bifravst/aws
Find, fix and prevent vulnerabilities in your code.
high severity
- Vulnerable module: jsonata
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › jsonata@1.8.4
Overview
jsonata is a JSON query and transformation language
Affected versions of this package are vulnerable to Prototype Pollution due to the use of the transform
operator to override properties on the Object
constructor and prototype. An attack can lead to denial of service, remote code execution, or other unexpected behavior in applications that evaluate user-provided expressions by crafting malicious expressions.
Workaround
This vulnerability can be mitigated by applying a specific patch if updating is not possible. The patch involves modifications to the jsonata.js
file to prevent overriding properties on the Object
constructor and 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 jsonata
to version 1.8.7, 2.0.4 or higher.
References
high severity
- Vulnerable module: fast-xml-parser
- Introduced through: @aws-sdk/client-cloudformation@3.3.0, @aws-sdk/client-s3@3.3.0 and others
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-cloudformation@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-cloudformation@3.347.1.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-s3@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-s3@3.6.3.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-sqs@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-sqs@3.327.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-sts@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-sts@3.54.2.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/cloudformation-helpers@5.0.2 › @aws-sdk/client-cloudformation@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @bifravst/cloudformation-helpers@9.1.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › @aws-sdk/client-sqs@3.4.1 › fast-xml-parser@3.21.1
…and 3 more
Overview
fast-xml-parser is a Validate XML, Parse XML, Build XML without C/C++ based libraries
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) due to allowing special characters in entity names, which are not escaped or sanitized. An attacker can inject an inefficient regex in the entity replacement step of the parser, this can cause the parser to stall for an indefinite amount of time.
Workaround
This vulnerability can be avoided by not parsing DOCTYPE
data with the processEntities: false
option.
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 fast-xml-parser
to version 4.2.4 or higher.
References
high severity
- Vulnerable module: ws
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › ws@7.4.2
Overview
ws is a simple to use websocket client, server and console for node.js.
Affected versions of this package are vulnerable to Denial of Service (DoS) when the number of received headers exceed the server.maxHeadersCount
or request.maxHeadersCount
threshold.
Workaround
This issue can be mitigating by following these steps:
Reduce the maximum allowed length of the request headers using the
--max-http-header-size=size
and/or themaxHeaderSize
options so that no more headers than theserver.maxHeadersCount
limit can be sent.Set
server.maxHeadersCount
to 0 so that no limit is applied.
PoC
const http = require('http');
const WebSocket = require('ws');
const server = http.createServer();
const wss = new WebSocket.Server({ server });
server.listen(function () {
const chars = "!#$%&'*+-.0123456789abcdefghijklmnopqrstuvwxyz^_`|~".split('');
const headers = {};
let count = 0;
for (let i = 0; i < chars.length; i++) {
if (count === 2000) break;
for (let j = 0; j < chars.length; j++) {
const key = chars[i] + chars[j];
headers[key] = 'x';
if (++count === 2000) break;
}
}
headers.Connection = 'Upgrade';
headers.Upgrade = 'websocket';
headers['Sec-WebSocket-Key'] = 'dGhlIHNhbXBsZSBub25jZQ==';
headers['Sec-WebSocket-Version'] = '13';
const request = http.request({
headers: headers,
host: '127.0.0.1',
port: server.address().port
});
request.end();
});
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 ws
to version 5.2.4, 6.2.3, 7.5.10, 8.17.1 or higher.
References
medium severity
- Vulnerable module: fast-xml-parser
- Introduced through: @aws-sdk/client-cloudformation@3.3.0, @aws-sdk/client-s3@3.3.0 and others
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-cloudformation@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-cloudformation@3.529.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-s3@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-s3@3.529.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-sqs@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-sqs@3.327.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-sts@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-sts@3.186.4.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/cloudformation-helpers@5.0.2 › @aws-sdk/client-cloudformation@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @bifravst/cloudformation-helpers@9.1.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › @aws-sdk/client-sqs@3.4.1 › fast-xml-parser@3.21.1
…and 3 more
Overview
fast-xml-parser is a Validate XML, Parse XML, Build XML without C/C++ based libraries
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in currency.js
, which can be triggered by supplying excessively long strings such as '\t'.repeat(13337) + '.'
Note: The vulnerability is in the experimental "v5" functionality that is included in version 4.x during development, at the time of discovery.
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 fast-xml-parser
to version 4.4.1 or higher.
References
medium severity
- Vulnerable module: fast-xml-parser
- Introduced through: @aws-sdk/client-cloudformation@3.3.0, @aws-sdk/client-s3@3.3.0 and others
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-cloudformation@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-cloudformation@3.276.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-s3@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-s3@3.6.2.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-sqs@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-sqs@3.276.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @aws-sdk/client-sts@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @aws-sdk/client-sts@3.54.2.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/cloudformation-helpers@5.0.2 › @aws-sdk/client-cloudformation@3.3.0 › fast-xml-parser@3.21.1Remediation: Upgrade to @bifravst/cloudformation-helpers@9.1.0.
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › @aws-sdk/client-sqs@3.4.1 › fast-xml-parser@3.21.1
…and 3 more
Overview
fast-xml-parser is a Validate XML, Parse XML, Build XML without C/C++ based libraries
Affected versions of this package are vulnerable to Prototype Pollution due to improper argument validation, which is exploitable via the aName
variable.
PoC
const { XMLParser, XMLBuilder, XMLValidator} = require("fast-xml-parser");
let XMLdata = "<__proto__><polluted>hacked</polluted></__proto__>"
const parser = new XMLParser();
let jObj = parser.parse(XMLdata);
console.log(jObj.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 fast-xml-parser
to version 4.1.2 or higher.
References
medium severity
- Vulnerable module: node-fetch
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › node-fetch@2.6.1
Overview
node-fetch is a light-weight module that brings window.fetch to node.js
Affected versions of this package are vulnerable to Information Exposure when fetching a remote url with Cookie, if it get a Location
response header, it will follow that url and try to fetch that url with provided cookie. This can lead to forwarding secure headers to 3th party.
Remediation
Upgrade node-fetch
to version 2.6.7, 3.1.1 or higher.
References
medium severity
- Vulnerable module: inflight
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › glob@7.1.6 › 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: ws
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › ws@7.4.2
Overview
ws is a simple to use websocket client, server and console for node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). A specially crafted value of the Sec-Websocket-Protocol
header can be used to significantly slow down a ws
server.
##PoC
for (const length of [1000, 2000, 4000, 8000, 16000, 32000]) {
const value = 'b' + ' '.repeat(length) + 'x';
const start = process.hrtime.bigint();
value.trim().split(/ *, */);
const end = process.hrtime.bigint();
console.log('length = %d, time = %f ns', 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 ws
to version 7.4.6, 6.2.2, 5.2.3 or higher.
References
medium severity
- Vulnerable module: xml2js
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › aws-sdk@2.834.0 › xml2js@0.4.19
Overview
Affected versions of this package are vulnerable to Prototype Pollution due to allowing an external attacker to edit or add new properties to an object. This is possible because the application does not properly validate incoming JSON keys, thus allowing the __proto__
property to be edited.
PoC
var parseString = require('xml2js').parseString;
let normal_user_request = "<role>admin</role>";
let malicious_user_request = "<__proto__><role>admin</role></__proto__>";
const update_user = (userProp) => {
// A user cannot alter his role. This way we prevent privilege escalations.
parseString(userProp, function (err, user) {
if(user.hasOwnProperty("role") && user?.role.toLowerCase() === "admin") {
console.log("Unauthorized Action");
} else {
console.log(user?.role[0]);
}
});
}
update_user(normal_user_request);
update_user(malicious_user_request);
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 xml2js
to version 0.5.0 or higher.
References
medium severity
new
- Module: paho-mqtt
- Introduced through: @bifravst/e2e-bdd-test-runner@5.1.6
Detailed paths
-
Introduced through: @bifravst/aws@bifravst/aws#2a939726535650d9eb9fa3a89fd779437db9928f › @bifravst/e2e-bdd-test-runner@5.1.6 › paho-mqtt@1.1.0
EPL-1.0 license