dhondta/bots-scheduler:requirements.txt

Vulnerabilities

25 via 28 paths

Dependencies

50

Source

GitHub

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Severity
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Status
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high severity
new

Improper Input Validation

  • Vulnerable module: ipaddress
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt ipaddress@1.0.23

Overview

ipaddress is an IPv4/IPv6 manipulation library

Affected versions of this package are vulnerable to Improper Input Validation. Improper input validation of octal strings in stdlib ipaddress allows unauthenticated remote attackers to perform indeterminate SSRF, RFI, and LFI attacks on many programs that rely on Python stdlib ipaddress. The highest threat from this vulnerability is to data integrity and system availability.

Remediation

There is no fixed version for ipaddress.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: markdown2
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt markdown2@2.3.10
    Remediation: Upgrade to tinyscript@0.1.
  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt codext@file-.codext-VERSION.txt markdown2@2.3.10
    Remediation: Upgrade to tinyscript@0.1.

Overview

markdown2 is a fast and complete Python implementation of Markdown.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). If an attacker provides a malicious string, it is possible to make markdown2 get stuck processing for an exponential time.

PoC

markdown2.markdown('[#a' + ' ' * 3456, extras=['numbering'])

markdown2.markdown('```' + '\n' * 3456, extras=['fenced-code-blocks'])

markdown2.markdown('-*-' + ' ' * 3456, use_file_vars=True)

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade markdown2 to version 2.4.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This can happen in the BLP container format where the reported size of the contained image is not properly checked. These images can cause arbitrarily large memory allocations.

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 Pillow to version 8.1.2 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This can happen in the ICO container format where the reported size of the contained image is not properly checked. These images can cause arbitrarily large memory allocations.

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 Pillow to version 8.1.2 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This can happen in the ICNS container format where the reported size of the contained image is not properly checked. These images can cause arbitrarily large memory allocations.

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 Pillow to version 8.1.2 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). Improper checks in BlpImagePlugin may result in the decoder running over empty data.

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 Pillow to version 8.2.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This is due to improper checks in FliDecode that may result in an infinite loop.

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 Pillow to version 8.2.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). Improper checks in PSDImagePlugin may result in a DoS when calling Image.open.

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 Pillow to version 8.2.0 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). The readline in EPS use an accidentally quadratic method of accumulating lines while looking for a line ending. A malicious EPS file can use this to perform a DoS in the open phase, before an image is accepted for opening.

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 Pillow to version 8.2.0 or higher.

References

high severity

Heap-based Buffer Overflow

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Heap-based Buffer Overflow insufficent fix for CVE-2020-35654 due to incorrect error checking in TiffDecode.c.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

high severity

Insufficient Validation

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Insufficient Validation. In TiffDecode.c, there is a negative-offset memcpy with an invalid size.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

high severity

Out-of-bounds Read

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. The PCX image decoder uses the reported image stride to calculate the row buffer, rather than calculating it from the image size.

Remediation

Upgrade Pillow to version 8.1.0 or higher.

References

high severity

Out-of-bounds Read

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. There is a 4 byte read overflow in SGIRleDecode.c, where the code is not correctly checking the offsets and length tables.

Remediation

Upgrade Pillow to version 8.1.0 or higher.

References

high severity

Out-of-bounds Read

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read due to invalid tile boundaries lead.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via next_object_id.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

high severity

Denial of Service (DoS)

  • Vulnerable module: pygments
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt pygments@2.5.2
    Remediation: Upgrade to tinyscript@0.1.
  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt mdv@1.7.4 pygments@2.5.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS). An infinite loop exists in SMLLexer that may lead to denial of service. This occurs when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by an input that only contains the "exception" keyword.

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 pygments to version 2.7.4 or higher.

References

high severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: pygments
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt pygments@2.5.2
    Remediation: Upgrade to tinyscript@0.1.
  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt mdv@1.7.4 pygments@2.5.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The lexers used to parse programming languages rely heavily on regular expressions. Some of these have exponential or cubic worst-case complexity and can be abuse by crafting malicious input.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

  • A The string must start with the letter 'A'
  • (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
  • D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

  1. CCC
  2. CC+C
  3. C+CC
  4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

String Number of C's Number of steps
ACCCX 3 38
ACCCCX 4 71
ACCCCCX 5 136
ACCCCCCCCCCCCCCX 14 65,553

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade pygments to version 2.7.4 or higher.

References

medium severity

Cryptographic Issues

  • Vulnerable module: ipaddress
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt ipaddress@1.0.23

Overview

ipaddress is an IPv4/IPv6 manipulation library

Affected versions of this package are vulnerable to Cryptographic Issues. The hash() methods of classes IPv4Interface and IPv6Interface had issue of generating constant hash values of 32 and 128 respectively causing hash collisions. The fix uses the hash() function to generate hash values for the objects instead of XOR operation.

Remediation

There is no fixed version for ipaddress.

References

medium severity

Hash Collision

  • Vulnerable module: ipaddress
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt ipaddress@1.0.23

Overview

ipaddress is an IPv4/IPv6 manipulation library

Affected versions of this package are vulnerable to Hash Collision. The package improperly computes hash values in the IPv4Interface and IPv6Interface classes, which might allow a remote attacker to cause a denial of service if an application is affected by the performance of a dictionary containing IPv4Interface or IPv6Interface objects, and this attacker can cause many dictionary entries to be created.

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

There is no fixed version for ipaddress.

References

medium severity

Buffer Overflow

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Buffer Overflow. Two Buffer Overflows exist in libImaging/TiffDecode.c.

Remediation

Upgrade Pillow to version 7.1.0 or higher.

References

medium severity

Out-of-Bounds

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-Bounds. Multiple out-of-bounds reads exist in libImaging/FliDecode.c.

Remediation

Upgrade Pillow to version 7.1.0 or higher.

References

medium severity

Out-of-bounds Read

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. In libImaging/SgiRleDecode.c a number of out-of-bounds reads exist in the parsing of SGI image files.

Remediation

Upgrade Pillow to version 7.1.0 or higher.

References

medium severity

Out-of-bounds Read

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. In libImaging/Jpeg2KDecode.c there are multiple out-of-bounds reads via a crafted JP2 file.

Remediation

Upgrade Pillow to version 7.1.0 or higher.

References

medium severity

Out-of-bounds Read

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. In libImaging/PcxDecode.c, an out-of-bounds read can occur when reading PCX files where state->shuffle is instructed to read beyond state->buffer.

Remediation

Upgrade Pillow to version 7.1.0 or higher.

References

medium severity

Out-of-bounds Write

  • Vulnerable module: pillow
  • Introduced through: tinyscript@file-.tinyscript-VERSION.txt

Detailed paths

  • Introduced through: dhondta/bots-scheduler@dhondta/bots-scheduler tinyscript@file-.tinyscript-VERSION.txt asciistuff@file-.asciistuff-VERSION.txt pillow@6.2.2
    Remediation: Upgrade to tinyscript@0.1.

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Write via OOB Write in TiffDecode.c when reading corrupt YCbCr files. This happens because of certain interpretation conflicts with LibTIFF in RGBA mode.

Remediation

Upgrade Pillow to version 8.1.0 or higher.

References