CVE-2026-45758 (GCVE-0-2026-45758)
Vulnerability from cvelistv5 – Published: 2026-06-05 19:35 – Updated: 2026-06-08 16:21
VLAI
Title
Malicious code in guardrails-ai 0.10.1 (supply chain compromise)
Summary
Guardrails AI is a Python framework that helps build AI applications. On May 11, 2026 at approximately 6:00 PM Pacific, an attacker published a malicious version of `guardrails-ai` (0.10.1) to PyPI. Aany user who installed `guardrails-ai==0.10.1` from PyPI on May 11, 2026 may be affected. Security researchers identified the malicious package within approximately 2 hours of publication, and PyPI quarantined the repository. Based on our telemetry, Guardrails AI maintainers have observed no requests to Guardrails AI infrastructure originating from the malicious 0.10.1 version, and a review of system and access logs has produced no evidence of user data exfiltration through their systems. Users should upgrade to version 0.10.2 or downgrade to version 0.10.0, both of which are unaffected. Those who installed version 0.10.1 should rotate any credentials accessible from their machine (GitHub PATs, cloud provider keys, package registry tokens, API keys) and audit their GitHub account for unauthorized workflows or repositories.
Severity
9.6 (Critical)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator (v2.0.3)
CWE
- CWE-506 - Embedded Malicious Code
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/guardrails-ai/guardrails/secur… | x_refsource_CONFIRM |
| https://github.com/guardrails-ai/guardrails/issues/1473 | x_refsource_MISC |
| https://github.com/guardrails-ai/guardrails/blob/… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| guardrails-ai | guardrails |
Affected:
= 0.10.1
|
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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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