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pysqlite3-binary

Artifact:
latest
Top 10k
DB-API 2.0 interface for Sqlite 3.x
License: unknown
Published: about 1 year ago




SAFE Assessment

Compliance

Licenses
No license compliance issues
Secrets
4 debugging symbols found

Security

Vulnerabilities
No known vulnerabilities detected
Hardening
2 execution hijacking concerns

Threats

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

Popularity

9.85M
Total Downloads
Contributor
Declared Dependencies
40
Dependents

Top issues

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.

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.

Problem

On Linux, external symbols are resolved via the procedure linkage table (PLT) and the global offset table (GOT). Without any protection, both are writable at runtime and thus leave the executable vulnerable to pointer hijacking - an attack where the function address is overwritten with an address of a malicious function. Pointer hijacking can be mitigated by using full read-only relocations, which instruct the compiler to unify global offset tables into a single read-only table. This requires that all external function symbols are resolved at load-time instead of during execution, and may increase loading time for large programs.

Prevalence in PyPI community

22 packages
found in
Top 100
122 packages
found in
Top 1k
767 packages
found in
Top 10k
16246 packages
in community

Next steps

In most cases, it's recommended to use full read-only relocations (in GCC: -Wl,-z,relro,-z,now).
If the executable load-time is an issue, you should use partial read-only relocations.

Problem

Debug databases are typically only used during software development. On Windows, they are usually files embedded into the executable (PDB), while on Linux, they're contained inside special executable sections. The databases contain private debug symbols that make it significantly easier to reverse-engineer a closed-source application. In some cases, having a debug database is equivalent to having access to the source code. Presence of debug databases could indicate that one or more software components have been built using a debug profile, instead of the release. Private debug databases can be embedded into software components by programming language tools.

Prevalence in PyPI community

22 packages
found in
Top 100
113 packages
found in
Top 1k
748 packages
found in
Top 10k
13672 packages
in community

Next steps

To remediate this issue and remove private debugging information, refer to your programming language toolchain documentation.

Problem

Common compilers often embed source code information into executables for debugging purposes, usually by mapping symbols to source filenames or paths. While this is typically desirable in open-source software and standard tools, that information can be used to determine security weaknesses, code repository layout, trade secrets and similar sensitive information. Such symbols make it easier to reverse-engineer a closed source application.

Prevalence in PyPI community

22 packages
found in
Top 100
122 packages
found in
Top 1k
834 packages
found in
Top 10k
18721 packages
in community

Next steps

Strip out such information in the linking phase by using compiler options like the -s flag in GCC, or in the post-build phase by using the strip tool.

Top behaviors

Prevalence in PyPI community

Behavior often found in this community (Common)
67 packages
found in
Top 100
520 packages
found in
Top 1k
3993 packages
found in
Top 10k
158349 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
12 packages
found in
Top 100
74 packages
found in
Top 1k
427 packages
found in
Top 10k
10198 packages
in community

Prevalence in PyPI community

Behavior often found in this community (Common)
70 packages
found in
Top 100
534 packages
found in
Top 1k
3771 packages
found in
Top 10k
146071 packages
in community

Prevalence in PyPI community

No behavior prevalence information at this time

Prevalence in PyPI community

Behavior often found in this community (Common)
75 packages
found in
Top 100
593 packages
found in
Top 1k
4478 packages
found in
Top 10k
229841 packages
in community

Top vulnerabilities

No vulnerabilities found.