Find, fix and prevent vulnerabilities in your code.
critical severity
- Vulnerable module: hawk
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › hawk@3.1.3
Overview
hawk is a library for the HTTP Hawk Authentication Scheme.
Affected versions of this package are vulnerable to Authentication Bypass. The incoming (client supplied) hash of the payload is trusted by the server and not verified before the signature is calculated.
A malicious actor in the middle can alter the payload and the server side will not identify the modification occurred because it simply uses the client provided value instead of verify the hash provided against the modified payload.
According to the maintainers this issue is to be considered out of scope as "payload hash validation is optional and up to developer to implement".
Remediation
There is no fixed version for hawk
.
References
high severity
- Vulnerable module: bl
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › bl@1.1.2
Overview
bl is a library that allows you to collect buffers and access with a standard readable buffer interface.
Affected versions of this package are vulnerable to Remote Memory Exposure. If user input ends up in consume()
argument and can become negative, BufferList state can be corrupted, tricking it into exposing uninitialized memory via regular .slice()
calls.
PoC by chalker
const { BufferList } = require('bl')
const secret = require('crypto').randomBytes(256)
for (let i = 0; i < 1e6; i++) {
const clone = Buffer.from(secret)
const bl = new BufferList()
bl.append(Buffer.from('a'))
bl.consume(-1024)
const buf = bl.slice(1)
if (buf.indexOf(clone) !== -1) {
console.error(`Match (at ${i})`, buf)
}
}
Remediation
Upgrade bl
to version 2.2.1, 3.0.1, 4.0.3, 1.2.3 or higher.
References
high severity
- Vulnerable module: ansi-regex
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › har-validator@2.0.6 › chalk@1.1.3 › has-ansi@2.0.0 › ansi-regex@2.1.1
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › har-validator@2.0.6 › chalk@1.1.3 › 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: fresh
- Introduced through: static-expiry@paulwalker/connect-static-expiry#87354eb859b503364d8d206130b71b258b3a2e80
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › static-expiry@paulwalker/connect-static-expiry#87354eb859b503364d8d206130b71b258b3a2e80 › fresh@0.3.0
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: hawk
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › hawk@3.1.3
Overview
hawk is a library for the HTTP Hawk Authentication Scheme.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in header parsing where each added character in the attacker's input increases the computation time exponentially.
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 hawk
to version 9.0.1 or higher.
References
medium severity
- Vulnerable module: jsonwebtoken
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › jsonwebtoken@5.4.1
Overview
jsonwebtoken is a JSON Web Token implementation (symmetric and asymmetric)
Affected versions of this package are vulnerable to Use of a Broken or Risky Cryptographic Algorithm such that the library can be misconfigured to use legacy, insecure key types for signature verification. For example, DSA keys could be used with the RS256 algorithm.
Exploitability
Users are affected when using an algorithm and a key type other than the combinations mentioned below:
EC: ES256, ES384, ES512
RSA: RS256, RS384, RS512, PS256, PS384, PS512
RSA-PSS: PS256, PS384, PS512
And for Elliptic Curve algorithms:
ES256: prime256v1
ES384: secp384r1
ES512: secp521r1
Workaround
Users who are unable to upgrade to the fixed version can use the allowInvalidAsymmetricKeyTypes
option to true
in the sign()
and verify()
functions to continue usage of invalid key type/algorithm combination in 9.0.0 for legacy compatibility.
Remediation
Upgrade jsonwebtoken
to version 9.0.0 or higher.
References
medium severity
- Vulnerable module: jsonwebtoken
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › jsonwebtoken@5.4.1
Overview
jsonwebtoken is a JSON Web Token implementation (symmetric and asymmetric)
Affected versions of this package are vulnerable to Improper Restriction of Security Token Assignment via the secretOrPublicKey
argument due to misconfigurations of the key retrieval function jwt.verify()
. Exploiting this vulnerability might result in incorrect verification of forged tokens when tokens signed with an asymmetric public key could be verified with a symmetric HS256 algorithm.
Note:
This vulnerability affects your application if it supports the usage of both symmetric and asymmetric keys in jwt.verify()
implementation with the same key retrieval function.
Remediation
Upgrade jsonwebtoken
to version 9.0.0 or higher.
References
medium severity
- Vulnerable module: request
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0
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: tough-cookie
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › tough-cookie@2.3.4
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: jsonwebtoken
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › jsonwebtoken@5.4.1
Overview
jsonwebtoken is a JSON Web Token implementation (symmetric and asymmetric)
Affected versions of this package are vulnerable to Improper Authentication such that the lack of algorithm definition in the jwt.verify()
function can lead to signature validation bypass due to defaulting to the none
algorithm for signature verification.
Exploitability
Users are affected only if all of the following conditions are true for the jwt.verify()
function:
A token with no signature is received.
No algorithms are specified.
A falsy (e.g.,
null
,false
,undefined
) secret or key is passed.
Remediation
Upgrade jsonwebtoken
to version 9.0.0 or higher.
References
medium severity
new
- Vulnerable module: cookie
- Introduced through: express@4.21.0
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › express@4.21.0 › cookie@0.6.0
Overview
Affected versions of this package are vulnerable to Cross-site Scripting (XSS) via the cookie name
, path
, or domain
, which can be used to set unexpected values to other cookie fields.
Workaround
Users who are not able to upgrade to the fixed version should avoid passing untrusted or arbitrary values for the cookie fields and ensure they are set by the application instead of user input.
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 cookie
to version 0.7.0 or higher.
References
medium severity
- Vulnerable module: hoek
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › hawk@3.1.3 › hoek@2.16.3Remediation: Open PR to patch hoek@2.16.3.
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › hawk@3.1.3 › boom@2.10.1 › hoek@2.16.3Remediation: Open PR to patch hoek@2.16.3.
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › hawk@3.1.3 › sntp@1.0.9 › hoek@2.16.3Remediation: Open PR to patch hoek@2.16.3.
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › hawk@3.1.3 › cryptiles@2.0.5 › boom@2.10.1 › hoek@2.16.3Remediation: Open PR to patch hoek@2.16.3.
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: ramda
- Introduced through: ramda@0.23.0
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › ramda@0.23.0Remediation: Upgrade to ramda@0.27.2.
Overview
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in source/trim.js
within variable ws
.
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 ramda
to version 0.27.2 or higher.
References
medium severity
- Vulnerable module: tunnel-agent
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › request@2.74.0 › tunnel-agent@0.4.3Remediation: Open PR to patch tunnel-agent@0.4.3.
Overview
tunnel-agent
is HTTP proxy tunneling agent. Affected versions of the package are vulnerable to Uninitialized Memory Exposure.
A possible memory disclosure vulnerability exists when a value of type number
is used to set the proxy.auth option of a request request
and results in a possible uninitialized memory exposures in the request body.
This is a result of unobstructed use of the Buffer
constructor, whose insecure default constructor increases the odds of memory leakage.
Details
Constructing a Buffer
class with integer N
creates a Buffer
of length N
with raw (not "zero-ed") memory.
In the following example, the first call would allocate 100 bytes of memory, while the second example will allocate the memory needed for the string "100":
// uninitialized Buffer of length 100
x = new Buffer(100);
// initialized Buffer with value of '100'
x = new Buffer('100');
tunnel-agent
's request
construction uses the default Buffer
constructor as-is, making it easy to append uninitialized memory to an existing list. If the value of the buffer list is exposed to users, it may expose raw server side memory, potentially holding secrets, private data and code. This is a similar vulnerability to the infamous Heartbleed
flaw in OpenSSL.
Proof of concept by ChALkeR
require('request')({
method: 'GET',
uri: 'http://www.example.com',
tunnel: true,
proxy:{
protocol: 'http:',
host:"127.0.0.1",
port:8080,
auth:80
}
});
You can read more about the insecure Buffer
behavior on our blog.
Similar vulnerabilities were discovered in request, mongoose, ws and sequelize.
Remediation
Upgrade tunnel-agent
to version 0.6.0 or higher.
Note This is vulnerable only for Node <=4
References
low severity
- Vulnerable module: ms
- Introduced through: twilio@ethanresnick/twilio-node#patch-1
Detailed paths
-
Introduced through: twilio-interactive-flow@ethanresnick/twilio-ivr#5b045d592fc94ae04c5254cfe1e31a88ae4f2dc9 › twilio@ethanresnick/twilio-node#patch-1 › jsonwebtoken@5.4.1 › ms@0.7.3Remediation: Open PR to patch ms@0.7.3.
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.