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Fencer Intel
high 8.6

GHSA-69x8-hrgq-fjj8 json

LiteLLM: Password hash exposure and pass-the-hash authentication bypass

published 7mo ago modified 2mo ago

cvss
8.6
version 4.0, the maintainers
cisa kev
Not listed
not in CISA's catalog
epss
—
no score, EPSS covers CVEs only
public exploits
0
none known

Summary

### Impact

Three issues combine into a full authentication bypass chain:

1. Weak hashing: User passwords are stored as unsalted SHA-256 hashes, making them vulnerable to rainbow table attacks and trivially identifying users with identical passwords. 2. Hash exposure: Multiple API endpoints (/user/info, /user/update, /spend/users) return the password hash field in responses to any authenticated user regardless of role. Plaintext passwords could also potentially be exposed in certain scenarios. 4. Pass-the-hash: The /v2/login endpoint accepts the raw SHA-256 hash as a valid password without re-hashing, allowing direct login with a stolen

An already authenticated user can retrieve another user's password hash from the API and use it to log in as that user. This enables full privilege escalation in three HTTP requests.

### Patches

Fixed in v1.83.0. Passwords are now hashed with scrypt (random 16-byte salt, n=16384, r=8, p=1). Password hashes are stripped from all API responses. Existing SHA-256 hashes are transparently migrated on next login.

Patch / fix

  • pypi litellm 1.83.0

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CVSS scores

assigned by version score vector
the maintainers 4.0 8.6 CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N

Affected packages

ecosystem package affected fixed in
pypi litellm
<1.83.0
1.83.0

Classification

Weakness
  • CWE-200 Exposure of Sensitive Information to an Unauthorized Actor
  • CWE-327 Use of a Broken or Risky Cryptographic Algorithm
  • CWE-916 Use of Password Hash With Insufficient Computational Effort

References

Sources

Fencer Intel keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.

The maintainers of BerriAI/litellm published their own advisory on GitHub. Reviewed sources take precedence over it.