Vulnerability-Lookup

PYSEC-2025-247

Vulnerability from pysec - Published: 2025-07-07 10:15 - Updated: 2026-07-13 05:49

Details

A vulnerability in the ArxivReader class of the run-llama/llama_index repository, versions up to v0.12.22.post1, allows for MD5 hash collisions when generating filenames for downloaded papers. This can lead to data loss as papers with identical titles but different contents may overwrite each other, preventing some papers from being processed for AI model training. The issue is resolved in version 0.12.28.

Severity

5.3 (Medium)


                  
                    CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N

Impacted products

Name	purl
llama-index	pkg:pypi/llama-index

Aliases

CVE-2025-3044

JSON

To clipboard

{
  "affected": [
    {
      "ecosystem_specific": {},
      "package": {
        "ecosystem": "PyPI",
        "name": "llama-index",
        "purl": "pkg:pypi/llama-index"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "0.12.28"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.10.0",
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        "0.9.7",
        "0.9.8",
        "0.9.8.post1",
        "0.9.9"
      ]
    }
  ],
  "aliases": [
    "CVE-2025-3044"
  ],
  "details": "A vulnerability in the ArxivReader class of the run-llama/llama_index repository, versions up to v0.12.22.post1, allows for MD5 hash collisions when generating filenames for downloaded papers. This can lead to data loss as papers with identical titles but different contents may overwrite each other, preventing some papers from being processed for AI model training. The issue is resolved in version 0.12.28.",
  "id": "PYSEC-2025-247",
  "modified": "2026-07-13T05:49:40.426796Z",
  "published": "2025-07-07T10:15:26.717Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/run-llama/llama_index/commit/0008041e8dde8e519621388e5d6f558bde6ef42e"
    },
    {
      "type": "EVIDENCE",
      "url": "https://huntr.com/bounties/80182c3a-876f-422f-8bac-38267e0345d6"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2025-3044 (GCVE-0-2025-3044)

Vulnerability from cvelistv5 – Published: 2025-07-07 09:54 – Updated: 2025-07-07 15:23

Title

MD5 Hash Collision in run-llama/llama_index

Summary

Severity

5.3 (Medium)


                        
                          CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N

SSVC

Exploitation: poc Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-07-07 15:23 UTC

CWE

CWE-440 - Expected Behavior Violation

Assigner

@huntr_ai CNA under the mitre root

CNA scorecard C 65/100 over 40 records in the last 180 days details

References

2 references

URL	Tags
https://huntr.com/bounties/80182c3a-876f-422f-8ba…
https://github.com/run-llama/llama_index/commit/0…

Impacted products

1 product

Vendor	Product	Version
run-llama	run-llama/llama_index	Affected: unspecified , < 0.12.28 (custom)

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-3044",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-07-07T15:23:15.234430Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-07-07T15:23:18.518Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://huntr.com/bounties/80182c3a-876f-422f-8bac-38267e0345d6"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "run-llama/llama_index",
          "vendor": "run-llama",
          "versions": [
            {
              "lessThan": "0.12.28",
              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability in the ArxivReader class of the run-llama/llama_index repository, versions up to v0.12.22.post1, allows for MD5 hash collisions when generating filenames for downloaded papers. This can lead to data loss as papers with identical titles but different contents may overwrite each other, preventing some papers from being processed for AI model training. The issue is resolved in version 0.12.28."
        }
      ],
      "metrics": [
        {
          "cvssV3_0": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 5.3,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "LOW",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N",
            "version": "3.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-440",
              "description": "CWE-440 Expected Behavior Violation",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-07-07T09:54:22.506Z",
        "orgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
        "shortName": "@huntr_ai"
      },
      "references": [
        {
          "url": "https://huntr.com/bounties/80182c3a-876f-422f-8bac-38267e0345d6"
        },
        {
          "url": "https://github.com/run-llama/llama_index/commit/0008041e8dde8e519621388e5d6f558bde6ef42e"
        }
      ],
      "source": {
        "advisory": "80182c3a-876f-422f-8bac-38267e0345d6",
        "discovery": "EXTERNAL"
      },
      "title": "MD5 Hash Collision in run-llama/llama_index"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "c09c270a-b464-47c1-9133-acb35b22c19a",
    "assignerShortName": "@huntr_ai",
    "cveId": "CVE-2025-3044",
    "datePublished": "2025-07-07T09:54:22.506Z",
    "dateReserved": "2025-03-31T12:26:26.971Z",
    "dateUpdated": "2025-07-07T15:23:18.518Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.

Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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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.

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