CVE-2026-59822 (GCVE-0-2026-59822)
Vulnerability from cvelistv5 – Published: 2026-07-08 19:32 – Updated: 2026-09-03 03:56Title
LiteLLM: MCP Authentication Bypass via OAuth2 Passthrough Fallback
Summary
LiteLLM is a proxy server (AI Gateway) to call LLM APIs in OpenAI (or native) format. Prior to 1.84.0, LiteLLM's MCP Streamable HTTP endpoint allowed an unauthenticated attacker to use a fabricated Authorization header to trigger an OAuth2 passthrough fallback path that replaced failed LiteLLM key validation with an empty UserAPIKeyAuth() object, allowing requests to reach MCP tooling without a valid LiteLLM key. This issue is fixed in version 1.84.0.
Severity
SSVC
Exploitation: active
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-02 00:00 UTC
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://github.com/BerriAI/litellm/security/advis… | x_refsource_CONFIRM |
| https://github.com/BerriAI/litellm/pull/26463 | x_refsource_MISC |
| https://github.com/BerriAI/litellm/commit/73869f0… | x_refsource_MISC |
| https://github.com/BerriAI/litellm/releases/tag/v1.84.0 | x_refsource_MISC |
| https://www.wiz.io/blog/ai-infrastructure-honeypot | third-party-advisory |
| https://www.cisa.gov/known-exploited-vulnerabilit… | government-resource |
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 47e54448-4335-469c-9262-cfc5965cea5b
Exploited: Yes
Timestamps
First Seen: 2026-09-02
Asserted: 2026-09-02
Scope
Notes: BerriAI LiteLLM Improper Authentication Vulnerability | Affected: BerriAI / LiteLLM | Description: BerriAI LiteLLM contains an improper authentication vulnerability in the MCP Streamable HTTP endpoint that could allow an unauthenticated attacker to establish an authenticated MCP session using an arbitrary Bearer token. | Required action: Apply mitigations in accordance with vendor instructions, ensuring compliance with CISA’s BOD 26-04 Prioritizing Security Updates Based on Risk (see URL in Notes) guidance and CISA’s “Forensics Triage Requirements” (see URL in Notes). Follow applicable BOD 26-04 guidance for cloud services or discontinue use of the product if mitigations are unavailable. Stakeholders are responsible for evaluating each asset's internet exposure and ensuring adherence to BOD 26-04 patching guidelines. | Due date: 2026-09-16 | Known ransomware campaign use (KEV): Unknown | Notes (KEV): https://github.com/BerriAI/litellm/security/advisories/GHSA-7488-6r32-c95q ; BOD 26-04: https://www.cisa.gov/news-events/directives/bod-26-04-prioritizing-security-updates-based-risk ; Forensics Triage Requirements: https://www.cisa.gov/news-events/directives/bod-26-04-implementation-guidance-prioritizing-security-updates-based-risk ; https://nvd.nist.gov/vuln/detail/CVE-2026-59822
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-287 CWE-306 |
|---|---|
| Feed | CISA Known Exploited Vulnerabilities Catalog |
| Product | LiteLLM |
| Due Date | 2026-09-16 |
| Date Added | 2026-09-02 |
| Vendorproject | BerriAI |
| Vulnerabilityname | BerriAI LiteLLM Improper Authentication Vulnerability |
| Knownransomwarecampaignuse | Unknown |
References
Created: 2026-10-02 08:09 CEST
| Updated: 2026-10-02 08:09 CEST
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: a294e7d0-dd3a-40e9-86d0-68839c8fd062
Exploited: Yes
Timestamps
First Seen: 2026-09-02
Asserted: 2026-09-02
Scope
Notes: LiteLLM: MCP Authentication Bypass via OAuth2 Passthrough Fallback | Affected: BerriAI / litellm | CVSS: 8.8 (HIGH) | EPSS: 0.00836 | Used in malware: unknown | Not yet in CISA KEV: False
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | LiteLLM: MCP Authentication Bypass via OAuth2 Passthrough Fallback |
| Cve Id | CVE-2026-59822 |
| Vendor | BerriAI |
| Ghsa Id | GHSA-7488-6R32-C95Q |
| Product | litellm |
| Added Date | 2026-09-02T17:31:01.269Z |
| Cvss Score | 8.8 |
| Epss Score | 0.00836 |
| Previous Ids | |
| Cvss Severity | HIGH |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.56171 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2026-59822 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | False |
References
Created: 2026-10-02 09:09 CEST
| Updated: 2026-10-02 09:09 CEST
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"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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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.
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.
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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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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