Vulnerability-Lookup

OPENSUSE-SU-2024:11558-1

Vulnerability from csaf_opensuse - Published: 2024-06-15 00:00 - Updated: 2024-06-15 00:00

Summary

python-Scrapy-doc-2.5.1-1.1 on GA media

Severity

Moderate

Notes

Title of the patch: python-Scrapy-doc-2.5.1-1.1 on GA media

Description of the patch: These are all security issues fixed in the python-Scrapy-doc-2.5.1-1.1 package on the GA media of openSUSE Tumbleweed.

Patchnames: openSUSE-Tumbleweed-2024-11558

CVE-2021-41125

6.5 (Medium)


                
                  CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N

Affected products

Recommended 12 products

Product	Version	Remediation
Unresolved product id: openSUSE Tumbleweed:python-Scrapy-doc-2.5.1-1.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python-Scrapy-doc-2.5.1-1.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python-Scrapy-doc-2.5.1-1.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python-Scrapy-doc-2.5.1-1.1.x86_64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python38-Scrapy-2.5.1-1.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python38-Scrapy-2.5.1-1.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python38-Scrapy-2.5.1-1.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python38-Scrapy-2.5.1-1.1.x86_64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python39-Scrapy-2.5.1-1.1.aarch64	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python39-Scrapy-2.5.1-1.1.ppc64le	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python39-Scrapy-2.5.1-1.1.s390x	—	Vendor Fix
Unresolved product id: openSUSE Tumbleweed:python39-Scrapy-2.5.1-1.1.x86_64	—	Vendor Fix

Threats

Impact moderate

References

5 references

URL	Category
https://www.suse.com/support/security/rating/	external
https://ftp.suse.com/pub/projects/security/csaf/o…	self
https://www.suse.com/security/cve/CVE-2021-41125/	self
https://www.suse.com/security/cve/CVE-2021-41125	external
https://bugzilla.suse.com/1191446	external

JSON

To clipboard

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  "vulnerabilities": [
    {
      "cve": "CVE-2021-41125",
      "ids": [
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          "system_name": "SUSE CVE Page",
          "text": "https://www.suse.com/security/cve/CVE-2021-41125"
        }
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      "notes": [
        {
          "category": "general",
          "text": "Scrapy is a high-level web crawling and scraping framework for Python. If you use `HttpAuthMiddleware` (i.e. the `http_user` and `http_pass` spider attributes) for HTTP authentication, all requests will expose your credentials to the request target. This includes requests generated by Scrapy components, such as `robots.txt` requests sent by Scrapy when the `ROBOTSTXT_OBEY` setting is set to `True`, or as requests reached through redirects. Upgrade to Scrapy 2.5.1 and use the new `http_auth_domain` spider attribute to control which domains are allowed to receive the configured HTTP authentication credentials. If you are using Scrapy 1.8 or a lower version, and upgrading to Scrapy 2.5.1 is not an option, you may upgrade to Scrapy 1.8.1 instead. If you cannot upgrade, set your HTTP authentication credentials on a per-request basis, using for example the `w3lib.http.basic_auth_header` function to convert your credentials into a value that you can assign to the `Authorization` header of your request, instead of defining your credentials globally using `HttpAuthMiddleware`.",
          "title": "CVE description"
        }
      ],
      "product_status": {
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          "summary": "CVE-2021-41125",
          "url": "https://www.suse.com/security/cve/CVE-2021-41125"
        },
        {
          "category": "external",
          "summary": "SUSE Bug 1191446 for CVE-2021-41125",
          "url": "https://bugzilla.suse.com/1191446"
        }
      ],
      "remediations": [
        {
          "category": "vendor_fix",
          "details": "To install this SUSE Security Update use the SUSE recommended installation methods like YaST online_update or \"zypper patch\".\n",
          "product_ids": [
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        {
          "cvss_v3": {
            "baseScore": 6.5,
            "baseSeverity": "MEDIUM",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N",
            "version": "3.1"
          },
          "products": [
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            "openSUSE Tumbleweed:python-Scrapy-doc-2.5.1-1.1.s390x",
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            "openSUSE Tumbleweed:python39-Scrapy-2.5.1-1.1.x86_64"
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      ],
      "threats": [
        {
          "category": "impact",
          "date": "2024-06-15T00:00:00Z",
          "details": "moderate"
        }
      ],
      "title": "CVE-2021-41125"
    }
  ]
}

CVE-2021-41125 (GCVE-0-2021-41125)

Vulnerability from cvelistv5 – Published: 2021-10-06 17:15 – Updated: 2024-08-04 02:59

Title

HTTP authentication credential leak to target websites in scrapy

Summary

Scrapy is a high-level web crawling and scraping framework for Python. If you use `HttpAuthMiddleware` (i.e. the `http_user` and `http_pass` spider attributes) for HTTP authentication, all requests will expose your credentials to the request target. This includes requests generated by Scrapy components, such as `robots.txt` requests sent by Scrapy when the `ROBOTSTXT_OBEY` setting is set to `True`, or as requests reached through redirects. Upgrade to Scrapy 2.5.1 and use the new `http_auth_domain` spider attribute to control which domains are allowed to receive the configured HTTP authentication credentials. If you are using Scrapy 1.8 or a lower version, and upgrading to Scrapy 2.5.1 is not an option, you may upgrade to Scrapy 1.8.1 instead. If you cannot upgrade, set your HTTP authentication credentials on a per-request basis, using for example the `w3lib.http.basic_auth_header` function to convert your credentials into a value that you can assign to the `Authorization` header of your request, instead of defining your credentials globally using `HttpAuthMiddleware`.

Severity

5.7 (Medium)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:N/A:N

CWE

CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor

Assigner

GitHub_M mitre root

References

5 references

URL	Tags
https://github.com/scrapy/scrapy/security/advisor…	x_refsource_CONFIRM
https://github.com/scrapy/scrapy/commit/b01d69a1b…	x_refsource_MISC
https://w3lib.readthedocs.io/en/latest/w3lib.html…	x_refsource_MISC
http://doc.scrapy.org/en/latest/topics/downloader…	x_refsource_MISC
https://lists.debian.org/debian-lts-announce/2022…	mailing-listx_refsource_MLIST

Impacted products

1 product

Vendor	Product	Version
scrapy	scrapy	Affected: < 1.8.1 Affected: >= 2.0.0, < 2.5.1

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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.