Vulnerability-Lookup

CVE-2026-84809 (GCVE-0-2026-84809)

Vulnerability from cvelistv5 – Published: 2026-09-02 16:59 – Updated: 2026-09-04 02:48

Title

Tencent AI-Infra-Guard skill-scan Analysis Bypass via Excluded Python Bytecode

Summary

Tencent AI-Infra-Guard's skill-scan component excludes compiled Python bytecode files from analysis by hardcoding __pycache__ directories and .pyc/.pyo/.pyd extensions into skip lists across multiple scanning surfaces. Attackers can distribute skills with benign Python source files alongside malicious compiled bytecode that executes on import while the scanner reports a safe verdict, enabling code execution when operators install the skill.

Severity

7.1 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N

6.5 (Medium)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-09-04 02:48 UTC

CWE

CWE-693 - Protection Mechanism Failure

Assigner

VulnCheck mitre root

References

6 references

URL	Tags
https://github.com/Tencent/AI-Infra-Guard/issues/531	issue-tracking
https://github.com/Tencent/AI-Infra-Guard/commit/…	patch
https://github.com/Tencent/AI-Infra-Guard/blob/v4…	technical-description
https://github.com/Tencent/AI-Infra-Guard/blob/v4…	technical-description
https://github.com/Tencent/AI-Infra-Guard	product
https://www.vulncheck.com/advisories/tencent-ai-i…	third-party-advisory

Impacted products

2 products

Vendor	Product	Version	CPE status
Tencent	AI-Infra-Guard	Affected: 0 , < 4.5.2 (semver) Affected: 4.6.0 , ≤ 4.6.0 (semver)	guessed
Tencent	aig-skill-scan	Affected: 0 , ≤ 0.2.1 (semver)	guessed

Date Public

2026-08-10 00:00

Credits

nedlir

Show details on NVD website

JSON

To clipboard

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FKIE_CVE-2026-84809

Vulnerability from fkie_nvd - Published: 2026-09-02 17:18 - Updated: 2026-09-04 03:17

Severity

6.5 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N

Summary

References

	URL	Tags
	disclosure@vulncheck.com	https://github.com/Tencent/AI-Infra-Guard
	disclosure@vulncheck.com	https://github.com/Tencent/AI-Infra-Guard/blob/v4.6.0/skill-scan/skill_scan/tools/dir/dir_actions.py
	disclosure@vulncheck.com	https://github.com/Tencent/AI-Infra-Guard/blob/v4.6.0/skill-scan/skill_scan/utils/pre_scan.py
	disclosure@vulncheck.com	https://github.com/Tencent/AI-Infra-Guard/commit/7e0f749e3c023e5c6ab7b32fe97b3f6f2e8aeb04
	disclosure@vulncheck.com	https://github.com/Tencent/AI-Infra-Guard/issues/531
	disclosure@vulncheck.com	https://www.vulncheck.com/advisories/tencent-ai-infra-guard-skill-scan-analysis-bypass-via-excluded-python-bytecode
	134c704f-9b21-4f2e-91b3-4a467353bcc0	https://github.com/Tencent/AI-Infra-Guard/issues/531

Impacted products

	Vendor	Product	Version

JSON

To clipboard

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          "confidentialityImpact": "NONE",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 3.6,
        "source": "disclosure@vulncheck.com",
        "type": "Secondary"
      }
    ],
    "cvssMetricV40": [
      {
        "cvssData": {
          "Automatable": "NOT_DEFINED",
          "Recovery": "NOT_DEFINED",
          "Safety": "NOT_DEFINED",
          "attackComplexity": "LOW",
          "attackRequirements": "NONE",
          "attackVector": "NETWORK",
          "availabilityRequirement": "NOT_DEFINED",
          "baseScore": 7.1,
          "baseSeverity": "HIGH",
          "confidentialityRequirement": "NOT_DEFINED",
          "exploitMaturity": "NOT_DEFINED",
          "integrityRequirement": "NOT_DEFINED",
          "modifiedAttackComplexity": "NOT_DEFINED",
          "modifiedAttackRequirements": "NOT_DEFINED",
          "modifiedAttackVector": "NOT_DEFINED",
          "modifiedPrivilegesRequired": "NOT_DEFINED",
          "modifiedSubAvailabilityImpact": "NOT_DEFINED",
          "modifiedSubConfidentialityImpact": "NOT_DEFINED",
          "modifiedSubIntegrityImpact": "NOT_DEFINED",
          "modifiedUserInteraction": "NOT_DEFINED",
          "modifiedVulnAvailabilityImpact": "NOT_DEFINED",
          "modifiedVulnConfidentialityImpact": "NOT_DEFINED",
          "modifiedVulnIntegrityImpact": "NOT_DEFINED",
          "privilegesRequired": "NONE",
          "providerUrgency": "NOT_DEFINED",
          "subAvailabilityImpact": "NONE",
          "subConfidentialityImpact": "NONE",
          "subIntegrityImpact": "NONE",
          "userInteraction": "PASSIVE",
          "valueDensity": "NOT_DEFINED",
          "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
          "version": "4.0",
          "vulnAvailabilityImpact": "NONE",
          "vulnConfidentialityImpact": "NONE",
          "vulnIntegrityImpact": "HIGH",
          "vulnerabilityResponseEffort": "NOT_DEFINED"
        },
        "source": "disclosure@vulncheck.com",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-84809",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-09-04T02:48:03.204497Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-09-02T17:18:05.150",
  "references": [
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://github.com/Tencent/AI-Infra-Guard"
    },
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://github.com/Tencent/AI-Infra-Guard/blob/v4.6.0/skill-scan/skill_scan/tools/dir/dir_actions.py"
    },
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://github.com/Tencent/AI-Infra-Guard/blob/v4.6.0/skill-scan/skill_scan/utils/pre_scan.py"
    },
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://github.com/Tencent/AI-Infra-Guard/commit/7e0f749e3c023e5c6ab7b32fe97b3f6f2e8aeb04"
    },
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://github.com/Tencent/AI-Infra-Guard/issues/531"
    },
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://www.vulncheck.com/advisories/tencent-ai-infra-guard-skill-scan-analysis-bypass-via-excluded-python-bytecode"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "url": "https://github.com/Tencent/AI-Infra-Guard/issues/531"
    }
  ],
  "sourceIdentifier": "disclosure@vulncheck.com",
  "vulnStatus": "Received",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-693"
        }
      ],
      "source": "disclosure@vulncheck.com",
      "type": "Secondary"
    }
  ]
}

GHSA-7VC4-66F2-3F5F

Vulnerability from github – Published: 2026-09-02 18:32 – Updated: 2026-09-02 18:32

Details

Tencent AI-Infra-Guard's skill-scan component excludes compiled Python bytecode files from analysis by hardcoding pycache directories and .pyc/.pyo/.pyd extensions into skip lists across multiple scanning surfaces. Attackers can distribute skills with benign Python source files alongside malicious compiled bytecode that executes on import while the scanner reports a safe verdict, enabling code execution when operators install the skill.

Severity

6.5 (Medium)


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

7.1 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N

Show details on source website

JSON

To clipboard

{
  "affected": [],
  "aliases": [
    "CVE-2026-84809"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-693"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-02T17:18:05Z",
    "severity": "HIGH"
  },
  "details": "Tencent AI-Infra-Guard\u0027s skill-scan component excludes compiled Python bytecode files from analysis by hardcoding __pycache__ directories and .pyc/.pyo/.pyd extensions into skip lists across multiple scanning surfaces. Attackers can distribute skills with benign Python source files alongside malicious compiled bytecode that executes on import while the scanner reports a safe verdict, enabling code execution when operators install the skill.",
  "id": "GHSA-7vc4-66f2-3f5f",
  "modified": "2026-09-02T18:32:29Z",
  "published": "2026-09-02T18:32:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-84809"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Tencent/AI-Infra-Guard/issues/531"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Tencent/AI-Infra-Guard/commit/7e0f749e3c023e5c6ab7b32fe97b3f6f2e8aeb04"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Tencent/AI-Infra-Guard"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Tencent/AI-Infra-Guard/blob/v4.6.0/skill-scan/skill_scan/tools/dir/dir_actions.py"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Tencent/AI-Infra-Guard/blob/v4.6.0/skill-scan/skill_scan/utils/pre_scan.py"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/tencent-ai-infra-guard-skill-scan-analysis-bypass-via-excluded-python-bytecode"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}

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.

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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.

Action not permitted

CVE-2026-84809 (GCVE-0-2026-84809)

FKIE_CVE-2026-84809

GHSA-7VC4-66F2-3F5F

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Related by attack behaviour