docs/snyk/master/argocd-test.html
high severity
Exploit: Proof of Concept
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the AST class, caused by catastrophic backtracking when an input string contains many * characters in a row, followed by an unmatched character.
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:
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.
Upgrade minimatch to version 3.1.3, 4.2.4, 5.1.7, 6.2.1, 7.4.7, 8.0.5, 9.0.6, 10.2.1 or higher.
high severity
Exploit: Proof of Concept
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity via the matchOne function. An attacker can cause significant delays in processing and stall the event loop by supplying specially crafted glob patterns containing multiple non-adjacent GLOBSTAR segments.
Upgrade minimatch to version 3.1.3, 4.2.5, 5.1.8, 6.2.2, 7.4.8, 8.0.6, 9.0.7, 10.2.3 or higher.
high severity
Exploit: Proof of Concept
fast-xml-parser is a Validate XML, Parse XML, Build XML without C/C++ based libraries
Affected versions of this package are vulnerable to XML Entity Expansion in replaceEntitiesValue() when handling excessive DOCTYPE input. An attacker can cause excessive resource consumption and make the application unresponsive by submitting malicious XML input with large text entities referenced multiple times. This is a bypass for Billion Laughs protection in DocTypeReader.js, which prevents excessive referencing within and entity, but doesn't prevent repeated expansion of large entities.
This vulnerability can be mitigated by disabling DOCTYPE parsing using the processEntities: false option.
const { XMLParser } = require('fast-xml-parser');
const entity = 'A'.repeat(1000);
const refs = '&big;'.repeat(100);
const xml = `<!DOCTYPE foo [<!ENTITY big "${entity}">]><root>${refs}</root>`;
console.time('parse');
new XMLParser().parse(xml);
console.timeEnd('parse');
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
Upgrade fast-xml-parser to version 4.5.4, 5.3.6 or higher.
high severity
Exploit: Proof of Concept
fast-xml-parser is a Validate XML, Parse XML, Build XML without C/C++ based libraries
Affected versions of this package are vulnerable to Incorrect Regular Expression in the entity parsing RegEx in DOCTYPE declarations. An attacker can inject arbitrary values that override built-in XML entities by crafting entity names containing ., which is interpreted as a regex wildcard, allowing malicious content to be substituted in place of standard entities when the XML is parsed and subsequently rendered or used in sensitive contexts.
Upgrade fast-xml-parser to version 4.5.4, 5.3.5 or higher.
medium severity
Exploit: Not Defined
golang.org/x/net/html is a package that implements an HTML5-compliant tokenizer and parser.
Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity via the html.Parse function due to quadratic parsing complexity when processing certain inputs, which can lead to denial of service (DoS) if an attacker provides specially crafted HTML content.
Upgrade golang.org/x/net/html to version 0.45.0 or higher.
medium severity
Exploit: Not Defined
golang.org/x/net/html is a package that implements an HTML5-compliant tokenizer and parser.
Affected versions of this package are vulnerable to Infinite loop via the html.Parse function. An attacker can cause resource exhaustion and disrupt service availability by submitting specially crafted HTML input that triggers an infinite parsing loop.
Upgrade golang.org/x/net/html to version 0.45.0 or higher.
medium severity
MPL-2.0 license
medium severity
MPL-2.0 license
medium severity
MPL-2.0 license
medium severity
MPL-2.0 license
medium severity
MPL-2.0 license
medium severity
Exploit: Not Defined
Affected versions of this package are vulnerable to Improper Validation of Integrity Check Value for .idx and .pack files. An attacker can cause the application to consume corrupted files, leading to unexpected errors, due to checksums not being checked in the loadIdxFile() function.
This vulnerability can be mitigated by running 'git fsck' from the git CLI to check for data corruption on a given repository.
Upgrade github.com/go-git/go-git/v5/storage/filesystem to version 5.16.5 or higher.
medium severity
Exploit: Proof of Concept
foundation-sites is a responsive front-end framework
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to inefficient backtracking in the regular expressions used in URL forms.
https://www.''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
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:
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.
There is no fixed version for foundation-sites.
medium severity
Exploit: Not Defined
fast-xml-parser is a Validate XML, Parse XML, Build XML without C/C++ based libraries
Affected versions of this package are vulnerable to Buffer Overflow via the XMLBuilder when preserveOrder:true is set. An attacker can cause the application to crash by providing specially crafted input data.
This vulnerability can be mitigated by using preserveOrder:false or by validating input data before passing it to the builder.
Upgrade fast-xml-parser to version 4.5.4, 5.3.8 or higher.
medium severity
Exploit: Not Defined
dompurify is a DOM-only XSS sanitizer for HTML, MathML and SVG.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS) in the createDOMPurify() function, via comments embedded in XML noscript, xmp, noembed, noframes, and iframe attributes containing scripts.
Cross-site scripting (or XSS) is a code vulnerability that occurs when an attacker “injects” a malicious script into an otherwise trusted website. The injected script gets downloaded and executed by the end user’s browser when the user interacts with the compromised website.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as < and > can be coded as > in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
There are a few methods by which XSS can be manipulated:
| Type | Origin | Description |
|---|---|---|
| Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
| Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
| DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
| Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
The following environments are susceptible to an XSS attack:
This section describes the top best practices designed to specifically protect your code:
?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.Upgrade dompurify to version 2.5.9, 3.3.2 or higher.
medium severity
Exploit: Not Defined
dompurify is a DOM-only XSS sanitizer for HTML, MathML and SVG.
Affected versions of this package are vulnerable to Cross-site Scripting (XSS) in the createDOMPurify() function, via comments embedded in XML textarea attributes containing scripts.
Cross-site scripting (or XSS) is a code vulnerability that occurs when an attacker “injects” a malicious script into an otherwise trusted website. The injected script gets downloaded and executed by the end user’s browser when the user interacts with the compromised website.
This is done by escaping the context of the web application; the web application then delivers that data to its users along with other trusted dynamic content, without validating it. The browser unknowingly executes malicious script on the client side (through client-side languages; usually JavaScript or HTML) in order to perform actions that are otherwise typically blocked by the browser’s Same Origin Policy.
Injecting malicious code is the most prevalent manner by which XSS is exploited; for this reason, escaping characters in order to prevent this manipulation is the top method for securing code against this vulnerability.
Escaping means that the application is coded to mark key characters, and particularly key characters included in user input, to prevent those characters from being interpreted in a dangerous context. For example, in HTML, < can be coded as < and > can be coded as > in order to be interpreted and displayed as themselves in text, while within the code itself, they are used for HTML tags. If malicious content is injected into an application that escapes special characters and that malicious content uses < and > as HTML tags, those characters are nonetheless not interpreted as HTML tags by the browser if they’ve been correctly escaped in the application code and in this way the attempted attack is diverted.
The most prominent use of XSS is to steal cookies (source: OWASP HttpOnly) and hijack user sessions, but XSS exploits have been used to expose sensitive information, enable access to privileged services and functionality and deliver malware.
There are a few methods by which XSS can be manipulated:
| Type | Origin | Description |
|---|---|---|
| Stored | Server | The malicious code is inserted in the application (usually as a link) by the attacker. The code is activated every time a user clicks the link. |
| Reflected | Server | The attacker delivers a malicious link externally from the vulnerable web site application to a user. When clicked, malicious code is sent to the vulnerable web site, which reflects the attack back to the user’s browser. |
| DOM-based | Client | The attacker forces the user’s browser to render a malicious page. The data in the page itself delivers the cross-site scripting data. |
| Mutated | The attacker injects code that appears safe, but is then rewritten and modified by the browser, while parsing the markup. An example is rebalancing unclosed quotation marks or even adding quotation marks to unquoted parameters. |
The following environments are susceptible to an XSS attack:
This section describes the top best practices designed to specifically protect your code:
?, &, /, <, > and spaces to their respective HTML or URL encoded equivalents.Upgrade dompurify to version 3.2.7 or higher.
medium severity
Exploit: Proof of Concept
diff is a javascript text differencing implementation.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the parsePatch() and applyPatch() functions if the user input passed without sanitisation. An attacker can cause the process to enter an infinite loop and exhaust system memory by providing a patch with filename headers containing \r, \u2028, or \u2029 characters or having control over patch's patch header for application generated patches.
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:
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.
Upgrade diff to version 3.5.1, 4.0.4, 5.2.2, 8.0.3 or higher.
low severity
Exploit: Proof of Concept
Affected versions of this package are vulnerable to Insecure Randomness due to its use of the hexoid() function in the generation of fingerprint IDs.
Upgrade formidable to version 2.1.3, 3.5.3 or higher.
low severity
Exploit: Proof of Concept
brace-expansion is a Brace expansion as known from sh/bash
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the expand() function, which is prone to catastrophic backtracking on very long malicious inputs.
import index from "./index.js";
let str = "{a}" + ",".repeat(100000) + "\u0000";
let startTime = performance.now();
const result = index(str);
let endTime = performance.now();
let timeTaken = endTime - startTime;
console.log(`匹配耗时: ${timeTaken.toFixed(3)} 毫秒`);
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:
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.
Upgrade brace-expansion to version 1.1.12, 2.0.2, 3.0.1, 4.0.1 or higher.