Vulnerabilities

 3 via 3 paths

Dependencies

 3

Source

 GitHub

Commit

 344346a5

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Severity
  • 3
Status
  • 3
  • 0
  • 0

low severity

Buffer Overflow

  • Vulnerable module: numpy
  • Introduced through: numpy@1.21.3

Detailed paths

  • Introduced through: chrislit/abydos@chrislit/abydos#344346a5fceb6acc631b3d24e16b73a303cece2c › numpy@1.21.3
    Remediation: Upgrade to numpy@1.22.0.

Overview

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to Buffer Overflow due to missing boundary checks in the array_from_pyobj function of fortranobject.c. This may allow an attacker to conduct Denial of Service by carefully constructing an array with negative values.

Remediation

Upgrade numpy to version 1.22.0 or higher.

References

Buffer Overflow vulnerability report

low severity

Denial of Service (DoS)

  • Vulnerable module: numpy
  • Introduced through: numpy@1.21.3

Detailed paths

  • Introduced through: chrislit/abydos@chrislit/abydos#344346a5fceb6acc631b3d24e16b73a303cece2c › numpy@1.21.3
    Remediation: Upgrade to numpy@1.22.0.

Overview

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to Denial of Service (DoS) due to an incomplete string comparison in the numpy.core component, which may allow attackers to fail the APIs via constructing specific string objects.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

  • High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

  • Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade numpy to version 1.22.0rc1 or higher.

References

Denial of Service (DoS) vulnerability report

low severity

NULL Pointer Dereference

  • Vulnerable module: numpy
  • Introduced through: numpy@1.21.3

Detailed paths

  • Introduced through: chrislit/abydos@chrislit/abydos#344346a5fceb6acc631b3d24e16b73a303cece2c › numpy@1.21.3
    Remediation: Upgrade to numpy@1.22.2.

Overview

numpy is a fundamental package needed for scientific computing with Python.

Affected versions of this package are vulnerable to NULL Pointer Dereference due to missing return-value validation in the PyArray_DescrNew function, which may allow attackers to conduct Denial of Service attacks by repetitively creating and sort arrays.

Note: This may likely only happen if application memory is already exhausted, as it requires the newdescr object of the PyArray_DescrNew to evaluate to NULL.

Remediation

Upgrade numpy to version 1.22.2 or higher.

References

NULL Pointer Dereference vulnerability report