Vulnerability-Lookup

CVE-2026-107291 (GCVE-0-2026-107291)

Vulnerability from cvelistv5 – Published: 2026-10-08 16:22 – Updated: 2026-10-08 17:25

Title

Pydantic AI OpenTelemetry instrumentation: exception events on tool and agent run spans include content when `include_content=False`

Summary

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.3.4 until 1.107.6 and 2.44.0, OpenTelemetry instrumentation configured with InstrumentationSettings(include_content=False) can still export sensitive agent content through exception.message and exception.stacktrace events, error status descriptions, and model_request_parameters containing instructions or the prompted_output_template. The exposed data is available to readers of the configured telemetry backend and can include tool feedback, provider error bodies, runtime instructions, and structured-output templates even though message attributes are redacted. This issue does not grant new access to agent data, and deployments that do not use include_content=False are not affected by the setting bypass. This issue is fixed in versions 1.107.6 and 2.44.0.

Severity

2.3 (Low)


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

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-10-08 17:25 UTC

CWE

CWE-212 - Improper Removal of Sensitive Information Before Storage or Transfer
CWE-532 - Insertion of Sensitive Information into Log File

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7668 records in the last 180 days details

References

13 references

URL	Tags
https://github.com/pydantic/pydantic-ai/security/…	x_refsource_CONFIRM
https://github.com/pydantic/pydantic-ai/pull/8403	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/pull/8404	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/pull/8408	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/pull/8428	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/pull/8429	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/commit/4e…	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/commit/6b…	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/commit/7e…	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/commit/96…	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/commit/de…	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/releases/…	x_refsource_MISC
https://github.com/pydantic/pydantic-ai/releases/…	x_refsource_MISC

Impacted products

2 products

Vendor	Product	Version	CPE status
pydantic	pydantic-ai	Affected: >= 0.3.4, < 1.107.6 Affected: >= 2.0.0b1, < 2.44.0	guessed
pydantic	pydantic-ai-slim	Affected: >= 0.3.4, < 1.107.6 Affected: >= 2.0.0b1, < 2.44.0	guessed

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                  "version": "\u003e= 0.3.4, \u003c 1.107.6"
                },
                {
                  "status": "affected",
                  "version": "\u003e= 2.0.0b1, \u003c 2.44.0"
                }
              ]
            },
            {
              "product": "pydantic-ai-slim",
              "vendor": "pydantic",
              "versions": [
                {
                  "status": "affected",
                  "version": "\u003e= 0.3.4, \u003c 1.107.6"
                },
                {
                  "status": "affected",
                  "version": "\u003e= 2.0.0b1, \u003c 2.44.0"
                }
              ]
            }
          ],
          "descriptions": [
            {
              "lang": "en",
              "value": "Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.3.4 until 1.107.6 and 2.44.0, OpenTelemetry instrumentation configured with InstrumentationSettings(include_content=False) can still export sensitive agent content through exception.message and exception.stacktrace events, error status descriptions, and model_request_parameters containing instructions or the prompted_output_template. The exposed data is available to readers of the configured telemetry backend and can include tool feedback, provider error bodies, runtime instructions, and structured-output templates even though message attributes are redacted. This issue does not grant new access to agent data, and deployments that do not use include_content=False are not affected by the setting bypass. This issue is fixed in versions 1.107.6 and 2.44.0."
            }
          ],
          "metrics": [
            {
              "cvssV4_0": {
                "attackComplexity": "LOW",
                "attackRequirements": "PRESENT",
                "attackVector": "NETWORK",
                "baseScore": 2.3,
                "baseSeverity": "LOW",
                "privilegesRequired": "LOW",
                "subAvailabilityImpact": "NONE",
                "subConfidentialityImpact": "NONE",
                "subIntegrityImpact": "NONE",
                "userInteraction": "NONE",
                "vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N",
                "version": "4.0",
                "vulnAvailabilityImpact": "NONE",
                "vulnConfidentialityImpact": "LOW",
                "vulnIntegrityImpact": "NONE"
              }
            }
          ],
          "problemTypes": [
            {
              "descriptions": [
                {
                  "cweId": "CWE-212",
                  "description": "CWE-212: Improper Removal of Sensitive Information Before Storage or Transfer",
                  "lang": "en",
                  "type": "CWE"
                }
              ]
            },
            {
              "descriptions": [
                {
                  "cweId": "CWE-532",
                  "description": "CWE-532: Insertion of Sensitive Information into Log File",
                  "lang": "en",
                  "type": "CWE"
                }
              ]
            }
          ],
          "providerMetadata": {
            "dateUpdated": "2026-10-08T16:22:51.763Z",
            "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
            "shortName": "GitHub_M"
          },
          "references": [
            {
              "name": "https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-4x9p-g9wm-8q7f",
              "tags": [
                "x_refsource_CONFIRM"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-4x9p-g9wm-8q7f"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/pull/8403",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/pull/8403"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/pull/8404",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/pull/8404"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/pull/8408",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/pull/8408"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/pull/8428",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/pull/8428"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/pull/8429",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/pull/8429"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/commit/4e013c51a50659aba2adf7853bfb22bb77f6a518",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/commit/4e013c51a50659aba2adf7853bfb22bb77f6a518"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/commit/6b14c74cb281f899a2ae4fae5327111e33f60771",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/commit/6b14c74cb281f899a2ae4fae5327111e33f60771"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/commit/7ee27e38ab2e525ca60ff1a25d16413ff989fd79",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/commit/7ee27e38ab2e525ca60ff1a25d16413ff989fd79"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/commit/963dec5f70d6f558997fc259356c0090cc5ea487",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/commit/963dec5f70d6f558997fc259356c0090cc5ea487"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/commit/de4e61515327bd80a19cd8552001c30933e6acc3",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/commit/de4e61515327bd80a19cd8552001c30933e6acc3"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6"
            },
            {
              "name": "https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0",
              "tags": [
                "x_refsource_MISC"
              ],
              "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0"
            }
          ],
          "source": {
            "advisory": "GHSA-4x9p-g9wm-8q7f",
            "discovery": "UNKNOWN"
          },
          "title": "Pydantic AI OpenTelemetry instrumentation: exception events on tool and agent run spans include content when `include_content=False`"
        }
      },
      "cveMetadata": {
        "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "assignerShortName": "GitHub_M",
        "cveId": "CVE-2026-107291",
        "datePublished": "2026-10-08T16:22:51.763Z",
        "dateReserved": "2026-10-07T15:53:23.586Z",
        "dateUpdated": "2026-10-08T17:25:18.280Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}

BREW-OTERM-CVE-2026-107291 (GHSA-4X9P-G9WM-8Q7F)

Vulnerability from osv_homebrew – Published: 2026-10-08 18:40 – Updated: 2026-10-08 18:40 – Source website

Summary

Pydantic AI OpenTelemetry instrumentation: exception events on tool and agent run spans include content when `include_content=False`

Details

Summary

Pydantic AI's OpenTelemetry instrumentation supports InstrumentationSettings(include_content=False) to exclude message content — user prompts, model completions, tool call arguments and responses, and any other message content — from exported telemetry, so that agents can be monitored without sending sensitive content to the observability backend.

The message attributes honoured the setting. Several other parts of the same spans did not, and exported content regardless of it:

Exceptions. Recorded as OpenTelemetry exception events, with their message and stack trace, on tool, agent run, model request, embedding and image generation spans, and on realtime session spans. The message of the exception carrying a tool's ModelRetry or ToolFailed feedback is the text sent back to the model, which can quote tool arguments and results. When a tool ran out of retries, the error that ended the run was chained from the last retry, so its stack trace repeated that text on the run span. Exceptions raised by tool code were recorded with their full message, as were failures of a model request, embedding or image generation, whose messages carry the provider's error response body.
The error status description. The OpenTelemetry SDK describes a span's ERROR status with the exception's type and message, so the message reached the backend a second time even where the event itself was redacted.
Instructions and the prompted-output template. The model_request_parameters attribute serialized the request's instruction parts in full, exporting the agent's instructions — both static and those built from dependencies at request time — along with the template used to prompt for structured output.

Details

Content reaches these places because of what they carry rather than through any single missing check, which is why the setting was applied correctly to the message attributes (gen_ai.input.messages, gen_ai.tool.call.arguments, gen_ai.tool.call.result, and so on) while these paths were not: the exception recording and the status description came from the OpenTelemetry SDK's defaults, and the instructions and output template were serialized as part of the request's parameters rather than treated as content.

Impact

This does not grant an attacker any new access to the agent or its data: the content is only visible to whoever can read the exported telemetry. The exposure matters when traces are exported to a destination whose audience is broader or less trusted than the agent's own data — a third-party observability vendor or a shared backend — which is the scenario include_content=False exists for.

Who Is Affected

You are affected if you enabled instrumentation with include_content=False. Instructions are exported on every successful run, so no failure is needed to be affected; the exception paths additionally require a tool to raise, or a model, embedding or image generation request to fail. Realtime sessions are affected the same way, through the errors their provider connections report. GHSA-3gh4-cghq-f8v4 stated that retries coming from tool calls were redacted correctly; that was true of the retry prompt in the message attributes but not of the exception event on the tool span. You are not affected if you don't set include_content=False.

Remediation

Upgrade to a patched version. With include_content=False, exception events now record only the exception type, error statuses carry no description, and model_request_parameters is exported without its instruction content or output template. If you rely on this setting, consider reviewing previously exported traces for exception events, for error status descriptions, and for model_request_parameters.

Workaround for Unpatched Versions

If you cannot upgrade, scrub the exception.message and exception.stacktrace event attributes, the error status description, and the instruction parts and prompted_output_template within model_request_parameters, on spans emitted by Pydantic AI in your telemetry pipeline (for example with an OpenTelemetry Collector processor). Setting include_model_request_parameters=False alongside include_content=False removes both, at the cost of the rest of that attribute.

Credits

Reported privately by @BrianWillows, whose report covered the exception events on tool and agent run spans. The remaining paths were found while fixing it, by a test that drives content through every channel at once and checks the whole exported trace.

Severity

2.3 (Low)


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

References

URL

Type

	https://github.com/pydantic/pydantic-ai/security/…	WEB
	https://github.com/pydantic/pydantic-ai/pull/8403	WEB
	https://github.com/pydantic/pydantic-ai/pull/8404	WEB
	https://github.com/pydantic/pydantic-ai/pull/8408	WEB
	https://github.com/pydantic/pydantic-ai/pull/8428	WEB
	https://github.com/pydantic/pydantic-ai/pull/8429	WEB
	https://github.com/pydantic/pydantic-ai/commit/4e…	WEB
	https://github.com/pydantic/pydantic-ai/commit/6b…	WEB
	https://github.com/pydantic/pydantic-ai/commit/7e…	WEB
	https://github.com/pydantic/pydantic-ai/commit/96…	WEB
	https://github.com/pydantic/pydantic-ai/commit/de…	WEB
	https://github.com/pydantic/pydantic-ai	PACKAGE
	https://github.com/pydantic/pydantic-ai/releases/…	WEB
	https://github.com/pydantic/pydantic-ai/releases/…	WEB

JSON

To clipboard

{
  "affected": [
    {
      "ecosystem_specific": {
        "fix": "bump",
        "range_state": "fixed",
        "resource": "pydantic-ai-slim",
        "resource_purl": "pkg:pypi/pydantic-ai-slim@2.51.0",
        "upstream_fixed_in": "2.44.0"
      },
      "package": {
        "ecosystem": "Homebrew",
        "name": "oterm",
        "purl": "pkg:brew/oterm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.15.0"
            },
            {
              "fixed": "0.25.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "database_specific": {
    "confidence": "high",
    "source": "matched",
    "strategy": "registry",
    "upstream_evidence": [
      {
        "ecosystem": "PyPI",
        "key": "pkg:pypi/pydantic-ai-slim@2.51.0",
        "name": "pydantic-ai-slim",
        "resource": "pydantic-ai-slim",
        "strategy": "registry",
        "subject_version": "2.51.0"
      }
    ]
  },
  "details": "### Summary\n\nPydantic AI\u0027s OpenTelemetry instrumentation supports `InstrumentationSettings(include_content=False)` to exclude message content \u2014 user prompts, model completions, tool call arguments and responses, and any other message content \u2014 from exported telemetry, so that agents can be monitored without sending sensitive content to the observability backend.\n\nThe message attributes honoured the setting. Several other parts of the same spans did not, and exported content regardless of it:\n\n- **Exceptions.** Recorded as OpenTelemetry exception events, with their message and stack trace, on tool, agent run, model request, embedding and image generation spans, and on realtime session spans. The message of the exception carrying a tool\u0027s `ModelRetry` or `ToolFailed` feedback is the text sent back to the model, which can quote tool arguments and results. When a tool ran out of retries, the error that ended the run was chained from the last retry, so its stack trace repeated that text on the run span. Exceptions raised by tool code were recorded with their full message, as were failures of a model request, embedding or image generation, whose messages carry the provider\u0027s error response body.\n- **The error status description.** The OpenTelemetry SDK describes a span\u0027s ERROR status with the exception\u0027s type and message, so the message reached the backend a second time even where the event itself was redacted.\n- **Instructions and the prompted-output template.** The `model_request_parameters` attribute serialized the request\u0027s instruction parts in full, exporting the agent\u0027s instructions \u2014 both static and those built from dependencies at request time \u2014 along with the template used to prompt for structured output.\n\n### Details\n\nContent reaches these places because of what they carry rather than through any single missing check, which is why the setting was applied correctly to the message attributes (`gen_ai.input.messages`, `gen_ai.tool.call.arguments`, `gen_ai.tool.call.result`, and so on) while these paths were not: the exception recording and the status description came from the OpenTelemetry SDK\u0027s defaults, and the instructions and output template were serialized as part of the request\u0027s parameters rather than treated as content.\n\n### Impact\n\nThis does not grant an attacker any new access to the agent or its data: the content is only visible to whoever can read the exported telemetry. The exposure matters when traces are exported to a destination whose audience is broader or less trusted than the agent\u0027s own data \u2014 a third-party observability vendor or a shared backend \u2014 which is the scenario `include_content=False` exists for.\n\n### Who Is Affected\n\nYou are affected if you enabled instrumentation with `include_content=False`. Instructions are exported on every successful run, so no failure is needed to be affected; the exception paths additionally require a tool to raise, or a model, embedding or image generation request to fail. Realtime sessions are affected the same way, through the errors their provider connections report. GHSA-3gh4-cghq-f8v4 stated that retries coming from tool calls were redacted correctly; that was true of the retry prompt in the message attributes but not of the exception event on the tool span. You are not affected if you don\u0027t set `include_content=False`.\n\n### Remediation\n\nUpgrade to a patched version. With `include_content=False`, exception events now record only the exception type, error statuses carry no description, and `model_request_parameters` is exported without its instruction content or output template. If you rely on this setting, consider reviewing previously exported traces for exception events, for error status descriptions, and for `model_request_parameters`.\n\n### Workaround for Unpatched Versions\n\nIf you cannot upgrade, scrub the `exception.message` and `exception.stacktrace` event attributes, the error status description, and the instruction parts and `prompted_output_template` within `model_request_parameters`, on spans emitted by Pydantic AI in your telemetry pipeline (for example with an OpenTelemetry Collector processor). Setting `include_model_request_parameters=False` alongside `include_content=False` removes both, at the cost of the rest of that attribute.\n\n### Credits\n\nReported privately by @BrianWillows, whose report covered the exception events on tool and agent run spans. The remaining paths were found while fixing it, by a test that drives content through every channel at once and checks the whole exported trace.",
  "id": "BREW-oterm-CVE-2026-107291",
  "modified": "2026-10-08T18:40:35Z",
  "published": "2026-10-08T18:40:35Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-4x9p-g9wm-8q7f"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8403"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8404"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8408"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8428"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8429"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/4e013c51a50659aba2adf7853bfb22bb77f6a518"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/6b14c74cb281f899a2ae4fae5327111e33f60771"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/7ee27e38ab2e525ca60ff1a25d16413ff989fd79"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/963dec5f70d6f558997fc259356c0090cc5ea487"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/de4e61515327bd80a19cd8552001c30933e6acc3"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/pydantic/pydantic-ai"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0"
    }
  ],
  "schema_version": "1.7.3",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Pydantic AI OpenTelemetry instrumentation: exception events on tool and agent run spans include content when `include_content=False`",
  "upstream": [
    "GHSA-4x9p-g9wm-8q7f",
    "CVE-2026-107291"
  ]
}

FKIE_CVE-2026-107291

Vulnerability from fkie_nvd - Published: 2026-10-08 17:17 - Updated: 2026-10-13 14:34

Severity

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

Summary

References

URL	Tags
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/commit/4e013c51a50659aba2adf7853bfb22bb77f6a518	Patch
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/commit/6b14c74cb281f899a2ae4fae5327111e33f60771	Patch
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/commit/7ee27e38ab2e525ca60ff1a25d16413ff989fd79	Patch
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/commit/963dec5f70d6f558997fc259356c0090cc5ea487	Patch
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/commit/de4e61515327bd80a19cd8552001c30933e6acc3	Patch
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/pull/8403	Patch, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/pull/8404	Patch, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/pull/8408	Patch, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/pull/8428	Patch, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/pull/8429	Exploit, Patch, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6	Patch, Release Notes, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0	Patch, Release Notes, Vendor Advisory
security-advisories@github.com	https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-4x9p-g9wm-8q7f	Mitigation, Vendor Advisory

Impacted products

	Vendor	Product	Version
	pydantic	pydantic_ai	*
	pydantic	pydantic_ai	*

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "pydantic-ai",
          "vendor": "pydantic",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 0.3.4, \u003c 1.107.6"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.0.0b1, \u003c 2.44.0"
            }
          ]
        },
        {
          "product": "pydantic-ai-slim",
          "vendor": "pydantic",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 0.3.4, \u003c 1.107.6"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.0.0b1, \u003c 2.44.0"
            }
          ]
        }
      ],
      "source": "security-advisories@github.com"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:pydantic:pydantic_ai:*:*:*:*:*:python:*:*",
              "matchCriteriaId": "B7E9041B-9F7B-4255-AD02-F18EB0BBCA6B",
              "versionEndExcluding": "1.107.4",
              "versionStartIncluding": "0.3.4",
              "vulnerable": true
            },
            {
              "criteria": "cpe:2.3:a:pydantic:pydantic_ai:*:-:*:*:*:python:*:*",
              "matchCriteriaId": "7FEC7EC8-5520-4930-8853-83108092F8BF",
              "versionEndExcluding": "2.44.0",
              "versionStartIncluding": "2.0.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.3.4 until 1.107.6 and 2.44.0, OpenTelemetry instrumentation configured with InstrumentationSettings(include_content=False) can still export sensitive agent content through exception.message and exception.stacktrace events, error status descriptions, and model_request_parameters containing instructions or the prompted_output_template. The exposed data is available to readers of the configured telemetry backend and can include tool feedback, provider error bodies, runtime instructions, and structured-output templates even though message attributes are redacted. This issue does not grant new access to agent data, and deployments that do not use include_content=False are not affected by the setting bypass. This issue is fixed in versions 1.107.6 and 2.44.0."
    }
  ],
  "id": "CVE-2026-107291",
  "lastModified": "2026-10-13T14:34:22.207",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 4.3,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "LOW",
          "integrityImpact": "NONE",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 1.4,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ],
    "cvssMetricV40": [
      {
        "cvssData": {
          "Automatable": "NOT_DEFINED",
          "Recovery": "NOT_DEFINED",
          "Safety": "NOT_DEFINED",
          "attackComplexity": "LOW",
          "attackRequirements": "PRESENT",
          "attackVector": "NETWORK",
          "availabilityRequirement": "NOT_DEFINED",
          "baseScore": 2.3,
          "baseSeverity": "LOW",
          "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": "LOW",
          "providerUrgency": "NOT_DEFINED",
          "subAvailabilityImpact": "NONE",
          "subConfidentialityImpact": "NONE",
          "subIntegrityImpact": "NONE",
          "userInteraction": "NONE",
          "valueDensity": "NOT_DEFINED",
          "vectorString": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:N/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": "LOW",
          "vulnIntegrityImpact": "NONE",
          "vulnerabilityResponseEffort": "NOT_DEFINED"
        },
        "source": "security-advisories@github.com",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-107291",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-10-08T17:25:09.227835Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-10-08T17:17:14.590",
  "references": [
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/commit/4e013c51a50659aba2adf7853bfb22bb77f6a518"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/commit/6b14c74cb281f899a2ae4fae5327111e33f60771"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/commit/7ee27e38ab2e525ca60ff1a25d16413ff989fd79"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/commit/963dec5f70d6f558997fc259356c0090cc5ea487"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/commit/de4e61515327bd80a19cd8552001c30933e6acc3"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/pull/8403"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/pull/8404"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/pull/8408"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/pull/8428"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Exploit",
        "Patch",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/pull/8429"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch",
        "Release Notes",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch",
        "Release Notes",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Mitigation",
        "Vendor Advisory"
      ],
      "url": "https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-4x9p-g9wm-8q7f"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-212"
        },
        {
          "lang": "en",
          "value": "CWE-532"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}

GHSA-4X9P-G9WM-8Q7F

Vulnerability from github – Published: 2026-10-08 16:48 – Updated: 2026-10-08 16:48

Summary

Pydantic AI OpenTelemetry instrumentation: exception events on tool and agent run spans include content when `include_content=False`

Details

Summary

The message attributes honoured the setting. Several other parts of the same spans did not, and exported content regardless of it:

Exceptions. Recorded as OpenTelemetry exception events, with their message and stack trace, on tool, agent run, model request, embedding and image generation spans, and on realtime session spans. The message of the exception carrying a tool's ModelRetry or ToolFailed feedback is the text sent back to the model, which can quote tool arguments and results. When a tool ran out of retries, the error that ended the run was chained from the last retry, so its stack trace repeated that text on the run span. Exceptions raised by tool code were recorded with their full message, as were failures of a model request, embedding or image generation, whose messages carry the provider's error response body.
The error status description. The OpenTelemetry SDK describes a span's ERROR status with the exception's type and message, so the message reached the backend a second time even where the event itself was redacted.
Instructions and the prompted-output template. The model_request_parameters attribute serialized the request's instruction parts in full, exporting the agent's instructions — both static and those built from dependencies at request time — along with the template used to prompt for structured output.

Details

Impact

Who Is Affected

Remediation

Workaround for Unpatched Versions

Credits

Severity

2.3 (Low)


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

Show details on source website

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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "pydantic-ai"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.3.4"
            },
            {
              "fixed": "1.107.6"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "pydantic-ai"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0b1"
            },
            {
              "fixed": "2.44.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "pydantic-ai-slim"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.3.4"
            },
            {
              "fixed": "1.107.6"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "pydantic-ai-slim"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.0.0b1"
            },
            {
              "fixed": "2.44.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-107291"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-212",
      "CWE-532"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-10-08T16:48:16Z",
    "nvd_published_at": null,
    "severity": "LOW"
  },
  "details": "### Summary\n\nPydantic AI\u0027s OpenTelemetry instrumentation supports `InstrumentationSettings(include_content=False)` to exclude message content \u2014 user prompts, model completions, tool call arguments and responses, and any other message content \u2014 from exported telemetry, so that agents can be monitored without sending sensitive content to the observability backend.\n\nThe message attributes honoured the setting. Several other parts of the same spans did not, and exported content regardless of it:\n\n- **Exceptions.** Recorded as OpenTelemetry exception events, with their message and stack trace, on tool, agent run, model request, embedding and image generation spans, and on realtime session spans. The message of the exception carrying a tool\u0027s `ModelRetry` or `ToolFailed` feedback is the text sent back to the model, which can quote tool arguments and results. When a tool ran out of retries, the error that ended the run was chained from the last retry, so its stack trace repeated that text on the run span. Exceptions raised by tool code were recorded with their full message, as were failures of a model request, embedding or image generation, whose messages carry the provider\u0027s error response body.\n- **The error status description.** The OpenTelemetry SDK describes a span\u0027s ERROR status with the exception\u0027s type and message, so the message reached the backend a second time even where the event itself was redacted.\n- **Instructions and the prompted-output template.** The `model_request_parameters` attribute serialized the request\u0027s instruction parts in full, exporting the agent\u0027s instructions \u2014 both static and those built from dependencies at request time \u2014 along with the template used to prompt for structured output.\n\n### Details\n\nContent reaches these places because of what they carry rather than through any single missing check, which is why the setting was applied correctly to the message attributes (`gen_ai.input.messages`, `gen_ai.tool.call.arguments`, `gen_ai.tool.call.result`, and so on) while these paths were not: the exception recording and the status description came from the OpenTelemetry SDK\u0027s defaults, and the instructions and output template were serialized as part of the request\u0027s parameters rather than treated as content.\n\n### Impact\n\nThis does not grant an attacker any new access to the agent or its data: the content is only visible to whoever can read the exported telemetry. The exposure matters when traces are exported to a destination whose audience is broader or less trusted than the agent\u0027s own data \u2014 a third-party observability vendor or a shared backend \u2014 which is the scenario `include_content=False` exists for.\n\n### Who Is Affected\n\nYou are affected if you enabled instrumentation with `include_content=False`. Instructions are exported on every successful run, so no failure is needed to be affected; the exception paths additionally require a tool to raise, or a model, embedding or image generation request to fail. Realtime sessions are affected the same way, through the errors their provider connections report. GHSA-3gh4-cghq-f8v4 stated that retries coming from tool calls were redacted correctly; that was true of the retry prompt in the message attributes but not of the exception event on the tool span. You are not affected if you don\u0027t set `include_content=False`.\n\n### Remediation\n\nUpgrade to a patched version. With `include_content=False`, exception events now record only the exception type, error statuses carry no description, and `model_request_parameters` is exported without its instruction content or output template. If you rely on this setting, consider reviewing previously exported traces for exception events, for error status descriptions, and for `model_request_parameters`.\n\n### Workaround for Unpatched Versions\n\nIf you cannot upgrade, scrub the `exception.message` and `exception.stacktrace` event attributes, the error status description, and the instruction parts and `prompted_output_template` within `model_request_parameters`, on spans emitted by Pydantic AI in your telemetry pipeline (for example with an OpenTelemetry Collector processor). Setting `include_model_request_parameters=False` alongside `include_content=False` removes both, at the cost of the rest of that attribute.\n\n### Credits\n\nReported privately by @BrianWillows, whose report covered the exception events on tool and agent run spans. The remaining paths were found while fixing it, by a test that drives content through every channel at once and checks the whole exported trace.",
  "id": "GHSA-4x9p-g9wm-8q7f",
  "modified": "2026-10-08T16:48:16Z",
  "published": "2026-10-08T16:48:16Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/security/advisories/GHSA-4x9p-g9wm-8q7f"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8403"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8404"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8408"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8428"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/pull/8429"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/4e013c51a50659aba2adf7853bfb22bb77f6a518"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/6b14c74cb281f899a2ae4fae5327111e33f60771"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/7ee27e38ab2e525ca60ff1a25d16413ff989fd79"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/963dec5f70d6f558997fc259356c0090cc5ea487"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/commit/de4e61515327bd80a19cd8552001c30933e6acc3"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/pydantic/pydantic-ai"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v1.107.6"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pydantic/pydantic-ai/releases/tag/v2.44.0"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Pydantic AI OpenTelemetry instrumentation: exception events on tool and agent run spans include content when `include_content=False`"
}

Sightings

Author	Source	Type	Date	Other

Nomenclature

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Confirmed: The vulnerability has been validated from an analyst's perspective.
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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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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.
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CVE-2026-107291 (GCVE-0-2026-107291)

BREW-OTERM-CVE-2026-107291 (GHSA-4X9P-G9WM-8Q7F)

Summary

Details

Impact

Who Is Affected

Remediation

Workaround for Unpatched Versions

Credits

FKIE_CVE-2026-107291

GHSA-4X9P-G9WM-8Q7F

Summary

Details

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Remediation

Workaround for Unpatched Versions

Credits

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