CVE-2023-39523 (GCVE-0-2023-39523)

Vulnerability from cvelistv5 – Published: 2023-08-07 20:55 – Updated: 2024-10-03 16:00
VLAI
Title
ScanCode.io command injection in docker image fetch process
Summary
ScanCode.io is a server to script and automate software composition analysis with ScanPipe pipelines. Prior to version 32.5.1, the software has a possible command injection vulnerability in the docker fetch process as it allows to append malicious commands in the `docker_reference` parameter. In the function `scanpipe/pipes/fetch.py:fetch_docker_image` the parameter `docker_reference` is user controllable. The `docker_reference` variable is then passed to the vulnerable function `get_docker_image_platform`. However, the `get_docker_image_plaform` function constructs a shell command with the passed `docker_reference`. The `pipes.run_command` then executes the shell command without any prior sanitization, making the function vulnerable to command injections. A malicious user who is able to create or add inputs to a project can inject commands. Although the command injections are blind and the user will not receive direct feedback without logs, it is still possible to cause damage to the server/container. The vulnerability appears for example if a malicious user adds a semicolon after the input of `docker://;`, it would allow appending malicious commands. Version 32.5.1 contains a patch for this issue. The `docker_reference` input should be sanitized to avoid command injections and, as a workaround, one may avoid creating commands with user controlled input directly.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-77 - Improper Neutralization of Special Elements used in a Command ('Command Injection')
Assigner
Impacted products
Vendor Product Version
nexB scancode.io Affected: < 32.5.1
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nexb scancode.io Affected: 0 , < 32.5.1 (custom)
    cpe:2.3:a:nexb:scancode.io:*:*:*:*:*:*:*:*
Create a notification for this product.
Show details on NVD website

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The vulnerability appears for example if a malicious user adds a semicolon after the input of `docker://;`, it would allow appending malicious commands.\\n\\nVersion 32.5.1 contains a patch for this issue. The `docker_reference` input should be sanitized to avoid command injections and, as a workaround, one may avoid creating commands with user controlled input directly.\"}], \"problemTypes\": [{\"descriptions\": [{\"lang\": \"en\", \"type\": \"CWE\", \"cweId\": \"CWE-77\", \"description\": \"CWE-77: Improper Neutralization of Special Elements used in a Command (\u0027Command Injection\u0027)\"}]}], \"providerMetadata\": {\"orgId\": \"a0819718-46f1-4df5-94e2-005712e83aaa\", \"shortName\": \"GitHub_M\", \"dateUpdated\": \"2023-08-07T20:55:46.855Z\"}}}",
      "cveMetadata": "{\"cveId\": \"CVE-2023-39523\", \"state\": \"PUBLISHED\", \"dateUpdated\": \"2024-10-03T16:00:56.672Z\", \"dateReserved\": \"2023-08-03T16:27:36.262Z\", \"assignerOrgId\": \"a0819718-46f1-4df5-94e2-005712e83aaa\", \"datePublished\": \"2023-08-07T20:55:46.855Z\", \"assignerShortName\": \"GitHub_M\"}",
      "dataType": "CVE_RECORD",
      "dataVersion": "5.1"
    }
  }
}


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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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.

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Detection rules are retrieved from Rulezet.

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