
  • Special conditions such as timing or configuration are required.

If successful

Confidentiality
none
Integrity
none
Availability
low · the service can be disrupted

Impact can extend beyond the vulnerable component (scope changes).

Attack vector
Network
Attack complexity
High
Privileges required
None
User interaction
None
Scope
Changed
Confidentiality impact
None
Integrity impact
None
Availability impact
Low

Weakness class (CWE)

CWE-119 · Improper Restriction of Operations within the Bounds of a Memory Buffer

CVSS vector

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

nvd-primary

Attack context

MITRE CAPEC attack patterns and ATT&CK techniques for this weakness class (CWE). A starting point for detection rules and threat hunting.

ATT&CK techniques

—

Change log

  1. Fix✗ → ✓

For records you follow, these changes also arrive as notifications. →

References

Show all references (1 more)

Vendor advisories and official records. Exploit/PoC links are deliberately left out.

All records