Find, fix and prevent vulnerabilities in your code.
high severity
- Vulnerable module: axios
- Introduced through: axios@0.27.2
Detailed paths
-
Introduced through: psitransfer@psi-4ward/psitransfer#5491b501f855edd3fec2a8e9beb9861512013303 › axios@0.27.2Remediation: Upgrade to axios@0.28.0.
Overview
axios is a promise-based HTTP client for the browser and Node.js.
Affected versions of this package are vulnerable to Cross-site Request Forgery (CSRF) due to inserting the X-XSRF-TOKEN
header using the secret XSRF-TOKEN
cookie value in all requests to any server when the XSRF-TOKEN
0 cookie is available, and the withCredentials
setting is turned on. If a malicious user manages to obtain this value, it can potentially lead to the XSRF defence mechanism bypass.
Workaround
Users should change the default XSRF-TOKEN
cookie name in the Axios configuration and manually include the corresponding header only in the specific places where it's necessary.
Remediation
Upgrade axios
to version 0.28.0, 1.6.0 or higher.
References
medium severity
- Vulnerable module: inflight
- Introduced through: archiver@5.3.2
Detailed paths
-
Introduced through: psitransfer@psi-4ward/psitransfer#5491b501f855edd3fec2a8e9beb9861512013303 › archiver@5.3.2 › archiver-utils@2.1.0 › glob@7.2.3 › inflight@1.0.6
-
Introduced through: psitransfer@psi-4ward/psitransfer#5491b501f855edd3fec2a8e9beb9861512013303 › archiver@5.3.2 › zip-stream@4.1.1 › archiver-utils@3.0.4 › 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: axios
- Introduced through: axios@0.27.2
Detailed paths
-
Introduced through: psitransfer@psi-4ward/psitransfer#5491b501f855edd3fec2a8e9beb9861512013303 › axios@0.27.2Remediation: Upgrade to axios@1.6.3.
Overview
axios is a promise-based HTTP client for the browser and Node.js.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS). An attacker can deplete system resources by providing a manipulated string as input to the format method, causing the regular expression to exhibit a time complexity of O(n^2)
. This makes the server to become unable to provide normal service due to the excessive cost and time wasted in processing vulnerable regular expressions.
PoC
const axios = require('axios');
console.time('t1');
axios.defaults.baseURL = '/'.repeat(10000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t1');
console.time('t2');
axios.defaults.baseURL = '/'.repeat(100000) + 'a/';
axios.get('/a').then(()=>{}).catch(()=>{});
console.timeEnd('t2');
/* stdout
t1: 60.826ms
t2: 5.826s
*/
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 axios
to version 1.6.3 or higher.