|2 via 2 paths|
Find, fix and prevent vulnerabilities in your code.
- Vulnerable module: json-schema
- Introduced through: firstname.lastname@example.org
Introduced through: email@example.com › firstname.lastname@example.org › email@example.com › firstname.lastname@example.org › email@example.com
Affected versions of this package are vulnerable to Prototype Pollution via the
validate function, which when given a special payload will pollute
Object with undesired attributes.
There are two main ways in which the pollution of prototypes occurs:
- Property 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
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object:
Hoek are examples of libraries susceptible to recursive merge attacks.
Property definition by path
theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to
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:
|Denial of service (DoS)||Client||This is the most likely attack.
DoS occurs when
The attacker pollutes
For example: if an attacker pollutes
|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.
|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
The following environments are susceptible to a Prototype Pollution attack:
- Application server
- Web server
How to prevent
- Freeze the prototype— use
- 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
For more information on this vulnerability type:
json-schema to version 0.4.0 or higher.
- Vulnerable module: node.extend
- Introduced through: firstname.lastname@example.org
Introduced through: email@example.com › firstname.lastname@example.org › email@example.com › firstname.lastname@example.org
node.extend is a port of jQuery.extend that actually works on node.js.
Affected versions of this package are vulnerable to Prototype Pollution. An attacker could inject arbitrary properties onto
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:
AThe 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.
DFinally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")' 0.04s user 0.01s system 95% cpu 0.052 total $ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")' 1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
|String||Number of C's||Number of steps|
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.
node.extend to version 1.1.7, 2.0.1 or higher.