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Vulnerability from cleanstart
Published
2026-07-21 07:03
Modified
2026-07-20 05:28
Summary
Security fixes for CVE-2026-0994, CVE-2026-50271 applied in versions: 1.90.2-r1, 1.91.3-r0
Details
Multiple security vulnerabilities affect the litellm-database package. These issues are resolved in later releases. See references for individual vulnerability details.
{
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"credits": [],
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"details": "Multiple security vulnerabilities affect the litellm-database package. These issues are resolved in later releases. See references for individual vulnerability details.",
"id": "CLEANSTART-2026-GR10254",
"modified": "2026-07-20T05:28:42Z",
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CVE-2026-0994 (GCVE-0-2026-0994)
Vulnerability from cvelistv5 – Published: 2026-01-23 14:55 – Updated: 2026-07-15 01:23
VLAI
EPSS
VEX
Title
Denial of Service in Python Protobuf
Summary
A denial-of-service (DoS) vulnerability exists in google.protobuf.json_format.ParseDict() in Python, where the max_recursion_depth limit can be bypassed when parsing nested google.protobuf.Any messages.
Due to missing recursion depth accounting inside the internal Any-handling logic, an attacker can supply deeply nested Any structures that bypass the intended recursion limit, eventually exhausting Python’s recursion stack and causing a RecursionError.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-674 - Uncontrolled Recursion
Assigner
References
19 references
Impacted products
21 products
| Vendor | Product | Version | |
|---|---|---|---|
| Python | Protobuf |
Affected:
<=v33.4
(custom)
|
|
| Red Hat | Red Hat Ansible Automation Platform 2.5 for RHEL 8 |
Unaffected:
0:5.29.6-1.el8ap , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.5::el8 |
|
| Red Hat | Red Hat Ansible Automation Platform 2.5 for RHEL 9 |
Unaffected:
0:5.29.6-1.el9ap , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.5::el9 |
|
| Red Hat | Red Hat Ansible Automation Platform 2.6 for RHEL 9 |
Unaffected:
0:5.29.6-1.el9ap , < *
(rpm)
cpe:/a:redhat:ansible_automation_platform:2.6::el9 |
|
| Red Hat | Red Hat Enterprise Linux 10 |
Unaffected:
0:3.19.6-15.el10_1 , < *
(rpm)
cpe:/o:redhat:enterprise_linux:10.1 |
|
| Red Hat | Red Hat Enterprise Linux 10.0 Extended Update Support |
Unaffected:
0:3.19.6-11.el10_0.1 , < *
(rpm)
cpe:/o:redhat:enterprise_linux_eus:10.0 |
|
| Red Hat | Red Hat Enterprise Linux 9 |
Unaffected:
0:3.14.0-17.el9_7 , < *
(rpm)
cpe:/a:redhat:enterprise_linux:9 |
|
| Red Hat | Red Hat Enterprise Linux 9.0 Update Services for SAP Solutions |
Unaffected:
0:3.14.0-9.el9_0.1 , < *
(rpm)
cpe:/a:redhat:rhel_e4s:9.0 |
|
| Red Hat | Red Hat Enterprise Linux 9.2 Update Services for SAP Solutions |
Unaffected:
0:3.14.0-13.el9_2.1 , < *
(rpm)
cpe:/a:redhat:rhel_e4s:9.2 |
|
| Red Hat | Red Hat Enterprise Linux 9.4 Extended Update Support |
Unaffected:
0:3.14.0-13.el9_4.1 , < *
(rpm)
cpe:/a:redhat:rhel_eus:9.4 |
|
| Red Hat | Red Hat Enterprise Linux 9.6 Extended Update Support |
Unaffected:
0:3.14.0-16.el9_6.1 , < *
(rpm)
cpe:/a:redhat:rhel_eus:9.6 |
|
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1772160593 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
|
| Red Hat | Red Hat AI Inference Server 3.2 |
Unaffected:
1772160625 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.2::el9 |
|
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1778244546 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
|
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1775680192 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
|
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1775680262 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
|
| Red Hat | Red Hat AI Inference Server 3.3 |
Unaffected:
1775749857 , < *
(rpm)
cpe:/a:redhat:ai_inference_server:3.3::el9 |
|
| Red Hat | Red Hat AMQ Clients |
cpe:/a:redhat:amq_clients:2023 |
|
| Red Hat | Red Hat Ansible Automation Platform 2 |
cpe:/a:redhat:ansible_automation_platform:2 |
|
| Red Hat | Red Hat Hardened Images |
cpe:/a:redhat:hummingbird:1 |
|
| Red Hat | Red Hat OpenStack Platform 16.2 |
cpe:/a:redhat:openstack:16.2 |
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"value": "RHSA-2026:8746: Red Hat AI Inference Server 3.3"
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CVE-2026-50271 (GCVE-0-2026-50271)
Vulnerability from cvelistv5 – Published: 2026-07-17 20:42 – Updated: 2026-07-20 19:16
VLAI
EPSS
VEX
Title
dd-trace-py: Improper parsing of W3C baggage headers may lead to DoS
Summary
Datadog dd-trace-py is the Datadog Python APM client. Prior to 4.8.2, Datadog tracing libraries that implement W3C baggage propagation parse incoming baggage HTTP headers without enforcing DD_TRACE_BAGGAGE_MAX_ITEMS or DD_TRACE_BAGGAGE_MAX_BYTES limits on the extract path. A remote, unauthenticated attacker can send a request whose baggage header contains an arbitrarily large number of comma-separated key-value pairs or a single very large value, causing unbounded CPU and memory consumption and enabling a remote denial of service against HTTP services with baggage propagation enabled. This issue is fixed in version 4.8.2.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/DataDog/dd-trace-py/security/a… | x_refsource_CONFIRM |
| https://github.com/DataDog/dd-trace-py/pull/17926 | x_refsource_MISC |
| https://github.com/DataDog/dd-trace-py/commit/9c8… | x_refsource_MISC |
| https://github.com/DataDog/dd-trace-py/releases/t… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| DataDog | dd-trace-py |
Affected:
< 4.8.2
|
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Loading…
Trend slope:
-
(linear fit over daily sighting counts)
Show additional events:
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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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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.
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