opent2t-translator-com-wink-lightbulb@0.1.9

Vulnerabilities

10 via 46 paths

Dependencies

199

Source

npm

Find, fix and prevent vulnerabilities in your code.

Severity
  • 1
  • 9
Status
  • 10
  • 0
  • 0

high severity

Uninitialized Memory Exposure

  • Vulnerable module: base64url
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 base64url@1.0.6
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 base64url@1.0.6

Overview

base64url Converting to, and from, base64url.

Affected versions of this package are vulnerable to Uninitialized Memory Exposure. An attacker could extract sensitive data from uninitialized memory or may cause a Denial of Service (DoS) by passing in a large number, in setups where typed user input can be passed (e.g. from JSON).

Details

The Buffer class on Node.js is a mutable array of binary data, and can be initialized with a string, array or number.

const buf1 = new Buffer([1,2,3]);
// creates a buffer containing [01, 02, 03]
const buf2 = new Buffer('test');
// creates a buffer containing ASCII bytes [74, 65, 73, 74]
const buf3 = new Buffer(10);
// creates a buffer of length 10

The first two variants simply create a binary representation of the value it received. The last one, however, pre-allocates a buffer of the specified size, making it a useful buffer, especially when reading data from a stream. When using the number constructor of Buffer, it will allocate the memory, but will not fill it with zeros. Instead, the allocated buffer will hold whatever was in memory at the time. If the buffer is not zeroed by using buf.fill(0), it may leak sensitive information like keys, source code, and system info.

Remediation

Upgrade base64url to version 3.0.0 or higher. Note This is vulnerable only for Node <=4

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: date-and-time
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 date-and-time@0.3.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 date-and-time@0.3.0

Overview

date-and-time is an A Minimalist DateTime utility for Node.js and the browser

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

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 date-and-time to version 0.14.2 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS )

  • Vulnerable module: marked
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 marked@0.3.19
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 marked@0.3.19

Overview

marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS ). The em regex within src/rules.js file have multiple unused capture groups which could lead to a denial of service attack if user input is reachable.

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 marked to version 1.1.1 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 marked@0.3.19
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 marked@0.3.19

Overview

marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The inline.text regex may take quadratic time to scan for potential email addresses starting at every point.

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 marked to version 0.6.2 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: marked
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 marked@0.3.19
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 marked@0.3.19

Overview

marked is a low-level compiler for parsing markdown without caching or blocking for long periods of time.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A Denial of Service condition could be triggered through exploitation of the heading regex.

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 marked to version 0.4.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0

Overview

validator is an A library of string validators and sanitizers.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isSlug function

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "111"
    for (var i = 0; i < n; i++) {
        ret += "a"
    }

    return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isSlug(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

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 validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0

Overview

validator is an A library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = ""
    for (var i = 0; i < n; i++) {
        ret += " "
    }

    return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.rtrim(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }

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 validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0

Overview

validator is an A library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = "hsla(0"
    for (var i = 0; i < n; i++) {
        ret += " "
    }

    return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 1000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
       validator.isHSL(attack_str)
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

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 validator to version 13.6.0 or higher.

References

medium severity

Regular Expression Denial of Service (ReDoS)

  • Vulnerable module: validator
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-parser@0.8.18 json-schema-ref-parser@3.3.1 z-schema@3.25.1 validator@10.11.0
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 z-schema@3.25.1 validator@10.11.0

Overview

validator is an A library of string validators and sanitizers.

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

PoC

var validator = require("validator")
function build_attack(n) {
    var ret = ""
    for (var i = 0; i < n; i++) {
        ret += "<"
    }

    return ret+"";
}
for(var i = 1; i <= 50000; i++) {
    if (i % 10000 == 0) {
        var time = Date.now();
        var attack_str = build_attack(i)
        validator.isEmail(attack_str,{ allow_display_name: true })
        var time_cost = Date.now() - time;
        console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
   }
}

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 validator to version 13.6.0 or higher.

References

medium severity

XML External Entity (XXE) Injection

  • Vulnerable module: xmldom
  • Introduced through: opent2t-translator-com-wink-hub@1.4.3

Detailed paths

  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 xmldom@0.1.31
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 xmldom@0.1.31
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 xmldom@0.1.31
  • Introduced through: opent2t-translator-com-wink-lightbulb@0.1.9 opent2t-translator-com-wink-hub@1.4.3 opent2t-onboarding-org-opent2t-onboarding-wink@1.4.0 opent2t@1.1.0 raml-1-parser@0.2.33 raml-definition-system@0.0.43 raml-typesystem@0.0.49 xmldom@0.1.31

Overview

xmldom is an A pure JavaScript W3C standard-based (XML DOM Level 2 Core) DOMParser and XMLSerializer module.

Affected versions of this package are vulnerable to XML External Entity (XXE) Injection. Does not correctly preserve system identifiers, FPIs or namespaces when repeatedly parsing and serializing maliciously crafted documents.

Details

XXE Injection is a type of attack against an application that parses XML input. XML is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. By default, many XML processors allow specification of an external entity, a URI that is dereferenced and evaluated during XML processing. When an XML document is being parsed, the parser can make a request and include the content at the specified URI inside of the XML document.

Attacks can include disclosing local files, which may contain sensitive data such as passwords or private user data, using file: schemes or relative paths in the system identifier.

For example, below is a sample XML document, containing an XML element- username.

<?xml version="1.0" encoding="ISO-8859-1"?>
   <username>John</username>
</xml>

An external XML entity - xxe, is defined using a system identifier and present within a DOCTYPE header. These entities can access local or remote content. For example the below code contains an external XML entity that would fetch the content of /etc/passwd and display it to the user rendered by username.

<?xml version="1.0" encoding="ISO-8859-1"?>
<!DOCTYPE foo [
   <!ENTITY xxe SYSTEM "file:///etc/passwd" >]>
   <username>&xxe;</username>
</xml>

Other XXE Injection attacks can access local resources that may not stop returning data, possibly impacting application availability and leading to Denial of Service.

Remediation

Upgrade xmldom to version 0.5.0 or higher.

References