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failRisk: Vulnerabilities
Scanned: 5 days ago

aws-cdk.lambda-layer-awscli

Artifact:
latest
Top 10k
An AWS Lambda layer that contains the AWS CLI
License: Permissive (Apache-2.0)
Published: over 2 years ago




SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
2 debugging symbols found

Security

Vulnerabilities
1 severe vulnerabilities exploited
Hardening
1 execution hijacking concerns

Threats

Tampering
No evidence of software tampering
Malware
No evidence of malware inclusion

Popularity

3.32M
Total Downloads
Contributor
Declared Dependencies
6
Dependents

Top issues

Problem

Software composition analysis has identified a component with one or more known severe vulnerabilities. Available threat intelligence telemetry has confirmed that the reported high or critical severity vulnerabilities are actively being exploited by malicious actors.

Prevalence in PyPI community

38 packages
found in
Top 100
303 packages
found in
Top 1k
2611 packages
found in
Top 10k
103184 packages
in community

Next steps

We strongly advise updating the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Software composition analysis has identified a component with one or more known vulnerabilities. Based on the CVSS scoring, these vulnerabilities have been marked as high severity.

Prevalence in PyPI community

50 packages
found in
Top 100
352 packages
found in
Top 1k
2858 packages
found in
Top 10k
108771 packages
in community

Next steps

Perform impact analysis for the reported CVEs.
Update the component to the latest version.
If the update can't resolve the issue, create a plan to isolate or replace the affected component.

Problem

Uniform Resource Locators (URLs) are structured addresses that point to locations and assets on the internet. URLs allow software developers to build complex applications that exchange data with servers that can be hosted in multiple geographical regions. URLs can commonly be found embedded in documentation, configuration files, source code and compiled binaries. One or more embedded URLs were discovered to link to raw files hosted on GitHub. Attackers often abuse popular web services to host malicious payloads. Since code-sharing services URLs are typically allowed by security solutions, using them for payload delivery increases the odds that the malicious code will reach the user. While the presence of code-sharing service locations does not imply malicious intent, all of their uses in a software package should be documented and approved. An increasing number of software supply chain attacks in the open source space leverages the GitHub service to deliver malicious payloads.

Prevalence in PyPI community

33 packages
found in
Top 100
206 packages
found in
Top 1k
1631 packages
found in
Top 10k
63840 packages
in community

Next steps

Investigate reported detections.
If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider an alternative delivery mechanism for software packages.

Problem

Applications communicate with web services by exchanging HTTP requests. During software development, externally hosted services are used by developers to debug software quality issues relating to exchanging HTTP requests. Attackers commonly abuse tools designed for HTTP request inspection to monitor network traffic and extract sensitive information from the HTTP traffic. While the presence of domains related to HTTP inspection does not imply malicious intent, all of their uses in a software package should be documented and approved. Attackers might have purposely injected security testing tools in the software package to monitor the network traffic of the infected computer system. It is also possible that the software package has mistakenly included a part of its testing infrastructure during packaging.

Prevalence in PyPI community

10 packages
found in
Top 100
39 packages
found in
Top 1k
229 packages
found in
Top 10k
11208 packages
in community

Next steps

Investigate reported detections.
If the software should not include these network references, investigate your build and release environment for software supply chain compromise.
You should delay the software release until the investigation is completed, or until the issue is risk accepted.
Consider removing all references to flagged network locations.

Problem

Buffer overrun protection on Linux is achieved in two ways. The most common solution is to use the stack canary (also called cookie). The stack canary is a special value written onto the stack that allows the operating system to detect and terminate the program if a stack overrun occurs. In most cases, compilers will apply the stack canary conservatively in order to avoid a negative performance impact. Therefore, stack canaries are often used together with another stack overrun mitigation - fortified functions. Fortified functions are usually wrappers around standard glibc functions (such as memcpy) which perform boundary checks either at compile time or run time to determine if a memory violation has occurred. The compiler needs additional context to generate such calls (for example, array size that needs to be known at compile time). Because of this, the compiler will virtually never substitute all viable functions with their fortified counterparts in complex programs. However, when combined with the stack canary, fortified functions provide a good measure of buffer overrun protection.

Prevalence in PyPI community

18 packages
found in
Top 100
112 packages
found in
Top 1k
646 packages
found in
Top 10k
13062 packages
in community

Next steps

Presence of unfortified memory functions may indicate use of unsafe programming practices, and you should avoid it if possible.
In GCC, enable fortified functions with -fstack-protector and -D_FORTIFY_SOURCE=2 flag, while using at least -O1 optimization level.

Top behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)
3 packages
found in
Top 100
17 packages
found in
Top 1k
81 packages
found in
Top 10k
1111 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
5 packages
found in
Top 100
28 packages
found in
Top 1k
165 packages
found in
Top 10k
3060 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
5 packages
found in
Top 100
28 packages
found in
Top 1k
162 packages
found in
Top 10k
3073 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
1 packages
found in
Top 100
10 packages
found in
Top 1k
32 packages
found in
Top 10k
909 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
34 packages
found in
Top 100
185 packages
found in
Top 1k
1062 packages
found in
Top 10k
25867 packages
in community

Top vulnerabilities

Vulnerability Exploitation Lifecycle
(5 Active Vulnerabilities)
2 (2 Fixable)
CVE-2024-37891m
CVE-2023-45803m
2 (2 Fixable)
CVE-2023-43804h
CVE-2025-50181m
None
None
Exploits Unknown
Exploits Exist
Exploited by Malware
Patching Mandated