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failRisk: Secrets
Scanned: 9 days ago

deltalake

Artifact:
Native Delta Lake Python binding based on delta-rs with Pandas integration
License: unknown
Published: 8 months ago




SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
2 plaintext private keys 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:

Popularity

157.11M
Total Downloads
Contributors
Declared Dependencies
136
Dependents

Top issues

Problem

Private keys are used to protect sensitive information, digitally sign content, and to secure information transmission. Private keys are considered secrets, and as such should never be published. Depending on the type of a private key, its exposure can carry a varying degree of risk. Attackers abuse private keys to gain unauthorized server access, decrypt sensitive information, digitally sign content, or impersonate users whose private keys have been leaked.

Prevalence in PyPI community

7 packages
found in
Top 100
35 packages
found in
Top 1k
162 packages
found in
Top 10k
2400 packages
in community

Next steps

Review the reported private keys and remove them from the software package if they were accidentally included.
If the keys were published unintentionally and the software has been made public, you should revoke the keys and file a security incident.

Problem

Private keys are used to protect sensitive information, digitally sign content, and to secure information transmission. Private keys are considered secrets, and as such should never be published. Depending on the private key type its exposure can carry a varying degree of risk. While it is common for private keys to be found as standalone files, the detected ones have been found embedded within another software package component. This could indicate an attempt to hide private key presence. Attackers abuse private keys to gain unauthorized server access, decrypt sensitive information, digitally sign content, or impersonate users whose private keys have been leaked.

Prevalence in PyPI community

8 packages
found in
Top 100
27 packages
found in
Top 1k
98 packages
found in
Top 10k
1458 packages
in community

Next steps

Review the reported private keys and remove them from the software package if they were accidentally included.
If the keys were published unintentionally and the software has been made public, you should revoke the keys and file a security incident.

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.

Top behaviors

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

Prevalence in PyPI community

Behavior often found in this community (Common)
34 packages
found in
Top 100
169 packages
found in
Top 1k
1256 packages
found in
Top 10k
55955 packages
in community

Top vulnerabilities

Vulnerability Exploitation Lifecycle
(2 Active Vulnerabilities)
None
None
None
None
Exploits Unknown
Exploits Exist
Exploited by Malware
Patching Mandated

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