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failIncident: Removal
Scanned: 6 days ago

delta-kernel-rust-sharing-wrapper

Artifact:
License: Permissive (Apache-2.0)
Published: 11 months ago



SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
No sensitive information found

Security

Vulnerabilities
No known vulnerabilities detected
Hardening
3 misconfigured toolchains detected

Threats

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

INCIDENTS FOR THIS VERSION:

removal
Reported By: Community

Popularity

5.58M
Total Downloads
Contributors
Declared Dependencies
2
Dependents

Top issues

Problem

Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors. These checks prevent the use of hard-to-secure string manipulation functions. They enforce static memory access checks, and allow only the use of range-verified string parsing functions. While these checks do not prevent every memory corruption issue by themselves, they do help reduce the likelihood.

Prevalence in PyPI community

4 packages
found in
Top 100
33 packages
found in
Top 1k
174 packages
found in
Top 10k
3639 packages
in community

Next steps

It's highly recommended to enable these checks for all software components used at security boundaries, or those that process user controlled inputs.
To enable these checks, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.

Problem

Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors, preventing them from reaching production. These checks minimize the number of security issues by enforcing strict memory access checks. They also prevent the use of hard-to-secure string and memory manipulation functions. To prove the binary has been compiled with these checks enabled, the compiler emits a special debug object. Removing the debug table eliminates this proof. Therefore, this check only applies to binaries that still have their debug tables.

Prevalence in PyPI community

6 packages
found in
Top 100
47 packages
found in
Top 1k
246 packages
found in
Top 10k
6306 packages
in community

Next steps

You should keep the debug table to prove that the SDL process has been followed.
To enable these checks, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.

Problem

Security Development Lifecycle (SDL) is a group of enhanced compile-time checks that report common coding mistakes as errors. These checks prevent the use of hard-to-secure memory manipulation functions. They enforce static memory access checks, and allow only the use of range-verified memory access functions. While these checks do not prevent every memory corruption issue by themselves, they do help reduce the likelihood.

Prevalence in PyPI community

2 packages
found in
Top 100
39 packages
found in
Top 1k
189 packages
found in
Top 10k
4600 packages
in community

Next steps

It's highly recommended to enable these checks for all software components used at security boundaries, or those that process user controlled inputs.
To enable these checks, refer to your programming language toolchain documentation.
In Microsoft VisualStudio, you can enable this feature by setting the compiler option /SDL to ON.

Problem

Software components contain executable code that performs actions implemented during its development. These actions are called behaviors. In the analysis report, behaviors are presented as human-readable descriptions that best match the underlying code intent. While most behaviors are benign, some are commonly abused by malicious software with the intent to cause harm. When a software package shares behavior traits with malicious software, it may become flagged by security solutions. Any detection from security solutions can cause friction for the end-users during software deployment. While the behavior is likely intended by the developer, there is a small chance this detection is true positive, and an early indication of a software supply chain attack.

Prevalence in PyPI community

0 packages
found in
Top 100
2 packages
found in
Top 1k
7 packages
found in
Top 10k
1009 packages
in community

Next steps

Investigate reported detections.
If the software intent does not relate to the reported behavior, 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 rewriting the flagged code without using the marked behaviors.

Problem

Software developers use programming and design knowledge to build reusable software components. Software components are the basic building blocks for modern applications. Software consumed by an enterprise consists of hundreds, and sometimes even thousands of open source components. Open source communities depend on the work of thousands of software developers that volunteer their time to maintain software components. Software developers build up the reputation of their open source projects by developing in public. Modern source code repositories have many social features that allow software developers to handle bug reports, have discussions with their users, and convey reaching significant project milestones. It is uncommon to find open source projects that omit linking their component to a publicly accessible source code repository.

Prevalence in PyPI community

No prevalence information at this time

Next steps

Check the software component behaviors for anomalies.
Consider exploratory software component testing within a sandbox environment.
Consider replacing the software component with a more widely used alternative.
Avoid using this software package until it is vetted as safe.

Top behaviors

Prevalence in PyPI community

Behavior commonly used by malicious software (Important)
Behavior often found in this community (Common)
3 packages
found in
Top 100
11 packages
found in
Top 1k
50 packages
found in
Top 10k
995 packages
in community

Prevalence in PyPI community

Behavior uncommon for this community (Uncommon)
0 packages
found in
Top 100
13 packages
found in
Top 1k
82 packages
found in
Top 10k
1822 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
2 packages
found in
Top 100
20 packages
found in
Top 1k
125 packages
found in
Top 10k
2532 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
23 packages
found in
Top 100
112 packages
found in
Top 1k
620 packages
found in
Top 10k
10791 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
16 packages
found in
Top 100
128 packages
found in
Top 1k
776 packages
found in
Top 10k
25965 packages
in community

Top vulnerabilities

No vulnerabilities found.