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critical severity
- Vulnerable module: open
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › open@0.0.5Remediation: Upgrade to snyk@1.76.0.
Overview
open is a cross platform package that opens stuff like URLs, files, executables.
Affected versions of this package are vulnerable to Arbitrary Code Injection when unsanitized user input is passed in.
The package does come with the following warning in the readme:
The same care should be taken when calling open as if you were calling child_process.exec directly. If it is an executable it will run in a new shell.
The package open
is replacing the opn
package, which is now deprecated. The older versions of open
are vulnerable.
Note: Upgrading open
to the last version will prevent this vulnerability but is also likely to have unwanted effects since it now has a very different API.
Remediation
Upgrade open
to version 6.0.0 or higher.
References
critical severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to SQL Injection via the replacements
statement. It allowed a malicious actor to pass dangerous values such as OR true; DROP TABLE
users through replacements which would result in arbitrary SQL execution.
Remediation
Upgrade sequelize
to version 6.19.1 or higher.
References
high severity
- Vulnerable module: open
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › open@0.0.5Remediation: Upgrade to snyk@1.76.0.
Overview
open is a cross platform package that opens stuff like URLs, files, executables.
Affected versions of this package are vulnerable to Arbitrary Command Injection. Urls are not properly escaped before concatenating them into the command that is opened using exec()
.
Note: Upgrading open
to the last version will prevent this vulnerability but is also likely to have unwanted effects since it now has a very different API.
Remediation
Upgrade open
to version 6.0.0 or higher.
References
high severity
- Vulnerable module: pg
- Introduced through: pg@6.1.2
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › pg@6.1.2Remediation: Upgrade to pg@6.1.6.
Overview
pg is a non-blocking PostgreSQL client for node.js.
Affected versions of this package are vulnerable to Arbitrary Code Execution. When parsing results of a query, it goes through a form of eval
, and with a specially crafted column name, an attacker can cause code to run remotely on the server.
PoC:
const { Client } = require('pg')
const client = new Client()
client.connect()
const sql = `SELECT 1 AS "\\'/*", 2 AS "\\'*/\n + console.log(process.env)] = null;\n//"`
client.query(sql, (err, res) => {
client.end()
});
Remediation
Upgrade pg
to version 2.11.2, 3.6.4, 4.5.7, 5.2.1, 6.0.5, 6.1.6, 6.2.5, 6.3.3, 6.4.2, 7.0.2, 7.1.2 or higher.
References
high severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to Improper Filtering of Special Elements due to attributes not being escaped if they included (
and )
, or were equal to *
and were split if they included the character .
.
Remediation
Upgrade sequelize
to version 6.29.0 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.20.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function zipObjectDeep
can be tricked into adding or modifying properties of the Object prototype. These properties will be present on all objects.
PoC
const _ = require('lodash');
_.zipObjectDeep(['__proto__.z'],[123]);
console.log(z); // 123
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.20 or higher.
References
high severity
- Vulnerable module: bson
- Introduced through: trailpack-cache@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-cache@2.0.0 › cache-manager-mongodb@0.1.7 › mongodb@2.2.36 › mongodb-core@2.1.20 › bson@1.0.9Remediation: Upgrade to trailpack-cache@3.0.0.
Overview
bson is a BSON Parser for node and browser.
Affected versions of this package are vulnerable to Internal Property Tampering. The package will ignore an unknown value for an object's _bsotype
, leading to cases where an object is serialized as a document rather than the intended BSON type.
NOTE: This vulnerability has also been identified as: CVE-2019-2391
Remediation
Upgrade bson
to version 1.1.4 or higher.
References
high severity
- Vulnerable module: bson
- Introduced through: trailpack-cache@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-cache@2.0.0 › cache-manager-mongodb@0.1.7 › mongodb@2.2.36 › mongodb-core@2.1.20 › bson@1.0.9Remediation: Upgrade to trailpack-cache@3.0.0.
Overview
bson is a BSON Parser for node and browser.
Affected versions of this package are vulnerable to Internal Property Tampering. The package will ignore an unknown value for an object's _bsotype
, leading to cases where an object is serialized as a document rather than the intended BSON type.
NOTE: This vulnerability has also been identified as: CVE-2020-7610
Remediation
Upgrade bson
to version 1.1.4 or higher.
References
high severity
- Vulnerable module: bower
- Introduced through: bower@1.8.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › bower@1.8.0Remediation: Upgrade to bower@1.8.8.
Overview
bower offers a generic, unopinionated solution to the problem of front-end package management.
Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip). Attackers can write arbitrary files when a malicious archive is extracted.
Details
It is exploited using a specially crafted zip archive, that holds path traversal filenames. When exploited, a filename in a malicious archive is concatenated to the target extraction directory, which results in the final path ending up outside of the target folder. For instance, a zip may hold a file with a "../../file.exe" location and thus break out of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicous file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
+2018-04-15 22:04:29 ..... 19 19 good.txt
+2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade bower
to version 1.8.8 or higher.
References
high severity
- Vulnerable module: ansi-regex
- Introduced through: snyk@1.25.0 and nunjucks@3.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.685.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › inquirer@1.0.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.78.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.685.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › yargs@3.32.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to nunjucks@3.2.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › inquirer@1.0.3 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.78.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › yargs@3.32.0 › cliui@3.2.0 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to nunjucks@3.2.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › inquirer@1.0.3 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.78.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › update-notifier@0.5.0 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › update-notifier@0.5.0 › string-length@1.0.1 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.73.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › inquirer@1.0.3 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1Remediation: Upgrade to snyk@1.78.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › update-notifier@0.5.0 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › yargs@3.32.0 › cliui@3.2.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to nunjucks@3.2.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › yargs@3.32.0 › cliui@3.2.0 › wrap-ansi@2.1.0 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to nunjucks@3.2.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › yargs@3.32.0 › cliui@3.2.0 › wrap-ansi@2.1.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1Remediation: Upgrade to nunjucks@3.2.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › yargs@4.8.1 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › yargs@4.8.1 › cliui@3.2.0 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › yargs@4.8.1 › cliui@3.2.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › boxen@0.3.1 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › yargs@4.8.1 › cliui@3.2.0 › wrap-ansi@2.1.0 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › boxen@0.3.1 › chalk@1.1.3 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › boxen@0.3.1 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › yargs@4.8.1 › cliui@3.2.0 › wrap-ansi@2.1.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › boxen@0.3.1 › widest-line@1.0.0 › string-width@1.0.2 › strip-ansi@3.0.1 › ansi-regex@2.1.1
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to the sub-patterns [[\\]()#;?]*
and (?:;[-a-zA-Z\\d\\/#&.:=?%@~_]*)*
.
PoC
import ansiRegex from 'ansi-regex';
for(var i = 1; i <= 50000; i++) {
var time = Date.now();
var attack_str = "\u001B["+";".repeat(i*10000);
ansiRegex().test(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:
- CCC
- CC+C
- C+CC
- 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 ansi-regex
to version 3.0.1, 4.1.1, 5.0.1, 6.0.1 or higher.
References
high severity
- Vulnerable module: dottie
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1 › dottie@1.1.1Remediation: Upgrade to trailpack-sequelize@2.0.2.
Overview
dottie is a Fast and safe nested object access and manipulation in JavaScript
Affected versions of this package are vulnerable to Prototype Pollution due to insufficient checks, via the set()
function and the current
variable in the /dottie.js
file.
PoC
var dottie = require("dottie")
var obj1 = {}
var obj2 = {}
var bad_path1 = '__proto__.test1'
var bad_path2 = '__proto__.test2'
console.log("before:"+ obj1.test1)
console.log("before:"+ obj2.test2)
dottie.default(obj1,bad_path1,"polluted1")
dottie.set(obj2,bad_path2,"polluted2")
console.log("after:"+obj1.test1)
console.log("after:"+obj2.test2)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade dottie
to version 2.0.4 or higher.
References
high severity
- Vulnerable module: fresh
- Introduced through: express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › fresh@0.3.0Remediation: Upgrade to express@4.15.5.
Overview
fresh
is HTTP response freshness testing.
Affected versions of this package are vulnerable to Regular expression Denial of Service (ReDoS) attacks. A Regular Expression (/ *, */
) was used for parsing HTTP headers and take about 2 seconds matching time for 50k characters.
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:
- CCC
- CC+C
- C+CC
- 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 fresh
to version 0.5.2 or higher.
References
high severity
- Vulnerable module: i18next
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › i18next@3.4.1Remediation: Upgrade to trails@3.0.0.
Overview
i18next is an internationalization framework for browser or any other javascript environment (eg. node.js).
Affected versions of this package are vulnerable to Prototype Pollution via getLastOfPath()
in i18next.js
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade i18next
to version 19.8.5 or higher.
References
high severity
new
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.17.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution through the zipObjectDeep
function due to improper user input sanitization in the baseZipObject
function.
PoC
lodash.zipobjectdeep:
const zipObjectDeep = require("lodash.zipobjectdeep");
let emptyObject = {};
console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined
zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function
console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true
lodash:
const test = require("lodash");
let emptyObject = {};
console.log(`[+] Before prototype pollution : ${emptyObject.polluted}`);
//[+] Before prototype pollution : undefined
test.zipObjectDeep(["constructor.prototype.polluted"], [true]);
//we inject our malicious attributes in the vulnerable function
console.log(`[+] After prototype pollution : ${emptyObject.polluted}`);
//[+] After prototype pollution : true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.17 or higher.
References
high severity
- Vulnerable module: moment
- Introduced through: moment@2.17.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › moment@2.17.1Remediation: Upgrade to moment@2.29.2.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Directory Traversal when a user provides a locale string which is directly used to switch moment locale.
Details
A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.
Directory Traversal vulnerabilities can be generally divided into two types:
- Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.
st
is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public
route.
If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.
curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa
Note %2e
is the URL encoded version of .
(dot).
- Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as
Zip-Slip
.
One way to achieve this is by using a malicious zip
archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip
archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
2018-04-15 22:04:29 ..... 19 19 good.txt
2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade moment
to version 2.29.2 or higher.
References
high severity
- Vulnerable module: mongodb
- Introduced through: trailpack-cache@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-cache@2.0.0 › cache-manager-mongodb@0.1.7 › mongodb@2.2.36Remediation: Upgrade to trailpack-cache@3.0.0.
Overview
mongodb is an official MongoDB driver for Node.js.
Affected versions of this package are vulnerable to Denial of Service (DoS). The package fails to properly catch an exception when a collection name is invalid and the DB does not exist, crashing the application.
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:
- CCC
- CC+C
- C+CC
- 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 mongodb
to version 3.1.13 or higher.
References
high severity
- Vulnerable module: nunjucks
- Introduced through: nunjucks@3.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0Remediation: Upgrade to nunjucks@3.2.3.
Overview
nunjucks is a powerful templating engine with inheritance, asynchronous control, and more (jinja2 inspired).
Affected versions of this package are vulnerable to Prototype Pollution.
via the constructor
class in nunjucks/src/runtime.js.
Remediation
Upgrade nunjucks
to version 3.2.3 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: body-parser@1.16.1 and express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › qs@6.2.1Remediation: Upgrade to body-parser@1.17.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › qs@6.2.0Remediation: Upgrade to express@4.15.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › qs@6.2.1Remediation: Upgrade to body-parser@1.17.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › qs@6.2.0Remediation: Upgrade to express@4.15.2.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Override Protection Bypass. By default qs
protects against attacks that attempt to overwrite an object's existing prototype properties, such as toString()
, hasOwnProperty()
,etc.
From qs
documentation:
By default parameters that would overwrite properties on the object prototype are ignored, if you wish to keep the data from those fields either use plainObjects as mentioned above, or set allowPrototypes to true which will allow user input to overwrite those properties. WARNING It is generally a bad idea to enable this option as it can cause problems when attempting to use the properties that have been overwritten. Always be careful with this option.
Overwriting these properties can impact application logic, potentially allowing attackers to work around security controls, modify data, make the application unstable and more.
In versions of the package affected by this vulnerability, it is possible to circumvent this protection and overwrite prototype properties and functions by prefixing the name of the parameter with [
or ]
. e.g. qs.parse("]=toString")
will return {toString = true}
, as a result, calling toString()
on the object will throw an exception.
Example:
qs.parse('toString=foo', { allowPrototypes: false })
// {}
qs.parse("]=toString", { allowPrototypes: false })
// {toString = true} <== prototype overwritten
For more information, you can check out our blog.
Disclosure Timeline
- February 13th, 2017 - Reported the issue to package owner.
- February 13th, 2017 - Issue acknowledged by package owner.
- February 16th, 2017 - Partial fix released in versions
6.0.3
,6.1.1
,6.2.2
,6.3.1
. - March 6th, 2017 - Final fix released in versions
6.4.0
,6.3.2
,6.2.3
,6.1.2
and6.0.4
Remediation
Upgrade qs
to version 6.0.4, 6.1.2, 6.2.3, 6.3.2 or higher.
References
high severity
- Vulnerable module: qs
- Introduced through: body-parser@1.16.1 and express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › qs@6.2.1Remediation: Upgrade to body-parser@1.19.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › qs@6.2.0Remediation: Upgrade to express@4.17.3.
Overview
qs is a querystring parser that supports nesting and arrays, with a depth limit.
Affected versions of this package are vulnerable to Prototype Poisoning which allows attackers to cause a Node process to hang, processing an Array object whose prototype has been replaced by one with an excessive length value.
Note: In many typical Express use cases, an unauthenticated remote attacker can place the attack payload in the query string of the URL that is used to visit the application, such as a[__proto__]=b&a[__proto__]&a[length]=100000000
.
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 qs
to version 6.2.4, 6.3.3, 6.4.1, 6.5.3, 6.6.1, 6.7.3, 6.8.3, 6.9.7, 6.10.3 or higher.
References
high severity
- Vulnerable module: semver
- Introduced through: pg@6.1.2
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › pg@6.1.2 › semver@4.3.2Remediation: Upgrade to pg@8.4.0.
Overview
semver is a semantic version parser used by npm.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range
, when untrusted user data is provided as a range.
PoC
const semver = require('semver')
const lengths_2 = [2000, 4000, 8000, 16000, 32000, 64000, 128000]
console.log("n[+] Valid range - Test payloads")
for (let i = 0; i =1.2.3' + ' '.repeat(lengths_2[i]) + '<1.3.0';
const start = Date.now()
semver.validRange(value)
// semver.minVersion(value)
// semver.maxSatisfying(["1.2.3"], value)
// semver.minSatisfying(["1.2.3"], value)
// new semver.Range(value, {})
const end = Date.now();
console.log('length=%d, time=%d ms', value.length, end - start);
}
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:
- CCC
- CC+C
- C+CC
- 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 semver
to version 5.7.2, 6.3.1, 7.5.2 or higher.
References
high severity
- Vulnerable module: unset-value
- Introduced through: nunjucks@3.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › readdirp@2.2.1 › micromatch@3.1.10 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › readdirp@2.2.1 › micromatch@3.1.10 › braces@2.3.2 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › readdirp@2.2.1 › micromatch@3.1.10 › extglob@2.0.4 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › readdirp@2.2.1 › micromatch@3.1.10 › nanomatch@1.2.13 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › readdirp@2.2.1 › micromatch@3.1.10 › extglob@2.0.4 › expand-brackets@2.1.4 › snapdragon@0.8.2 › base@0.11.2 › cache-base@1.0.1 › unset-value@1.0.0
Overview
Affected versions of this package are vulnerable to Prototype Pollution via the unset
function in index.js
, because it allows access to object prototype properties.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade unset-value
to version 2.0.1 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.12.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The function defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
using a constructor
payload.
PoC by Snyk
const mergeFn = require('lodash').defaultsDeep;
const payload = '{"constructor": {"prototype": {"a0": true}}}'
function check() {
mergeFn({}, JSON.parse(payload));
if (({})[`a0`] === true) {
console.log(`Vulnerable to Prototype Pollution via ${payload}`);
}
}
check();
For more information, check out our blog post
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.12 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.17.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution via the set
and setwith
functions due to improper user input sanitization.
PoC
lod = require('lodash')
lod.set({}, "__proto__[test2]", "456")
console.log(Object.prototype)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.17 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.11.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The functions merge
, mergeWith
, and defaultsDeep
could be tricked into adding or modifying properties of Object.prototype
. This is due to an incomplete fix to CVE-2018-3721
.
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.11 or higher.
References
high severity
- Vulnerable module: nconf
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-config@1.0.1 › nconf@0.7.2Remediation: Upgrade to snyk@1.465.0.
Overview
nconf is a Hierarchical node.js configuration with files, environment variables, command-line arguments, and atomic object merging.
Affected versions of this package are vulnerable to Prototype Pollution. When using the memory
engine, it is possible to store a nested JSON representation of the configuration. The .set()
function, that is responsible for setting the configuration properties, is vulnerable to Prototype Pollution. By providing a crafted property, it is possible to modify the properties on the Object.prototype
.
PoC
const nconf = require('nconf');
nconf.use('memory')
console.log({}.polluted)
nconf.set('__proto__:polluted', 'yes')
console.log({}.polluted)
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade nconf
to version 0.11.4 or higher.
References
high severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1Remediation: Upgrade to trailpack-sequelize@2.0.2.
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to Hash Injection. Using specially crafted requests an attacker can bypass secret_token
protections on websites using sequalize.
For example:
db.Token.findOne({
where: {
token: req.query.token
}
);
Node.js and other platforms allow nested parameters, i.e. token[$gt]=1
will be transformed into token = {"$gt":1}
. When such a hash is passed into sequalize
it will consider it a query (greater than 1) and find the first token in the DB, bypassing security of this endpoint.
Remediation
Upgrade sequelize
to version 4.12.0 or higher.
References
high severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.21.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Command Injection via template
.
PoC
var _ = require('lodash');
_.template('', { variable: '){console.log(process.env)}; with(obj' })()
Remediation
Upgrade lodash
to version 4.17.21 or higher.
References
high severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to SQL Injection due to an improper escaping for multiple appearances of $
in a string.
Remediation
Upgrade sequelize
to version 6.21.2 or higher.
References
medium severity
- Vulnerable module: i18next
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › i18next@3.4.1Remediation: Upgrade to trails@2.0.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › i18next@3.4.1Remediation: Upgrade to trails@2.0.2.
Overview
i18next
is i18next internationalization framework.
Affected versions of the package are vulnerable to Cross-site Scripting (XSS) due to not escaping variables as expected. When passing any interpolation
options without including escapeValue
, the function this.escapeValue
will get set to undefined
in Interpolator
. Meaning values aren't being escaped even though users expect them to be.
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
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.
Types of attacks
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. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade i18next
to version 3.4.4 or higher.
References
medium severity
- Vulnerable module: request
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › request@2.88.2
Overview
request is a simplified http request client.
Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) due to insufficient checks in the lib/redirect.js
file by allowing insecure redirects in the default configuration, via an attacker-controller server that does a cross-protocol redirect (HTTP to HTTPS, or HTTPS to HTTP).
NOTE: request
package has been deprecated, so a fix is not expected. See https://github.com/request/request/issues/3142.
Remediation
A fix was pushed into the master
branch but not yet published.
References
medium severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1Remediation: Upgrade to trailpack-sequelize@2.0.2.
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to Denial of Service (DoS). The afterResults
function for the SQLite dialect fails to catch a TypeError
exception for the results
variable. This allows attackers to submit malicious input that forces the exception and crashes the Node process.
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:
- CCC
- CC+C
- C+CC
- 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 sequelize
to version 4.44.4 or higher.
References
medium severity
- Vulnerable module: tough-cookie
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › request@2.88.2 › tough-cookie@2.5.0
Overview
tough-cookie is a RFC6265 Cookies and CookieJar module for Node.js.
Affected versions of this package are vulnerable to Prototype Pollution due to improper handling of Cookies when using CookieJar in rejectPublicSuffixes=false
mode. Due to an issue with the manner in which the objects are initialized, an attacker can expose or modify a limited amount of property information on those objects. There is no impact to availability.
PoC
// PoC.js
async function main(){
var tough = require("tough-cookie");
var cookiejar = new tough.CookieJar(undefined,{rejectPublicSuffixes:false});
// Exploit cookie
await cookiejar.setCookie(
"Slonser=polluted; Domain=__proto__; Path=/notauth",
"https://__proto__/admin"
);
// normal cookie
var cookie = await cookiejar.setCookie(
"Auth=Lol; Domain=google.com; Path=/notauth",
"https://google.com/"
);
//Exploit cookie
var a = {};
console.log(a["/notauth"]["Slonser"])
}
main();
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade tough-cookie
to version 4.1.3 or higher.
References
medium severity
- Vulnerable module: snyk
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0Remediation: Upgrade to snyk@1.996.0.
Overview
snyk is an advanced tool that scans and monitors projects for security vulnerabilities.
Affected versions of this package are vulnerable to Command Injection via the snyk-go-plugin
which is used by the Snyk CLI tool.
A successful exploit, allows attackers to run arbitrary commands on the host system where the Snyk CLI is installed. In order to exploit this vulnerability, a target would have to execute the “snyk test” command on untrusted files. As developers are unlikely to run "snyk test" on untrusted files, an attacker might have to trick them into opening a malicious file before running "snyk test".
Remediation
Upgrade snyk
to version 1.996.0 or higher.
References
medium severity
- Vulnerable module: dot-prop
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › configstore@2.1.0 › dot-prop@3.0.0
Overview
dot-prop is a package to get, set, or delete a property from a nested object using a dot path.
Affected versions of this package are vulnerable to Prototype Pollution. It is possible for a user to modify the prototype of a base object.
PoC by aaron_costello
var dotProp = require("dot-prop")
const object = {};
console.log("Before " + object.b); //Undefined
dotProp.set(object, '__proto__.b', true);
console.log("After " + {}.b); //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:
- CCC
- CC+C
- C+CC
- 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 dot-prop
to version 4.2.1, 5.1.1 or higher.
References
medium severity
- Vulnerable module: hoek
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › hoek@4.1.0Remediation: Upgrade to trails@2.0.2.
Overview
hoek is an Utility methods for the hapi ecosystem.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
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:
- CCC
- CC+C
- C+CC
- 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 hoek
to version 4.2.1, 5.0.3 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var _= require('lodash');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
_.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade lodash
to version 4.17.5 or higher.
References
medium severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to Access of Resource Using Incompatible Type ('Type Confusion') due to improper user-input sanitization, due to unsafe fall-through in GET WHERE
conditions.
Remediation
Upgrade sequelize
to version 6.28.1 or higher.
References
medium severity
- Vulnerable module: undefsafe
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › undefsafe@0.0.3Remediation: Upgrade to snyk@1.78.0.
Overview
undefsafe is a Simple function for retrieving deep object properties without getting "Cannot read property 'X' of undefined".
Affected versions of this package are vulnerable to Prototype Pollution. The a
function could be tricked into adding or modifying properties of Object.prototype
using a __proto__
payload.
PoC by JHU System Security Lab
var a = require("undefsafe");
var payload = "__proto__.toString";
a({},payload,"JHU");
console.log({}.toString);
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:
- CCC
- CC+C
- C+CC
- 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 undefsafe
to version 2.0.3 or higher.
References
medium severity
- Vulnerable module: inflight
- Introduced through: trailpack-cache@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-cache@2.0.0 › cache-manager-fs-binary@1.0.4 › glob@7.2.3 › inflight@1.0.6
Overview
Affected versions of this package are vulnerable to Missing Release of Resource after Effective Lifetime via the makeres
function due to improperly deleting keys from the reqs
object after execution of callbacks. This behavior causes the keys to remain in the reqs
object, which leads to resource exhaustion.
Exploiting this vulnerability results in crashing the node
process or in the application crash.
Note: This library is not maintained, and currently, there is no fix for this issue. To overcome this vulnerability, several dependent packages have eliminated the use of this library.
To trigger the memory leak, an attacker would need to have the ability to execute or influence the asynchronous operations that use the inflight module within the application. This typically requires access to the internal workings of the server or application, which is not commonly exposed to remote users. Therefore, “Attack vector” is marked as “Local”.
PoC
const inflight = require('inflight');
function testInflight() {
let i = 0;
function scheduleNext() {
let key = `key-${i++}`;
const callback = () => {
};
for (let j = 0; j < 1000000; j++) {
inflight(key, callback);
}
setImmediate(scheduleNext);
}
if (i % 100 === 0) {
console.log(process.memoryUsage());
}
scheduleNext();
}
testInflight();
Remediation
There is no fixed version for inflight
.
References
medium severity
- Vulnerable module: express
- Introduced through: express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1Remediation: Upgrade to express@4.19.2.
Overview
express is a minimalist web framework.
Affected versions of this package are vulnerable to Open Redirect due to the implementation of URL encoding using encodeurl
before passing it to the location
header. This can lead to unexpected evaluations of malformed URLs by common redirect allow list implementations in applications, allowing an attacker to bypass a properly implemented allow list and redirect users to malicious sites.
Remediation
Upgrade express
to version 4.19.2, 5.0.0-beta.3 or higher.
References
medium severity
- Vulnerable module: nunjucks
- Introduced through: nunjucks@3.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0Remediation: Upgrade to nunjucks@3.2.4.
Overview
nunjucks is a powerful templating engine with inheritance, asynchronous control, and more (jinja2 inspired).
Affected versions of this package are vulnerable to Cross-site Scripting (XSS) in the second parameter, when more than one user-controlled parameter is used on the same line in a view. Autoescaping can be bypassed by including a \
in the user input string.
PoC
https://<application-url>/?lang=jp\&place=};alert(document.domain)//
Details
A cross-site scripting attack occurs when the attacker tricks a legitimate web-based application or site to accept a request as originating from a trusted source.
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.
Types of attacks
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. |
Affected environments
The following environments are susceptible to an XSS attack:
- Web servers
- Application servers
- Web application environments
How to prevent
This section describes the top best practices designed to specifically protect your code:
- Sanitize data input in an HTTP request before reflecting it back, ensuring all data is validated, filtered or escaped before echoing anything back to the user, such as the values of query parameters during searches.
- Convert special characters such as
?
,&
,/
,<
,>
and spaces to their respective HTML or URL encoded equivalents. - Give users the option to disable client-side scripts.
- Redirect invalid requests.
- Detect simultaneous logins, including those from two separate IP addresses, and invalidate those sessions.
- Use and enforce a Content Security Policy (source: Wikipedia) to disable any features that might be manipulated for an XSS attack.
- Read the documentation for any of the libraries referenced in your code to understand which elements allow for embedded HTML.
Remediation
Upgrade nunjucks
to version 3.2.4 or higher.
References
medium severity
- Vulnerable module: snyk
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0Remediation: Upgrade to snyk@1.1064.0.
Overview
snyk is a advanced tool that scans and monitors projects for security vulnerabilities.
Affected versions of this package are vulnerable to Code Injection.
when analyzing a project. An attacker who can convince a user to scan a malicious project can include
commands in a build file such as build.gradle
or gradle-wrapper.jar
, which will be executed with the privileges of the application.
This vulnerability may be triggered when running the the CLI tool directly, or when running a scan with one of the IDE plugins that invoke the Snyk CLI.
Successful exploitation of this issue would likely require some level of social engineering - to coerce an untrusted project to be downloaded and analyzed via the Snyk CLI or opened in an IDE where a Snyk IDE plugin is installed and enabled. Additionally, if the IDE has a Trust feature then the target folder must be marked as ‘trusted’ in order to be vulnerable.
NOTE: This issue is independent of the one reported in CVE-2022-40764, and upgrading to a fixed version for this addresses that issue as well.
The affected IDE plugins and versions are:
- VS Code - Affected: <=1.8.0, Fixed: 1.9.0
- IntelliJ - Affected: <=2.4.47, Fixed: 2.4.48
- Visual Studio - Affected: <=1.1.30, Fixed: 1.1.31
- Eclipse - Affected: <=v20221115, Fixed: v20221130
- Language Server - Affected: <=v20221109, Fixed: v20221130
Remediation
Upgrade snyk
to version 1.1064.0 or higher.
References
medium severity
- Vulnerable module: minimist
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › mkdirp@0.5.1 › minimist@0.0.8Remediation: Upgrade to trails@2.0.2.
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype
using a constructor
or __proto__
payload.
PoC by Snyk
require('minimist')('--__proto__.injected0 value0'.split(' '));
console.log(({}).injected0 === 'value0'); // true
require('minimist')('--constructor.prototype.injected1 value1'.split(' '));
console.log(({}).injected1 === 'value1'); // true
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 0.2.1, 1.2.3 or higher.
References
medium severity
- Vulnerable module: yargs-parser
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › yargs@4.8.1 › yargs-parser@2.4.1
Overview
yargs-parser is a mighty option parser used by yargs.
Affected versions of this package are vulnerable to Prototype Pollution. The library could be tricked into adding or modifying properties of Object.prototype
using a __proto__
payload.
Our research team checked several attack vectors to verify this vulnerability:
- It could be used for privilege escalation.
- The library could be used to parse user input received from different sources:
- terminal emulators
- system calls from other code bases
- CLI RPC servers
PoC by Snyk
const parser = require("yargs-parser");
console.log(parser('--foo.__proto__.bar baz'));
console.log(({}).bar);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade yargs-parser
to version 5.0.1, 13.1.2, 15.0.1, 18.1.1 or higher.
References
medium severity
- Vulnerable module: got
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-resolve-deps@1.7.0 › clite@0.3.0 › update-notifier@0.6.3 › latest-version@2.0.0 › package-json@2.4.0 › got@5.7.1
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › update-notifier@0.5.0 › latest-version@1.0.1 › package-json@1.2.0 › got@3.3.1Remediation: Upgrade to snyk@1.73.0.
Overview
Affected versions of this package are vulnerable to Open Redirect due to missing verification of requested URLs. It allowed a victim to be redirected to a UNIX socket.
Remediation
Upgrade got
to version 11.8.5, 12.1.0 or higher.
References
medium severity
- Vulnerable module: glob-parent
- Introduced through: nunjucks@3.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › glob-parent@2.0.0Remediation: Upgrade to nunjucks@3.2.1.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › anymatch@1.3.2 › micromatch@2.3.11 › parse-glob@3.0.4 › glob-base@0.3.0 › glob-parent@2.0.0
Overview
glob-parent is a package that helps extracting the non-magic parent path from a glob string.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). The enclosure
regex used to check for strings ending in enclosure containing path separator.
PoC by Yeting Li
var globParent = require("glob-parent")
function build_attack(n) {
var ret = "{"
for (var i = 0; i < n; i++) {
ret += "/"
}
return ret;
}
globParent(build_attack(5000));
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:
- CCC
- CC+C
- C+CC
- 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 glob-parent
to version 5.1.2 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.21.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the toNumber
, trim
and trimEnd
functions.
POC
var lo = require('lodash');
function build_blank (n) {
var ret = "1"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret + "1";
}
var s = build_blank(50000)
var time0 = Date.now();
lo.trim(s)
var time_cost0 = Date.now() - time0;
console.log("time_cost0: " + time_cost0)
var time1 = Date.now();
lo.toNumber(s)
var time_cost1 = Date.now() - time1;
console.log("time_cost1: " + time_cost1)
var time2 = Date.now();
lo.trimEnd(s)
var time_cost2 = Date.now() - time2;
console.log("time_cost2: " + time_cost2)
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:
- CCC
- CC+C
- C+CC
- 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 lodash
to version 4.17.21 or higher.
References
medium severity
- Vulnerable module: minimatch
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0 › snyk-recursive-readdir@2.0.0 › minimatch@3.0.2
Overview
minimatch is a minimal matching utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the braceExpand
function in minimatch.js
.
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:
- CCC
- CC+C
- C+CC
- 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 minimatch
to version 3.0.5 or higher.
References
medium severity
- Vulnerable module: sequelize
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1
Overview
sequelize is a promise-based Node.js ORM for Postgres, MySQL, MariaDB, SQLite and Microsoft SQL Server.
Affected versions of this package are vulnerable to Information Exposure due to improper user-input, by allowing an attacker to create malicious queries leading to SQL errors.
Remediation
Upgrade sequelize
to version 6.28.1 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1 › validator@5.7.0
Overview
validator is 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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: validator
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1 › validator@5.7.0
Overview
validator is 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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: validator
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1 › validator@5.7.0
Overview
validator is 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:
- CCC
- CC+C
- C+CC
- 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
- Vulnerable module: snyk
- Introduced through: snyk@1.25.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › snyk@1.25.0Remediation: Upgrade to snyk@1.1064.0.
Overview
snyk is an advanced tool that scans and monitors projects for security vulnerabilities.
Affected versions of this package are vulnerable to Command Injection due to an incomplete fix for CVE-2022-40764.
A successful exploit allows attackers to run arbitrary commands on the host system where the Snyk CLI is installed by passing in crafted command line flags.
In order to exploit this vulnerability, a user would have to execute the snyk test
command on untrusted files. In most cases, an attacker positioned to control the command line arguments to the Snyk CLI would already be positioned to execute arbitrary commands. However, this could be abused in specific scenarios, such as continuous integration pipelines, where developers can control the arguments passed to the Snyk CLI to leverage this component as part of a wider attack against an integration/build pipeline.
This issue has been addressed in the latest Snyk Docker images available at https://hub.docker.com/r/snyk/snyk as of 2022-11-29. Images downloaded and built prior to that date should be updated.
The issue has also been addressed in the Snyk TeamCity CI/CD plugin as of version v20221130.093605.
Remediation
Upgrade snyk
to version 1.1064.0 or higher.
References
medium severity
- Vulnerable module: i18next
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › i18next@3.4.1Remediation: Upgrade to trails@3.0.0.
Overview
i18next is an internationalization framework for browser or any other javascript environment (eg. node.js).
Affected versions of this package are vulnerable to Buffer Overflow. It is possible to cause buffer overflow by changing the translation to be recursive.
Remediation
Upgrade i18next
to version 19.5.5 or higher.
References
medium severity
- Vulnerable module: i18next
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › i18next@3.4.1Remediation: Upgrade to trails@3.0.0.
Overview
i18next is an internationalization framework for browser or any other javascript environment (eg. node.js).
Affected versions of this package are vulnerable to Prototype Pollution. This vulnerability relates to the AddResourceBundle
API which uses the the deepExtend
function (https://github.com/i18next/i18next/blob/master/i18next.js#L361-L370
) internally to extend existing translations in a file. Depending on if user input is provided, an attacker can overwrite and pollute the object prototype of a program.
PoC
import i18n from "i18next";
i18n.init({
resources: {
en: {
namespace1: {
key: 'hello from namespace 1'
},
namespace2: {
key: 'hello from namespace 2'
}
},
de: {
namespace1: {
key: 'hallo von namespace 1'
},
namespace2: {
key: 'hallo von namespace 2'
}
}
}
});
var malicious_payload = '{"__proto__":{"vulnerable":"Polluted"}}';
i18n.init({ resources: {} });
i18n.addResourceBundle('en', 'namespace1', JSON.parse(malicious_payload)
,true,true);
console.log(i18n.options.resources);
//a newly created empty object has the vulnerable property
console.log({}.vulnerable);
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade i18next
to version 19.8.3 or higher.
References
medium severity
- Vulnerable module: lodash
- Introduced through: lodash@4.17.4 and trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › lodash@4.17.4Remediation: Upgrade to lodash@4.17.11.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › lodash@4.17.2Remediation: Upgrade to trails@2.0.2.
Overview
lodash is a modern JavaScript utility library delivering modularity, performance, & extras.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It parses dates using regex strings, which may cause a slowdown of 2 seconds per 50k characters.
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:
- CCC
- CC+C
- C+CC
- 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 lodash
to version 4.17.11 or higher.
References
low severity
- Vulnerable module: braces
- Introduced through: nunjucks@3.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › anymatch@1.3.2 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to nunjucks@3.1.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › nunjucks@3.0.0 › chokidar@1.7.0 › anymatch@1.3.2 › micromatch@2.3.11 › braces@1.8.5Remediation: Upgrade to nunjucks@3.1.3.
Overview
braces is a Bash-like brace expansion, implemented in JavaScript.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\{(,+(?:(\{,+\})*),*|,*(?:(\{,+\})*),+)\}
) in order to detects empty braces. This can cause an impact of about 10 seconds matching time for data 50K characters long.
Disclosure Timeline
- Feb 15th, 2018 - Initial Disclosure to package owner
- Feb 16th, 2018 - Initial Response from package owner
- Feb 18th, 2018 - Fix issued
- Feb 19th, 2018 - Vulnerability published
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:
- CCC
- CC+C
- C+CC
- 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 braces
to version 2.3.1 or higher.
References
low severity
- Vulnerable module: debug
- Introduced through: body-parser@1.16.1 and express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › debug@2.6.1Remediation: Upgrade to body-parser@1.18.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › finalhandler@0.5.1 › debug@2.2.0Remediation: Upgrade to express@4.15.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › debug@2.6.1Remediation: Upgrade to body-parser@1.18.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › finalhandler@0.5.1 › debug@2.2.0Remediation: Upgrade to express@4.15.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0Remediation: Upgrade to express@4.15.5.
Overview
debug is a small debugging utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the function useColors
via manipulation of the str
argument.
The vulnerability can cause a very low impact of about 2 seconds of matching time for data 50k characters long.
Note: CVE-2017-20165 is a duplicate of this vulnerability.
PoC
Use the following regex in the %o
formatter.
/\s*\n\s*/
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:
- CCC
- CC+C
- C+CC
- 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 debug
to version 2.6.9, 3.1.0, 3.2.7, 4.3.1 or higher.
References
low severity
- Vulnerable module: mime
- Introduced through: express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › mime@1.3.4Remediation: Upgrade to express@4.16.0.
Overview
mime is a comprehensive, compact MIME type module.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It uses regex the following regex /.*[\.\/\\]/
in its lookup, which can cause a slowdown of 2 seconds for 50k characters.
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:
- CCC
- CC+C
- C+CC
- 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 mime
to version 1.4.1, 2.0.3 or higher.
References
low severity
- Vulnerable module: minimist
- Introduced through: trails@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trails@2.0.0 › mkdirp@0.5.1 › minimist@0.0.8Remediation: Upgrade to trails@2.0.2.
Overview
minimist is a parse argument options module.
Affected versions of this package are vulnerable to Prototype Pollution due to a missing handler to Function.prototype
.
Notes:
This vulnerability is a bypass to CVE-2020-7598
The reason for the different CVSS between CVE-2021-44906 to CVE-2020-7598, is that CVE-2020-7598 can pollute objects, while CVE-2021-44906 can pollute only function.
PoC by Snyk
require('minimist')('--_.constructor.constructor.prototype.foo bar'.split(' '));
console.log((function(){}).foo); // bar
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade minimist
to version 0.2.4, 1.2.6 or higher.
References
low severity
- Vulnerable module: moment
- Introduced through: moment@2.17.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › moment@2.17.1Remediation: Upgrade to moment@2.19.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › moment@2.17.1Remediation: Upgrade to moment@2.19.3.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (/[0-9]*['a-z\u00A0-\u05FF\u0700-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]+|[\u0600-\u06FF\/]+(\s*?[\u0600-\u06FF]+){1,2}/i
) in order to parse dates specified as strings. This can cause a very low impact of about 2 seconds matching time for data 50k characters long.
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:
- CCC
- CC+C
- C+CC
- 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 moment
to version 2.19.3 or higher.
References
low severity
- Vulnerable module: ms
- Introduced through: body-parser@1.16.1 and express@4.14.1
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › debug@2.6.1 › ms@0.7.2Remediation: Upgrade to body-parser@1.17.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › ms@0.7.2Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › ms@0.7.2Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › finalhandler@0.5.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › body-parser@1.16.1 › debug@2.6.1 › ms@0.7.2Remediation: Upgrade to body-parser@1.17.2.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › ms@0.7.2Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › ms@0.7.2Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › finalhandler@0.5.1 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.0.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › send@0.14.2 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › express@4.14.1 › serve-static@1.11.2 › send@0.14.2 › debug@2.2.0 › ms@0.7.1Remediation: Upgrade to express@4.15.3.
Overview
ms
is a tiny millisecond conversion utility.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to an incomplete fix for previously reported vulnerability npm:ms:20151024. The fix limited the length of accepted input string to 10,000 characters, and turned to be insufficient making it possible to block the event loop for 0.3 seconds (on a typical laptop) with a specially crafted string passed to ms()
function.
Proof of concept
ms = require('ms');
ms('1'.repeat(9998) + 'Q') // Takes about ~0.3s
Note: Snyk's patch for this vulnerability limits input length to 100 characters. This new limit was deemed to be a breaking change by the author. Based on user feedback, we believe the risk of breakage is very low, while the value to your security is much greater, and therefore opted to still capture this change in a patch for earlier versions as well. Whenever patching security issues, we always suggest to run tests on your code to validate that nothing has been broken.
For more information on Regular Expression Denial of Service (ReDoS)
attacks, go to our blog.
Disclosure Timeline
- Feb 9th, 2017 - Reported the issue to package owner.
- Feb 11th, 2017 - Issue acknowledged by package owner.
- April 12th, 2017 - Fix PR opened by Snyk Security Team.
- May 15th, 2017 - Vulnerability published.
- May 16th, 2017 - Issue fixed and version
2.0.0
released. - May 21th, 2017 - Patches released for versions
>=0.7.1, <=1.0.0
.
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:
- CCC
- CC+C
- C+CC
- 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 ms
to version 2.0.0 or higher.
References
low severity
- Vulnerable module: validator
- Introduced through: trailpack-sequelize@2.0.0
Detailed paths
-
Introduced through: statszee@lobetia/statszee#90dd96620937f01599e6e17dc70a5d3824d6ecb8 › trailpack-sequelize@2.0.0 › sequelize@3.35.1 › validator@5.7.0Remediation: Upgrade to trailpack-sequelize@2.0.2.
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). It used a regular expression (^\s*data:([a-z]+\/[a-z0-9\-\+]+(;[a-z\-]+=[a-z0-9\-]+)?)?(;base64)?,[a-z0-9!\$&',\(\)\*\+,;=\-\._~:@\/\?%\s]*\s*$
) in order to validate Data URIs. This can cause an impact of about 10 seconds matching time for data 70K characters long.
Disclosure Timeline
- Feb 15th, 2018 - Initial Disclosure to package owner
- Feb 16th, 2018 - Initial Response from package owner
- Feb 18th, 2018 - Fix issued
- Feb 18th, 2018 - Vulnerability published
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:
- CCC
- CC+C
- C+CC
- 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 9.4.1 or higher.